Integrated analysis of DNA methylation and gene expression reveals specific signaling pathways associated with platinum resistance in ovarian cancer

Directory of Open Access Journals (Sweden)

Chung Jae

2009-06-01

Full Text Available Abstract Background Cisplatin and carboplatin are the primary first-line therapies for the treatment of ovarian cancer. However, resistance to these platinum-based drugs occurs in the large majority of initially responsive tumors, resulting in fully chemoresistant, fatal disease. Although the precise mechanism(s underlying the development of platinum resistance in late-stage ovarian cancer patients currently remains unknown, CpG-island (CGI methylation, a phenomenon strongly associated with aberrant gene silencing and ovarian tumorigenesis, may contribute to this devastating condition. Methods To model the onset of drug resistance, and investigate DNA methylation and gene expression alterations associated with platinum resistance, we treated clonally derived, drug-sensitive A2780 epithelial ovarian cancer cells with increasing concentrations of cisplatin. After several cycles of drug selection, the isogenic drug-sensitive and -resistant pairs were subjected to global CGI methylation and mRNA expression microarray analyses. To identify chemoresistance-associated, biological pathways likely impacted by DNA methylation, promoter CGI methylation and mRNA expression profiles were integrated and subjected to pathway enrichment analysis. Results Promoter CGI methylation revealed a positive association (Spearman correlation of 0.99 between the total number of hypermethylated CGIs and GI50 values (i.e., increased drug resistance following successive cisplatin treatment cycles. In accord with that result, chemoresistance was reversible by DNA methylation inhibitors. Pathway enrichment analysis revealed hypermethylation-mediated repression of cell adhesion and tight junction pathways and hypomethylation-mediated activation of the cell growth-promoting pathways PI3K/Akt, TGF-beta, and cell cycle progression, which may contribute to the onset of chemoresistance in ovarian cancer cells. Conclusion Selective epigenetic disruption of distinct biological

Integrated pathway clusters with coherent biological themes for target prioritisation.

Directory of Open Access Journals (Sweden)

Yi-An Chen

Full Text Available Prioritising candidate genes for further experimental characterisation is an essential, yet challenging task in biomedical research. One way of achieving this goal is to identify specific biological themes that are enriched within the gene set of interest to obtain insights into the biological phenomena under study. Biological pathway data have been particularly useful in identifying functional associations of genes and/or gene sets. However, biological pathway information as compiled in varied repositories often differs in scope and content, preventing a more effective and comprehensive characterisation of gene sets. Here we describe a new approach to constructing biologically coherent gene sets from pathway data in major public repositories and employing them for functional analysis of large gene sets. We first revealed significant overlaps in gene content between different pathways and then defined a clustering method based on the shared gene content and the similarity of gene overlap patterns. We established the biological relevance of the constructed pathway clusters using independent quantitative measures and we finally demonstrated the effectiveness of the constructed pathway clusters in comparative functional enrichment analysis of gene sets associated with diverse human diseases gathered from the literature. The pathway clusters and gene mappings have been integrated into the TargetMine data warehouse and are likely to provide a concise, manageable and biologically relevant means of functional analysis of gene sets and to facilitate candidate gene prioritisation.

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

Directory of Open Access Journals (Sweden)

Jose A Santiago

Full Text Available Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level.Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP, previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS and the Prognostic Biomarker Study (PROBE, revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients.These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

Science.gov (United States)

Santiago, Jose A; Potashkin, Judith A

2013-01-01

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that

ComPath: comparative enzyme analysis and annotation in pathway/subsystem contexts

Directory of Open Access Journals (Sweden)

Kim Sun

2008-03-01

Full Text Available Abstract Background Once a new genome is sequenced, one of the important questions is to determine the presence and absence of biological pathways. Analysis of biological pathways in a genome is a complicated task since a number of biological entities are involved in pathways and biological pathways in different organisms are not identical. Computational pathway identification and analysis thus involves a number of computational tools and databases and typically done in comparison with pathways in other organisms. This computational requirement is much beyond the capability of biologists, so information systems for reconstructing, annotating, and analyzing biological pathways are much needed. We introduce a new comparative pathway analysis workbench, ComPath, which integrates various resources and computational tools using an interactive spreadsheet-style web interface for reliable pathway analyses. Results ComPath allows users to compare biological pathways in multiple genomes using a spreadsheet style web interface where various sequence-based analysis can be performed either to compare enzymes (e.g. sequence clustering and pathways (e.g. pathway hole identification, to search a genome for de novo prediction of enzymes, or to annotate a genome in comparison with reference genomes of choice. To fill in pathway holes or make de novo enzyme predictions, multiple computational methods such as FASTA, Whole-HMM, CSR-HMM (a method of our own introduced in this paper, and PDB-domain search are integrated in ComPath. Our experiments show that FASTA and CSR-HMM search methods generally outperform Whole-HMM and PDB-domain search methods in terms of sensitivity, but FASTA search performs poorly in terms of specificity, detecting more false positive as E-value cutoff increases. Overall, CSR-HMM search method performs best in terms of both sensitivity and specificity. Gene neighborhood and pathway neighborhood (global network visualization tools can be used

Integrated bioinformatics analysis reveals key candidate genes and pathways in breast cancer.

Science.gov (United States)

Wang, Yuzhi; Zhang, Yi; Huang, Qian; Li, Chengwen

2018-04-19

Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non‑tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t‑tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein‑protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM‑receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator‑activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2‑a, baculoviral inhibitor of apoptosis repeat‑containing protein 5, cyclin‑dependent kinase 1, G2/mitotic‑specific cyclin‑B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid‑body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide

Fostering development of nursing practices to support integrated care when implementing integrated care pathways: what levers to use?

Science.gov (United States)

Longpré, Caroline; Dubois, Carl-Ardy

2017-11-29

Care integration has been the focus of recent health system reforms. Given their functions at all levels of the care continuum, nurses have a substantial and primordial role to play in such integration processes. The aim of this study was to identify levers and strategies that organizations can use to support the development of a nursing practice aligned with the requirements of care integration in a health and social services centre (HSSC) in Quebec. The research design was a cross-sectional descriptive qualitative study based on a single case study with nested levels of analysis. The case was a public, multi-disciplinary HSSC in a semi-urban region of Quebec. Semi-structured interviews with 37 persons (nurses, professionals, managers, administrators) allowed for data saturation and ensured theoretical representation by covering four care pathways constituting different care integration contexts. Analysis involved four steps: preparing a predetermined list of codes based on the reference framework developed by Minkman (2011); coding transcript content; developing general and summary matrices to group observations for each care pathway; and creating a general model showing the overall results for the four pathways. The organization's capacity for response with regard to developing an integrated system of services resulted in two types of complementary interventions. The first involved investing in key resources and renewing organizational structures; the second involved deploying a series of organizational and clinical-administrative processes. In resource terms, integration efforts resulted in setting up new strategic services, re-arranging physical infrastructures, and deploying new technological resources. Organizational and clinical-administrative processes to promote integration involved renewing governance, improving the flow of care pathways, fostering continuous quality improvement, developing new roles, promoting clinician collaboration, and strengthening

Integrative Network Analysis Unveils Convergent Molecular Pathways in Parkinson's Disease and Diabetes

OpenAIRE

Santiago, Jose A.; Potashkin, Judith A.

2013-01-01

Background Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. ...

Integrated care pathways for airway diseases (AIRWAYS-ICPs)

NARCIS (Netherlands)

Bousquet, J.; Addis, A.; Adcock, I.; Agache, I.; Agusti, A.; Alonso, A.; Annesi-Maesano, I.; Anto, J. M.; Bachert, C.; Baena-Cagnani, C. E.; Bai, C.; Baigenzhin, A.; Barbara, C.; Barnes, P. J.; Bateman, E. D.; Beck, L.; Bedbrook, A.; Bel, E. H.; Benezet, O.; Bennoor, K. S.; Benson, M.; Bernabeu-Wittel, M.; Bewick, M.; Bindslev-Jensen, C.; Blain, H.; Blasi, F.; Bonini, M.; Bonini, S.; Boulet, L. P.; Bourdin, A.; Bourret, R.; Bousquet, P. J.; Brightling, C. E.; Briggs, A.; Brozek, J.; Buhl, R.; Bush, A.; Caimmi, D.; Calderon, M.; Calverley, P.; Camargos, P. A.; Camuzat, T.; Canonica, G. W.; Carlsen, K. H.; Casale, T. B.; Cazzola, M.; Cepeda Sarabia, A. M.; Cesario, A.; Chen, Y. Z.; Chkhartishvili, E.; Chavannes, N. H.; Chiron, R.; Chuchalin, A.; Chung, K. F.; Cox, L.; Crooks, G.; Crooks, M. G.; Cruz, A. A.; Custovic, A.; Dahl, R.; Dahlen, S. E.; de Blay, F.; Dedeu, T.; Deleanu, D.; Demoly, P.; Devillier, P.; Didier, A.; Dinh-Xuan, A. T.; Djukanovic, R.; Dokic, D.; Douagui, H.; Dubakiene, R.; Eglin, S.; Elliot, F.; Emuzyte, R.; Fabbri, L.; Fink Wagner, A.; Fletcher, M.; Fokkens, W. J.; Fonseca, J.; Franco, A.; Frith, P.; Furber, A.; Gaga, M.; Garcés, J.; Garcia-Aymerich, J.; Gamkrelidze, A.; Gonzales-Diaz, S.; Gouzi, F.; Guzmán, M. A.; Haahtela, T.; Harrison, D.; Hayot, M.; Heaney, L. G.; Heinrich, J.; Hellings, P. W.; Hooper, J.; Humbert, M.; Hyland, M.; Iaccarino, G.; Jakovenko, D.; Jardim, J. R.; Jeandel, C.; Jenkins, C.; Johnston, S. L.; Jonquet, O.; Joos, G.; Jung, K. S.; Kalayci, O.; Karunanithi, S.; Keil, T.; Khaltaev, N.; Kolek, V.; Kowalski, M. L.; Kull, I.; Kuna, P.; Kvedariene, V.; Le, L. T.; Lodrup Carlsen, K. C.; Louis, R.; MacNee, W.; Mair, A.; Majer, I.; Manning, P.; de Manuel Keenoy, E.; Masjedi, M. R.; Melen, E.; Melo-Gomes, E.; Menzies-Gow, A.; Mercier, G.; Mercier, J.; Michel, J. P.; Miculinic, N.; Mihaltan, F.; Milenkovic, B.; Molimard, M.; Momas, I.; Montilla-Santana, A.; Morais-Almeida, M.; Morgan, M.; N'Diaye, M.; Nafti, S.; Nekam, K.; Neou, A.; Nicod, L.; O'Hehir, R.; Ohta, K.; Paggiaro, P.; Palkonen, S.; Palmer, S.; Papadopoulos, N. G.; Papi, A.; Passalacqua, G.; Pavord, I.; Pigearias, B.; Plavec, D.; Postma, D. S.; Price, D.; Rabe, K. F.; Radier Pontal, F.; Redon, J.; Rennard, S.; Roberts, J.; Robine, J. M.; Roca, J.; Roche, N.; Rodenas, F.; Roggeri, A.; Rolland, C.; Rosado-Pinto, J.; Ryan, D.; Samolinski, B.; Sanchez-Borges, M.; Schünemann, H. J.; Sheikh, A.; Shields, M.; Siafakas, N.; Sibille, Y.; Similowski, T.; Small, I.; Sola-Morales, O.; Sooronbaev, T.; Stelmach, R.; Sterk, P. J.; Stiris, T.; Sud, P.; Tellier, V.; To, T.; Todo-Bom, A.; Triggiani, M.; Valenta, R.; Valero, A. L.; Valiulis, A.; Valovirta, E.; van Ganse, E.; Vandenplas, O.; Vasankari, T.; Vestbo, J.; Vezzani, G.; Viegi, G.; Visier, L.; Vogelmeier, C.; Vontetsianos, T.; Wagstaff, R.; Wahn, U.; Wallaert, B.; Whalley, B.; Wickman, M.; Williams, D. M.; Wilson, N.; Yawn, B. P.; Yiallouros, P. K.; Yorgancioglu, A.; Yusuf, O. M.; Zar, H. J.; Zhong, N.; Zidarn, M.; Zuberbier, T.

2014-01-01

The objective of Integrated Care Pathways for Airway Diseases (AIRWAYS-ICPs) is to launch a collaboration to develop multi-sectoral care pathways for chronic respiratory diseases in European countries and regions. AIRWAYS-ICPs has strategic relevance to the European Union Health Strategy and will

Integrated care pathways for airway diseases (AIRWAYS-ICPs)

NARCIS (Netherlands)

Bousquet, J.; Addis, A.; Adcock, I.; Agache, I.; Agusti, A.; Alonso, A.; Annesi-Maesano, I.; Anto, J. M.; Bachert, C.; Baena-Cagnani, C. E.; Bai, C.; Baigenzhin, A.; Barbara, C.; Barnes, P. J.; Bateman, E. D.; Beck, L.; Bedbrook, A.; Bel, E. H.; Benezet, O.; Bennoor, K. S.; Benson, M.; Bernabeu-Wittel, M.; Bewick, M.; Bindslev-Jensen, C.; Blain, H.; Blasi, F.; Bonini, M.; Bonini, S.; Boulet, L. P.; Bourdin, A.; Bourret, R.; Bousquet, P. J.; Brightling, C. E.; Briggs, A.; Brozek, J.; Buh, R.; Bush, A.; Caimmi, D.; Calderon, M.; Calverley, P.; Camargos, P. A.; Camuzat, T.; Canonica, G. W.; Carlsen, K. H.; Casale, T. B.; Cazzola, M.; Sarabia, A. M. Cepeda; Cesario, A.; Chen, Y. Z.; Chkhartishvili, E.; Chavannes, N. H.; Chiron, R.; Chuchalin, A.; Chung, K. F.; Cox, L.; Crooks, G.; Crooks, M. G.; Cruz, A. A.; Custovic, A.; Dahl, R.; Dahlen, S. E.; De Blay, F.; Dedeu, T.; Deleanu, D.; Demoly, P.; Devillier, P.; Didier, A.; Dinh-Xuan, A. T.; Djukanovic, R.; Dokic, D.; Douagui, H.; Dubakiene, R.; Eglin, S.; Elliot, F.; Emuzyte, R.; Fabbri, L.; Wagner, A. Fink; Fletcher, M.; Fokkens, W. J.; Fonseca, J.; Franco, A.; Frith, P.; Furber, A.; Gaga, M.; Garces, J.; Garcia-Aymerich, J.; Gamkrelidze, A.; Gonzales-Diaz, S.; Gouzi, F.; Guzman, M. A.; Haahtela, T.; Harrison, D.; Hayot, M.; Heaney, L. G.; Heinrich, J.; Hellings, P. W.; Hooper, J.; Humbert, M.; Hyland, M.; Iaccarino, G.; Jakovenko, D.; Jardim, J. R.; Jeandel, C.; Jenkins, C.; Johnston, S. L.; Jonquet, O.; Joos, G.; Jung, K. S.; Kalayci, O.; Karunanithi, S.; Keil, T.; Khaltaev, N.; Kolek, V.; Kowalski, M. L.; Kull, I.; Kuna, P.; Kvedariene, V.; Le, L. T.; Carlsen, K. C. Lodrup; Louis, R.; MacNee, W.; Mair, A.; Majer, I.; Manning, P.; Keenoy, E. de Manuel; Masjedi, M. R.; Meten, E.; Melo-Gomes, E.; Menzies-Gow, A.; Mercier, G.; Mercier, J.; Michel, J. P.; Miculinic, N.; Mihaltan, F.; Milenkovic, B.; Molimard, M.; Mamas, I.; Montilla-Santana, A.; Morais-Almeida, M.; Morgan, M.; N'Diaye, M.; Nafti, S.; Nekam, K.; Neou, A.; Nicod, L.; O'Hehir, R.; Ohta, K.; Paggiaro, P.; Palkonen, S.; Palmer, S.; Papadopoulos, N. G.; Papi, A.; Passalacqua, G.; Pavord, I.; Pigearias, B.; Plavec, D.; Postma, D. S.; Price, D.; Rabe, K. F.; Pontal, F. Radier; Redon, J.; Rennard, S.; Roberts, J.; Robine, J. M.; Roca, J.; Roche, N.; Rodenas, F.; Roggeri, A.; Rolland, C.; Rosado-Pinto, J.; Ryan, D.; Samolinski, B.; Sanchez-Borges, M.; Schunemann, H. J.; Sheikh, A.; Shields, M.; Siafakas, N.; Sibille, Y.; Similowski, T.; Small, I.; Sola-Morales, O.; Sooronbaev, T.; Stelmach, R.; Sterk, P. J.; Stiris, T.; Sud, P.; Tellier, V.; To, T.; Todo-Bom, A.; Triggiani, M.; Valenta, R.; Valero, A. L.; Valiulis, A.; Valovirta, E.; Van Ganse, E.; Vandenplas, O.; Vasankari, T.; Vestbo, J.; Vezzani, G.; Viegi, G.; Visier, L.; Vogelmeier, C.; Vontetsianos, T.; Wagstaff, R.; Wahn, U.; Wallaert, B.; Whalley, B.; Wickman, M.; Williams, D. M.; Wilson, N.; Yawn, B. P.; Yiallouros, P. K.; Yorgancioglu, A.; Yusuf, O. M.; Zar, H. J.; Zhong, N.; Zidarn, M.; Zuberbier, T.

The objective of Integrated Care Pathways for Airway Diseases (AIRWAYS-ICPs) is to launch a collaboration to develop multi-sectoral care pathways for chronic respiratory diseases in European countries and regions. AIRWAYS-ICPs has strategic relevance to the European Union Health Strategy and will

Exploring the Unfolding Pathway of Maltose Binding Proteins: An Integrated Computational Approach

KAUST Repository

Guardiani, Carlo; Marino, Daniele Di; Tramontano, Anna; Chinappi, Mauro; Cecconi, Fabio

2014-01-01

© 2014 American Chemical Society. Recent single-molecule force spectroscopy experiments on the Maltose Binding Proteins (MBPs) identified four stable structural units, termed unfoldons, that resist mechanical stress and determine the intermediates of the unfolding pathway. In this work, we analyze the topological origin and the dynamical role of the unfoldons using an integrated approach which combines a graph-theoretical analysis of the interaction network of the MBP native-state with steered molecular dynamics simulations. The topological analysis of the native state, while revealing the structural nature of the unfoldons, provides a framework to interpret the MBP mechanical unfolding pathway. Indeed, the experimental pathway can be effectively predicted by means of molecular dynamics simulations with a simple topology-based and low-resolution model of the MBP. The results obtained from the coarse-grained approach are confirmed and further refined by all-atom molecular dynamics.

Exploring the Unfolding Pathway of Maltose Binding Proteins: An Integrated Computational Approach

KAUST Repository

Guardiani, Carlo

2014-09-09

© 2014 American Chemical Society. Recent single-molecule force spectroscopy experiments on the Maltose Binding Proteins (MBPs) identified four stable structural units, termed unfoldons, that resist mechanical stress and determine the intermediates of the unfolding pathway. In this work, we analyze the topological origin and the dynamical role of the unfoldons using an integrated approach which combines a graph-theoretical analysis of the interaction network of the MBP native-state with steered molecular dynamics simulations. The topological analysis of the native state, while revealing the structural nature of the unfoldons, provides a framework to interpret the MBP mechanical unfolding pathway. Indeed, the experimental pathway can be effectively predicted by means of molecular dynamics simulations with a simple topology-based and low-resolution model of the MBP. The results obtained from the coarse-grained approach are confirmed and further refined by all-atom molecular dynamics.

A novel bi-level meta-analysis approach: applied to biological pathway analysis.

Science.gov (United States)

Nguyen, Tin; Tagett, Rebecca; Donato, Michele; Mitrea, Cristina; Draghici, Sorin

2016-02-01

The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study. We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis. The R scripts are available on demand from the authors. sorin@wayne.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

User Interface Requirements for Web-Based Integrated Care Pathways: Evidence from the Evaluation of an Online Care Pathway Investigation Tool.

Science.gov (United States)

Balatsoukas, Panos; Williams, Richard; Davies, Colin; Ainsworth, John; Buchan, Iain

2015-11-01

Integrated care pathways (ICPs) define a chronological sequence of steps, most commonly diagnostic or treatment, to be followed in providing care for patients. Care pathways help to ensure quality standards are met and to reduce variation in practice. Although research on the computerisation of ICP progresses, there is still little knowledge on what are the requirements for designing user-friendly and usable electronic care pathways, or how users (normally health care professionals) interact with interfaces that support design, analysis and visualisation of ICPs. The purpose of the study reported in this paper was to address this gap by evaluating the usability of a novel web-based tool called COCPIT (Collaborative Online Care Pathway Investigation Tool). COCPIT supports the design, analysis and visualisation of ICPs at the population level. In order to address the aim of this study, an evaluation methodology was designed based on heuristic evaluations and a mixed method usability test. The results showed that modular visualisation and direct manipulation of information related to the design and analysis of ICPs is useful for engaging and stimulating users. However, designers should pay attention to issues related to the visibility of the system status and the match between the system and the real world, especially in relation to the display of statistical information about care pathways and the editing of clinical information within a care pathway. The paper concludes with recommendations for interface design.

Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

Directory of Open Access Journals (Sweden)

Wu Xiaogang

2012-06-01

Full Text Available In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease, and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI database, and pathway enrichment from the human pathway database (HPD. We use a recently-published microarray dataset (GSE24215 related to insulin resistance and type 2 diabetes (T2D as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

Science.gov (United States)

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Integrative pathway knowledge bases as a tool for systems molecular medicine.

Science.gov (United States)

Liang, Mingyu

2007-08-20

There exists a sense of urgency to begin to generate a cohesive assembly of biomedical knowledge as the pace of knowledge accumulation accelerates. The urgency is in part driven by the emergence of systems molecular medicine that emphasizes the combination of systems analysis and molecular dissection in the future of medical practice and research. A potentially powerful approach is to build integrative pathway knowledge bases that link organ systems function with molecules.

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens.

Science.gov (United States)

Zhou, Hufeng; Jin, Jingjing; Zhang, Haojun; Yi, Bo; Wozniak, Michal; Wong, Limsoon

2012-01-01

Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and

GenMAPP 2: new features and resources for pathway analysis

Directory of Open Access Journals (Sweden)

Dahlquist Kam D

2007-06-01

Full Text Available Abstract Background Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses. Results To address the growing needs of the microarray community we have released version 2 of Gene Map Annotator and Pathway Profiler (GenMAPP, a new GenMAPP database schema, and integrated resources for pathway analysis. We have redesigned the GenMAPP database to support multiple gene annotations and species as well as custom species database creation for a potentially unlimited number of species. We have expanded our pathway resources by utilizing homology information to translate pathway content between species and extending existing pathways with data derived from conserved protein interactions and coexpression. We have implemented a new mode of data visualization to support analysis of complex data, including time-course, single nucleotide polymorphism (SNP, and splicing. GenMAPP version 2 also offers innovative ways to display and share data by incorporating HTML export of analyses for entire sets of pathways as organized web pages. Conclusion GenMAPP version 2 provides a means to rapidly interrogate complex experimental data for pathway-level changes in a diverse range of organisms.

White matter integrity deficits in prefrontal-amygdala pathways in Williams syndrome.

Science.gov (United States)

Avery, Suzanne N; Thornton-Wells, Tricia A; Anderson, Adam W; Blackford, Jennifer Urbano

2012-01-16

Williams syndrome is a neurodevelopmental disorder associated with significant non-social fears. Consistent with this elevated non-social fear, individuals with Williams syndrome have an abnormally elevated amygdala response when viewing threatening non-social stimuli. In typically-developing individuals, amygdala activity is inhibited through dense, reciprocal white matter connections with the prefrontal cortex. Neuroimaging studies suggest a functional uncoupling of normal prefrontal-amygdala inhibition in individuals with Williams syndrome, which might underlie both the extreme amygdala activity and non-social fears. This functional uncoupling might be caused by structural deficits in underlying white matter pathways; however, prefrontal-amygdala white matter deficits have yet to be explored in Williams syndrome. We used diffusion tensor imaging to investigate prefrontal-amygdala white matter integrity differences in individuals with Williams syndrome and typically-developing controls with high levels of non-social fear. White matter pathways between the amygdala and several prefrontal regions were isolated using probabilistic tractography. Within each pathway, we tested for between-group differences in three measures of white matter integrity: fractional anisotropy (FA), radial diffusivity (RD), and parallel diffusivity (λ(1)). Individuals with Williams syndrome had lower FA, compared to controls, in several of the prefrontal-amygdala pathways investigated, indicating a reduction in white matter integrity. Lower FA in Williams syndrome was explained by significantly higher RD, with no differences in λ(1), suggestive of lower fiber density or axon myelination in prefrontal-amygdala pathways. These results suggest that deficits in the structural integrity of prefrontal-amygdala white matter pathways might underlie the increased amygdala activity and extreme non-social fears observed in Williams syndrome. Copyright © 2011 Elsevier Inc. All rights reserved.

How Effective Are Clinical Pathways With and Without Online Peer-Review? An Analysis of Bone Metastases Pathway in a Large, Integrated National Cancer Institute-Designated Comprehensive Cancer Center Network

Energy Technology Data Exchange (ETDEWEB)

Beriwal, Sushil, E-mail: beriwals@upmc.edu [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, PA (United States); Rajagopalan, Malolan S.; Flickinger, John C.; Rakfal, Susan M. [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, PA (United States); Rodgers, Edwin [Via Oncology, Pittsburgh, PA (United States); Heron, Dwight E. [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, PA (United States)

2012-07-15

Purpose: Clinical pathways are an important tool used to manage the quality in health care by standardizing processes. This study evaluated the impact of the implementation of a peer-reviewed clinical pathway in a large, integrated National Cancer Institute-Designated Comprehensive Cancer Center Network. Methods: In 2003, we implemented a clinical pathway for the management of bone metastases with palliative radiation therapy. In 2009, we required the entry of management decisions into an online tool that records pathway choices. The pathway specified 1 or 5 fractions for symptomatic bone metastases with the option of 10-14 fractions for certain clinical situations. The data were obtained from 13 integrated sites (3 central academic, 10 community locations) from 2003 through 2010. Results: In this study, 7905 sites were treated with 64% of courses delivered in community practice and 36% in academic locations. Academic practices were more likely than community practices to treat with 1-5 fractions (63% vs. 23%; p < 0.0001). The number of delivered fractions decreased gradually from 2003 to 2010 for both academic and community practices (p < 0.0001); however, greater numbers of fractions were selected more often in community practices (p < 0.0001). Using multivariate logistic regression, we found that a significantly greater selection of 1-5 fractions developed after implementation online pathway monitoring (2009) with an odds ratio of 1.2 (confidence interval, 1.1-1.4) for community and 1.3 (confidence interval, 1.1-1.6) for academic practices. The mean number of fractions also decreased after online peer review from 6.3 to 6.0 for academic (p = 0.07) and 9.4 to 9.0 for community practices (p < 0.0001). Conclusion: This is one of the first studies to examine the efficacy of a clinical pathway for radiation oncology in an integrated cancer network. Clinical pathway implementation appears to be effective in changing patterns of care, particularly with online clinical

How Effective Are Clinical Pathways With and Without Online Peer-Review? An Analysis of Bone Metastases Pathway in a Large, Integrated National Cancer Institute–Designated Comprehensive Cancer Center Network

International Nuclear Information System (INIS)

Beriwal, Sushil; Rajagopalan, Malolan S.; Flickinger, John C.; Rakfal, Susan M.; Rodgers, Edwin; Heron, Dwight E.

2012-01-01

Purpose: Clinical pathways are an important tool used to manage the quality in health care by standardizing processes. This study evaluated the impact of the implementation of a peer-reviewed clinical pathway in a large, integrated National Cancer Institute–Designated Comprehensive Cancer Center Network. Methods: In 2003, we implemented a clinical pathway for the management of bone metastases with palliative radiation therapy. In 2009, we required the entry of management decisions into an online tool that records pathway choices. The pathway specified 1 or 5 fractions for symptomatic bone metastases with the option of 10–14 fractions for certain clinical situations. The data were obtained from 13 integrated sites (3 central academic, 10 community locations) from 2003 through 2010. Results: In this study, 7905 sites were treated with 64% of courses delivered in community practice and 36% in academic locations. Academic practices were more likely than community practices to treat with 1–5 fractions (63% vs. 23%; p < 0.0001). The number of delivered fractions decreased gradually from 2003 to 2010 for both academic and community practices (p < 0.0001); however, greater numbers of fractions were selected more often in community practices (p < 0.0001). Using multivariate logistic regression, we found that a significantly greater selection of 1–5 fractions developed after implementation online pathway monitoring (2009) with an odds ratio of 1.2 (confidence interval, 1.1–1.4) for community and 1.3 (confidence interval, 1.1–1.6) for academic practices. The mean number of fractions also decreased after online peer review from 6.3 to 6.0 for academic (p = 0.07) and 9.4 to 9.0 for community practices (p < 0.0001). Conclusion: This is one of the first studies to examine the efficacy of a clinical pathway for radiation oncology in an integrated cancer network. Clinical pathway implementation appears to be effective in changing patterns of care, particularly with

Floral pathway integrator gene expression mediates gradual transmission of environmental and endogenous cues to flowering time.

Science.gov (United States)

van Dijk, Aalt D J; Molenaar, Jaap

2017-01-01

The appropriate timing of flowering is crucial for the reproductive success of plants. Hence, intricate genetic networks integrate various environmental and endogenous cues such as temperature or hormonal statues. These signals integrate into a network of floral pathway integrator genes. At a quantitative level, it is currently unclear how the impact of genetic variation in signaling pathways on flowering time is mediated by floral pathway integrator genes. Here, using datasets available from literature, we connect Arabidopsis thaliana flowering time in genetic backgrounds varying in upstream signalling components with the expression levels of floral pathway integrator genes in these genetic backgrounds. Our modelling results indicate that flowering time depends in a quite linear way on expression levels of floral pathway integrator genes. This gradual, proportional response of flowering time to upstream changes enables a gradual adaptation to changing environmental factors such as temperature and light.

Floral pathway integrator gene expression mediates gradual transmission of environmental and endogenous cues to flowering time

Directory of Open Access Journals (Sweden)

Aalt D.J. van Dijk

2017-04-01

Full Text Available The appropriate timing of flowering is crucial for the reproductive success of plants. Hence, intricate genetic networks integrate various environmental and endogenous cues such as temperature or hormonal statues. These signals integrate into a network of floral pathway integrator genes. At a quantitative level, it is currently unclear how the impact of genetic variation in signaling pathways on flowering time is mediated by floral pathway integrator genes. Here, using datasets available from literature, we connect Arabidopsis thaliana flowering time in genetic backgrounds varying in upstream signalling components with the expression levels of floral pathway integrator genes in these genetic backgrounds. Our modelling results indicate that flowering time depends in a quite linear way on expression levels of floral pathway integrator genes. This gradual, proportional response of flowering time to upstream changes enables a gradual adaptation to changing environmental factors such as temperature and light.

Electronic patient information systems and care pathways: the organisational challenges of implementation and integration.

Science.gov (United States)

Dent, Mike; Tutt, Dylan

2014-09-01

Our interest here is with the 'marriage' of e-patient information systems with care pathways in order to deliver integrated care. We report on the development and implementation of four such pathways within two National Health Service primary care trusts in England: (a) frail elderly care, (b) stroke care, (c) diabetic retinopathy screening and (d) intermediate care. The pathways were selected because each represents a different type of information and data 'couplings', in terms of task interdependency with some pathways/systems reflecting more complex coordinating patterns than others. Our aim here is identify and explain how health professionals and information specialists in two organisational National Health Service primary care trusts organisationally construct and use such systems and, in particular, the implications this has for issues of professional and managerial control and autonomy. The article is informed by an institutionalist analysis. © The Author(s) 2013.

PathText: a text mining integrator for biological pathway visualizations

Science.gov (United States)

Kemper, Brian; Matsuzaki, Takuya; Matsuoka, Yukiko; Tsuruoka, Yoshimasa; Kitano, Hiroaki; Ananiadou, Sophia; Tsujii, Jun'ichi

2010-01-01

Motivation: Metabolic and signaling pathways are an increasingly important part of organizing knowledge in systems biology. They serve to integrate collective interpretations of facts scattered throughout literature. Biologists construct a pathway by reading a large number of articles and interpreting them as a consistent network, but most of the models constructed currently lack direct links to those articles. Biologists who want to check the original articles have to spend substantial amounts of time to collect relevant articles and identify the sections relevant to the pathway. Furthermore, with the scientific literature expanding by several thousand papers per week, keeping a model relevant requires a continuous curation effort. In this article, we present a system designed to integrate a pathway visualizer, text mining systems and annotation tools into a seamless environment. This will enable biologists to freely move between parts of a pathway and relevant sections of articles, as well as identify relevant papers from large text bases. The system, PathText, is developed by Systems Biology Institute, Okinawa Institute of Science and Technology, National Centre for Text Mining (University of Manchester) and the University of Tokyo, and is being used by groups of biologists from these locations. Contact: brian@monrovian.com. PMID:20529930

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

Science.gov (United States)

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

Science.gov (United States)

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Integrated care pathways for airway diseases (AIRWAYS-ICPs)

DEFF Research Database (Denmark)

Bousquet, J; Addis, A; Adcock, I

2014-01-01

The objective of Integrated Care Pathways for Airway Diseases (AIRWAYS-ICPs) is to launch a collaboration to develop multi-sectoral care pathways for chronic respiratory diseases in European countries and regions. AIRWAYS-ICPs has strategic relevance to the European Union Health Strategy...... and will add value to existing public health knowledge by: 1) proposing a common framework of care pathways for chronic respiratory diseases, which will facilitate comparability and trans-national initiatives; 2) informing cost-effective policy development, strengthening in particular those on smoking...... and environmental exposure; 3) aiding risk stratification in chronic disease patients, using a common strategy; 4) having a significant impact on the health of citizens in the short term (reduction of morbidity, improvement of education in children and of work in adults) and in the long-term (healthy ageing); 5...

kpath: integration of metabolic pathway linked data.

Science.gov (United States)

Navas-Delgado, Ismael; García-Godoy, María Jesús; López-Camacho, Esteban; Rybinski, Maciej; Reyes-Palomares, Armando; Medina, Miguel Ángel; Aldana-Montes, José F

2015-01-01

In the last few years, the Life Sciences domain has experienced a rapid growth in the amount of available biological databases. The heterogeneity of these databases makes data integration a challenging issue. Some integration challenges are locating resources, relationships, data formats, synonyms or ambiguity. The Linked Data approach partially solves the heterogeneity problems by introducing a uniform data representation model. Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. This article introduces kpath, a database that integrates information related to metabolic pathways. kpath also provides a navigational interface that enables not only the browsing, but also the deep use of the integrated data to build metabolic networks based on existing disperse knowledge. This user interface has been used to showcase relationships that can be inferred from the information available in several public databases. © The Author(s) 2015. Published by Oxford University Press.

Penalized differential pathway analysis of integrative oncogenomics studies

NARCIS (Netherlands)

van Wieringen, W.N.; van de Wiel, M.A.

2014-01-01

Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving

Integrative analysis of RUNX1 downstream pathways and target genes

Directory of Open Access Journals (Sweden)

Liu Marjorie

2008-07-01

Full Text Available Abstract Background The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML. The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. Results Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1 cell lines with RUNX1 mutations from FPD-AML patients, 2 over-expression of RUNX1 and CBFβ, and 3 Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFβ. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. Conclusion This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease

Methods of assessing total doses integrated across pathways

International Nuclear Information System (INIS)

Grzechnik, M.; Camplin, W.; Clyne, F.; Allott, R.; Webbe-Wood, D.

2006-01-01

Calculated doses for comparison with limits resulting from discharges into the environment should be summed across all relevant pathways and food groups to ensure adequate protection. Current methodology for assessments used in the radioactivity in Food and the Environment (R.I.F.E.) reports separate doses from pathways related to liquid discharges of radioactivity to the environment from those due to gaseous releases. Surveys of local inhabitant food consumption and occupancy rates are conducted in the vicinity of nuclear sites. Information has been recorded in an integrated way, such that the data for each individual is recorded for all pathways of interest. These can include consumption of foods, such as fish, crustaceans, molluscs, fruit and vegetables, milk and meats. Occupancy times over beach sediments and time spent in close proximity to the site is also recorded for inclusion of external and inhalation radiation dose pathways. The integrated habits survey data may be combined with monitored environmental radionuclide concentrations to calculate total dose. The criteria for successful adoption of a method for this calculation were: Reproducibility can others easily use the approach and reassess doses? Rigour and realism how good is the match with reality?Transparency a measure of the ease with which others can understand how the calculations are performed and what they mean. Homogeneity is the group receiving the dose relatively homogeneous with respect to age, diet and those aspects that affect the dose received? Five methods of total dose calculation were compared and ranked according to their suitability. Each method was labelled (A to E) and given a short, relevant name for identification. The methods are described below; A) Individual doses to individuals are calculated and critical group selection is dependent on dose received. B) Individual Plus As in A, but consumption and occupancy rates for high dose is used to derive rates for application in

A Model of an Integrated Immune System Pathway in Homo sapiens and Its Interaction with Superantigen Producing Expression Regulatory Pathway in Staphylococcus aureus: Comparing Behavior of Pathogen Perturbed and Unperturbed Pathway

Science.gov (United States)

Tomar, Namrata; De, Rajat K.

2013-01-01

Response of an immune system to a pathogen attack depends on the balance between the host immune defense and the virulence of the pathogen. Investigation of molecular interactions between the proteins of a host and a pathogen helps in identifying the pathogenic proteins. It is necessary to understand the dynamics of a normally behaved host system to evaluate the capacity of its immune system upon pathogen attack. In this study, we have compared the behavior of an unperturbed and pathogen perturbed host system. Moreover, we have developed a formalism under Flux Balance Analysis (FBA) for the optimization of conflicting objective functions. We have constructed an integrated pathway system, which includes Staphylococcal Superantigen (SAg) expression regulatory pathway and TCR signaling pathway of Homo sapiens. We have implemented the method on this pathway system and observed the behavior of host signaling molecules upon pathogen attack. The entire study has been divided into six different cases, based on the perturbed/unperturbed conditions. In other words, we have investigated unperturbed and pathogen perturbed human TCR signaling pathway, with different combinations of optimization of concentrations of regulatory and signaling molecules. One of these cases has aimed at finding out whether minimization of the toxin production in a pathogen leads to the change in the concentration levels of the proteins coded by TCR signaling pathway genes in the infected host. Based on the computed results, we have hypothesized that the balance between TCR signaling inhibitory and stimulatory molecules can keep TCR signaling system into resting/stimulating state, depending upon the perturbation. The proposed integrated host-pathogen interaction pathway model has accurately reflected the experimental evidences, which we have used for validation purpose. The significance of this kind of investigation lies in revealing the susceptible interaction points that can take back the

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

Science.gov (United States)

Waagmeester, Andra; Kutmon, Martina; Riutta, Anders; Miller, Ryan; Willighagen, Egon L; Evelo, Chris T; Pico, Alexander R

2016-06-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

Directory of Open Access Journals (Sweden)

Andra Waagmeester

2016-06-01

Full Text Available The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources

Science.gov (United States)

Waagmeester, Andra; Pico, Alexander R.

2016-01-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. PMID:27336457

Analysis of Membrane Protein Topology in the Plant Secretory Pathway.

Science.gov (United States)

Guo, Jinya; Miao, Yansong; Cai, Yi

2017-01-01

Topology of membrane proteins provides important information for the understanding of protein function and intermolecular associations. Integrate membrane proteins are generally transported from endoplasmic reticulum (ER) to Golgi and downstream compartments in the plant secretory pathway. Here, we describe a simple method to study membrane protein topology along the plant secretory pathway by transiently coexpressing a fluorescent protein (XFP)-tagged membrane protein and an ER export inhibitor protein, ARF1 (T31N), in tobacco BY-2 protoplast. By fractionation, microsome isolation, and trypsin digestion, membrane protein topology could be easily detected by either direct confocal microscopy imaging or western-blot analysis using specific XFP antibodies. A similar strategy in determining membrane protein topology could be widely adopted and applied to protein analysis in a broad range of eukaryotic systems, including yeast cells and mammalian cells.

Pathway analysis: State of the art

Directory of Open Access Journals (Sweden)

Miguel Angel eGarcía-Campos

2015-12-01

Full Text Available Pathway analysis is a set of widely used tools for research in life sciences intended to give meaning to high-throughput biological data. The methodology of these tools settles in the gathering and usage of knowledge that comprise biomolecular functioning, coupled with statistical testing and other algorithms. Despite their wide employment, pathway analysis foundations and overall background may not be fully understood, leading to misinterpretation of analysis results. This review attempts to comprise the fundamental knowledge to take into consideration when using pathway analysis as a hypothesis generation tool. We discuss the key elements that are part of these methodologies, their capabilities and current deficiencies. We also present an overview of current and all-time popular methods, highlighting different classes across them. In doing so, we show the exploding diversity of methods that pathway analysis encompasses, point out commonly overlooked caveats, and direct attention to a potential new class of methods that attempt to zoom the analysis scope to the sample scale.

The Integration of Epistasis Network and Functional Interactions in a GWAS Implicates RXR Pathway Genes in the Immune Response to Smallpox Vaccine.

Directory of Open Access Journals (Sweden)

Brett A McKinney

Full Text Available Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA, which has been implicated in a previous epistasis network analysis of smallpox vaccine.

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

Science.gov (United States)

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Pathway analysis of IMC

DEFF Research Database (Denmark)

Skrypnyuk, Nataliya; Nielson, Flemming; Pilegaard, Henrik

2009-01-01

We present the ongoing work on the pathway analysis of a stochastic calculus. Firstly we present a particular stochastic calculus that we have chosen for our modeling - the Interactive Markov Chains calculus, IMC for short. After that we specify a few restrictions that we have introduced into the...... into the syntax of IMC in order to make our analysis feasible. Finally we describe the analysis itself together with several theoretical results that we have proved for it.......We present the ongoing work on the pathway analysis of a stochastic calculus. Firstly we present a particular stochastic calculus that we have chosen for our modeling - the Interactive Markov Chains calculus, IMC for short. After that we specify a few restrictions that we have introduced...

Integrated omics analysis of specialized metabolism in medicinal plants.

Science.gov (United States)

Rai, Amit; Saito, Kazuki; Yamazaki, Mami

2017-05-01

Medicinal plants are a rich source of highly diverse specialized metabolites with important pharmacological properties. Until recently, plant biologists were limited in their ability to explore the biosynthetic pathways of these metabolites, mainly due to the scarcity of plant genomics resources. However, recent advances in high-throughput large-scale analytical methods have enabled plant biologists to discover biosynthetic pathways for important plant-based medicinal metabolites. The reduced cost of generating omics datasets and the development of computational tools for their analysis and integration have led to the elucidation of biosynthetic pathways of several bioactive metabolites of plant origin. These discoveries have inspired synthetic biology approaches to develop microbial systems to produce bioactive metabolites originating from plants, an alternative sustainable source of medicinally important chemicals. Since the demand for medicinal compounds are increasing with the world's population, understanding the complete biosynthesis of specialized metabolites becomes important to identify or develop reliable sources in the future. Here, we review the contributions of major omics approaches and their integration to our understanding of the biosynthetic pathways of bioactive metabolites. We briefly discuss different approaches for integrating omics datasets to extract biologically relevant knowledge and the application of omics datasets in the construction and reconstruction of metabolic models. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

Science.gov (United States)

Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

2015-02-01

To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

Regulation of Cell Wall Biogenesis in Saccharomyces cerevisiae: The Cell Wall Integrity Signaling Pathway

Science.gov (United States)

Levin, David E.

2011-01-01

The yeast cell wall is a strong, but elastic, structure that is essential not only for the maintenance of cell shape and integrity, but also for progression through the cell cycle. During growth and morphogenesis, and in response to environmental challenges, the cell wall is remodeled in a highly regulated and polarized manner, a process that is principally under the control of the cell wall integrity (CWI) signaling pathway. This pathway transmits wall stress signals from the cell surface to the Rho1 GTPase, which mobilizes a physiologic response through a variety of effectors. Activation of CWI signaling regulates the production of various carbohydrate polymers of the cell wall, as well as their polarized delivery to the site of cell wall remodeling. This review article centers on CWI signaling in Saccharomyces cerevisiae through the cell cycle and in response to cell wall stress. The interface of this signaling pathway with other pathways that contribute to the maintenance of cell wall integrity is also discussed. PMID:22174182

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

Science.gov (United States)

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

The base excision repair pathway is required for efficient lentivirus integration.

Directory of Open Access Journals (Sweden)

Kristine E Yoder

Full Text Available An siRNA screen has identified several proteins throughout the base excision repair (BER pathway of oxidative DNA damage as important for efficient HIV infection. The proteins identified included early repair factors such as the base damage recognition glycosylases OGG1 and MYH and the late repair factor POLß, implicating the entire BER pathway. Murine cells with deletions of the genes Ogg1, Myh, Neil1 and Polß recapitulate the defect of HIV infection in the absence of BER. Defective infection in the absence of BER proteins was also seen with the lentivirus FIV, but not the gammaretrovirus MMLV. BER proteins do not affect HIV infection through its accessory genes nor the central polypurine tract. HIV reverse transcription and nuclear entry appear unaffected by the absence of BER proteins. However, HIV integration to the host chromosome is reduced in the absence of BER proteins. Pre-integration complexes from BER deficient cell lines show reduced integration activity in vitro. Integration activity is restored by addition of recombinant BER protein POLß. Lentiviral infection and integration efficiency appears to depend on the presence of BER proteins.

KeyPathwayMinerWeb

DEFF Research Database (Denmark)

List, Markus; Alcaraz, Nicolas; Dissing-Hansen, Martin

2016-01-01

, for instance), KeyPathwayMiner extracts connected sub-networks containing a high number of active or differentially regulated genes (proteins, metabolites) in the molecular profiles. The web interface at (http://keypathwayminer.compbio.sdu.dk) implements all core functionalities of the KeyPathwayMiner tool set......We present KeyPathwayMinerWeb, the first online platform for de novo pathway enrichment analysis directly in the browser. Given a biological interaction network (e.g. protein-protein interactions) and a series of molecular profiles derived from one or multiple OMICS studies (gene expression...... such as data integration, input of background knowledge, batch runs for parameter optimization and visualization of extracted pathways. In addition to an intuitive web interface, we also implemented a RESTful API that now enables other online developers to integrate network enrichment as a web service...

Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR

DEFF Research Database (Denmark)

Jakočiūnas, Tadas; Jensen, Emil D.; Jensen, Michael Krogh

2018-01-01

and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking......Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome...... engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. Cas...

Expression profiling on soybean leaves reveals integration of ER- and osmotic-stress pathways

Directory of Open Access Journals (Sweden)

Dewey Ralph E

2007-11-01

Full Text Available Abstract Background Despite the potential of the endoplasmic reticulum (ER stress response to accommodate adaptive pathways, its integration with other environmental-induced responses is poorly understood in plants. We have previously demonstrated that the ER-stress sensor binding protein (BiP from soybean exhibits an unusual response to drought. The members of the soybean BiP gene family are differentially regulated by osmotic stress and soybean BiP confers tolerance to drought. While these results may reflect crosstalk between the osmotic and ER-stress signaling pathways, the lack of mutants, transcriptional response profiles to stresses and genome sequence information of this relevant crop has limited our attempts to identify integrated networks between osmotic and ER stress-induced adaptive responses. As a fundamental step towards this goal, we performed global expression profiling on soybean leaves exposed to polyethylene glycol treatment (osmotic stress or to ER stress inducers. Results The up-regulated stress-specific changes unmasked the major branches of the ER-stress response, which include enhancing protein folding and degradation in the ER, as well as specific osmotically regulated changes linked to cellular responses induced by dehydration. However, a small proportion (5.5% of total up-regulated genes represented a shared response that seemed to integrate the two signaling pathways. These co-regulated genes were considered downstream targets based on similar induction kinetics and a synergistic response to the combination of osmotic- and ER-stress-inducing treatments. Genes in this integrated pathway with the strongest synergistic induction encoded proteins with diverse roles, such as plant-specific development and cell death (DCD domain-containing proteins, an ubiquitin-associated (UBA protein homolog and NAC domain-containing proteins. This integrated pathway diverged further from characterized specific branches of ER-stress as

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

Directory of Open Access Journals (Sweden)

Mónica Escandón

2018-04-01

Full Text Available The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3 at which P. radiata plants changed from an initial stress response program (shorter-term response to an acclimation one (longer-term response. Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs, fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR and isopentenyl adenosine (iPA as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin, crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

Integrating Multiple Microarray Data for Cancer Pathway Analysis Using Bootstrapping K-S Test

Directory of Open Access Journals (Sweden)

Bing Han

2009-01-01

Full Text Available Previous applications of microarray technology for cancer research have mostly focused on identifying genes that are differentially expressed between a particular cancer and normal cells. In a biological system, genes perform different molecular functions and regulate various biological processes via interactions with other genes thus forming a variety of complex networks. Therefore, it is critical to understand the relationship (e.g., interactions between genes across different types of cancer in order to gain insights into the molecular mechanisms of cancer. Here we propose an integrative method based on the bootstrapping Kolmogorov-Smirnov test and a large set of microarray data produced with various types of cancer to discover common molecular changes in cells from normal state to cancerous state. We evaluate our method using three key pathways related to cancer and demonstrate that it is capable of finding meaningful alterations in gene relations.

Psychotherapy, psychopathology, research and practice: pathways of connections and integration.

Science.gov (United States)

Castonguay, Louis G

2011-03-01

This paper describes three pathways of connections between different communities of knowledge seekers: integration of psychotherapeutic approaches, integration of psychotherapy and psychopathology, and integration of science and practice. Some of the issues discussed involve the delineation and investigation of common factors (e.g., principles of change), improvement of major forms of psychotherapy, clinical implications of psychopathology research, as well as current and future directions related to practice-research networks. The aim of this paper is to suggest that building bridges across theoretical orientations, scientific fields, professional experiences, and epistemological views may be a fruitful strategy to improve our understanding and the impact of psychotherapy.

A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways

Science.gov (United States)

Han, Junwei; Li, Chunquan; Yang, Haixiu; Xu, Yanjun; Zhang, Chunlong; Ma, Jiquan; Shi, Xinrui; Liu, Wei; Shang, Desi; Yao, Qianlan; Zhang, Yunpeng; Su, Fei; Feng, Li; Li, Xia

2015-01-01

Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI). PMID:25551156

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

Science.gov (United States)

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

atBioNet– an integrated network analysis tool for genomics and biomarker discovery

Directory of Open Access Journals (Sweden)

Ding Yijun

2012-07-01

Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

Science.gov (United States)

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

Integrated Network Analysis and Effective Tools in Plant Systems Biology

Directory of Open Access Journals (Sweden)

Atsushi eFukushima

2014-11-01

Full Text Available One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1 network visualization tools, (2 pathway analyses, (3 genome-scale metabolic reconstruction, and (4 the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.

Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease.

Science.gov (United States)

Zhang, Yan; Liu, Dianming; Wang, Lihong; Wang, Shuyuan; Yu, Xuexin; Dai, Enyu; Liu, Xinyi; Luo, Shanshun; Jiang, Wei

2015-12-01

Coronary artery disease (CAD) is the most common type of heart disease. However, the molecular mechanisms of CAD remain elusive. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, inferring risk regulatory pathways is an important step toward elucidating the mechanisms underlying CAD. With advances in high-throughput data, we developed an integrated systems approach to identify CAD risk regulatory pathways and key regulators. Firstly, a CAD-related core subnetwork was identified from a curated transcription factor (TF) and microRNA (miRNA) regulatory network based on a random walk algorithm. Secondly, candidate risk regulatory pathways were extracted from the subnetwork by applying a breadth-first search (BFS) algorithm. Then, risk regulatory pathways were prioritized based on multiple CAD-associated data sources. Finally, we also proposed a new measure to prioritize upstream regulators. We inferred that phosphatase and tensin homolog (PTEN) may be a key regulator in the dysregulation of risk regulatory pathways. This study takes a closer step than the identification of disease subnetworks or modules. From the risk regulatory pathways, we could understand the flow of regulatory information in the initiation and progression of the disease. Our approach helps to uncover its potential etiology. We developed an integrated systems approach to identify risk regulatory pathways. We proposed a new measure to prioritize the key regulators in CAD. PTEN may be a key regulator in dysregulation of the risk regulatory pathways.

Towards integrating extracellular matrix and immunological pathways.

Science.gov (United States)

Boyd, David F; Thomas, Paul G

2017-10-01

The extracellular matrix (ECM) is a complex and dynamic structure made up of an estimated 300 different proteins. The ECM is also a rich source of cytokines and growth factors in addition to numerous bioactive ECM degradation products that influence cell migration, proliferation, and differentiation. The ECM is constantly being remodeled during homeostasis and in a wide range of pathological contexts. Changes in the ECM modulate immune responses, which in turn regulate repair and regeneration of tissues. Here, we review the many components of the ECM, enzymes involved in ECM remodeling, and the signals that feed into immunological pathways in the context of a dynamic ECM. We highlight studies that have taken an integrative approach to studying immune responses in the context of the ECM and studies that use novel proteomic strategies. Finally, we discuss research challenges relevant to the integration of immune and ECM networks and propose experimental and translational approaches to resolve these issues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrated bioinformatic analysis unveils significant genes and pathways in the pathogenesis of supratentorial primitive neuroectodermal tumor

Directory of Open Access Journals (Sweden)

Wang G

2018-04-01

Full Text Available Guang-Yu Wang,1,* Ling Li,2,* Bo Liu,1 Xiao Han,1 Chun-Hua Wang,1 Ji-Wen Wang3 1Department of Neurosurgery, 2Department of Pediatrics, Qilu Children’s Hospital of Shandong University, Jinan, Shandong, 3Department of Neurology, Shanghai Children’s Medical Center, Shanghai Jiaotong University School of Medicine, Pudong New District, Shanghai, People’s Republic of China *These authors contributed equally to this work Purpose: This study aimed to explore significant genes and pathways involved in the pathogenesis of supratentorial primitive neuroectodermal tumor (sPNET. Materials and methods: Gene expression profile of GSE14295 was downloaded from publicly available Gene Expression Omnibus (GEO database. Differentially expressed genes (DEGs were screened out in primary sPNET samples compared with normal fetal and adult brain reference samples (sPNET vs fetal brain and sPNET vs adult brain. Pathway enrichment analysis of these DEGs was conducted, followed by protein–protein interaction (PPI network construction and significant module selection. Additionally, transcription factors (TFs regulating the common DEGs in the two comparison groups were identified, and the regulatory network was constructed. Results: In total, 526 DEGs (99 up- and 427 downregulated in sPNET vs fetal brain and 815 DEGs (200 up- and 615 downregulated in sPNET vs adult brain were identified. DEGs in sPNET vs fetal brain and sPNET vs adult brain were associated with calcium signaling pathway, cell cycle, and p53 signaling pathway. CDK1, CDC20, BUB1B, and BUB1 were hub nodes in the PPI networks of DEGs in sPNET vs fetal brain and sPNET vs adult brain. Significant modules were extracted from the PPI networks. In addition, 64 upregulated and 200 downregulated overlapping DEGs were identified in both sPNET vs fetal brain and sPNET vs adult brain. The genes involved in the regulatory network upon overlapping DEGs and the TFs were correlated with calcium signaling pathway

Safety assessment for deep underground disposal vault-pathways analysis

International Nuclear Information System (INIS)

Lyon, R.B.; Rosinger, E.L.J.

1980-01-01

The concept verification phase of the Canadian programme for the disposal of nuclear fuel waste encompasses a period of about three years before the start of site selection. During this time, the methodology for Environmental and Safety Assessment studies is being developed by focusing on a model site. Pathways analysis is an important component of these studies. It involves the prediction of the rate at which radionuclides might be released from a disposal vault and travel through the geosphere and biosphere to reach man. The pathways analysis studies cover three major topics: geosphere pathways analysis, biosphere pathways analysis and potentially-disruptive-phenomena analysis. Geosphere pathways analysis includes a total systems analysis, using the computer program GARD2, vault analysis, which considers container failure and waste leaching, hydrogeological modelling and geochemical modelling. Biosphere pathways analysis incorporates a compartmental modelling approach using the computer program RAMM, and a food chain analysis using the computer program FOOD II. Potentially-disruptive-phenomena analysis involves the estimation of the probability and consequences of events such as earthquakes which might reduce the effectiveness of the barriers preventing the release of radionuclides. The current stage of development of the required methodology and data is discussed in each of the three areas and preliminary results are presented. (author)

Sensitivity analysis of intracellular signaling pathway kinetics predicts targets for stem cell fate control.

Directory of Open Access Journals (Sweden)

Alborz Mahdavi

2007-07-01

Full Text Available Directing stem cell fate requires knowledge of how signaling networks integrate temporally and spatially segregated stimuli. We developed and validated a computational model of signal transducer and activator of transcription-3 (Stat3 pathway kinetics, a signaling network involved in embryonic stem cell (ESC self-renewal. Our analysis identified novel pathway responses; for example, overexpression of the receptor glycoprotein-130 results in reduced pathway activation and increased ESC differentiation. We used a systematic in silico screen to identify novel targets and protein interactions involved in Stat3 activation. Our analysis demonstrates that signaling activation and desensitization (the inability to respond to ligand restimulation is regulated by balancing the activation state of a distributed set of parameters including nuclear export of Stat3, nuclear phosphatase activity, inhibition by suppressor of cytokine signaling, and receptor trafficking. This knowledge was used to devise a temporally modulated ligand delivery strategy that maximizes signaling activation and leads to enhanced ESC self-renewal.

Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

Science.gov (United States)

Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

2017-09-21

Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

Sensitivity and uncertainty analysis of the PATHWAY radionuclide transport model

International Nuclear Information System (INIS)

Otis, M.D.

1983-01-01

Procedures were developed for the uncertainty and sensitivity analysis of a dynamic model of radionuclide transport through human food chains. Uncertainty in model predictions was estimated by propagation of parameter uncertainties using a Monte Carlo simulation technique. Sensitivity of model predictions to individual parameters was investigated using the partial correlation coefficient of each parameter with model output. Random values produced for the uncertainty analysis were used in the correlation analysis for sensitivity. These procedures were applied to the PATHWAY model which predicts concentrations of radionuclides in foods grown in Nevada and Utah and exposed to fallout during the period of atmospheric nuclear weapons testing in Nevada. Concentrations and time-integrated concentrations of iodine-131, cesium-136, and cesium-137 in milk and other foods were investigated. 9 figs., 13 tabs

Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential.

Science.gov (United States)

Asplund-Samuelsson, Johannes; Janasch, Markus; Hudson, Elton P

2018-01-01

Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of the metabolic network in the photoautotroph Synechocystis with that of the heterotroph E. coli using the novel workflow POPPY (Prospecting Optimal Pathways with PYthon). First, E. coli and Synechocystis metabolomic and fluxomic data were combined with metabolic models to identify thermodynamic constraints on metabolite concentrations (NET analysis). Then, thousands of automatically constructed pathways were placed within each network and subjected to a network-embedded variant of the max-min driving force analysis (NEM). We found that the networks had different capabilities for imparting thermodynamic driving forces toward certain compounds. Key metabolites were constrained differently in Synechocystis due to opposing flux directions in glycolysis and carbon fixation, the forked tri-carboxylic acid cycle, and photorespiration. Furthermore, the lysine biosynthesis pathway in Synechocystis was identified as thermodynamically constrained, impacting both endogenous and heterologous reactions through low 2-oxoglutarate levels. Our study also identified important yet poorly covered areas in existing metabolomics data and provides a reference for future thermodynamics-based engineering in Synechocystis and beyond. The POPPY methodology represents a step in making optimal pathway-host matches, which is likely to become important as the practical range of host organisms is diversified. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Primary Metabolic Pathways and Metabolic Flux Analysis

DEFF Research Database (Denmark)

Villadsen, John

2015-01-01

his chapter introduces the metabolic flux analysis (MFA) or stoichiometry-based MFA, and describes the quantitative basis for MFA. It discusses the catabolic pathways in which free energy is produced to drive the cell-building anabolic pathways. An overview of these primary pathways provides...... the reader who is primarily trained in the engineering sciences with atleast a preliminary introduction to biochemistry and also shows how carbon is drained off the catabolic pathways to provide precursors for cell mass building and sometimes for important industrial products. The primary pathways...... to be examined in the following are: glycolysis, primarily by the EMP pathway, but other glycolytic pathways is also mentioned; fermentative pathways in which the redox generated in the glycolytic reactions are consumed; reactions in the tricarboxylic acid (TCA) cycle, which produce biomass precursors and redox...

Integrating nitric oxide into salicylic acid and jasmonic acid/ethylene plant defense pathways

DEFF Research Database (Denmark)

Mur, Luis A J; Prats, Elena; Pierre, Sandra

2013-01-01

to be tailored to particular biotic stresses. Nitric oxide (NO) has emerged as a major signal influencing resistance mediated by both signalling pathways but no attempt has been made to integrate NO into established SA/JA/ET interactions. NO has been shown to act as an inducer or suppressor of signalling along......Plant defence against pests and pathogens is known to be conferred by either salicylic acid (SA) or jasmonic acid (JA)/ethylene (ET) pathways, depending on infection or herbivore-grazing strategy. It is well attested that SA and JA/ET pathways are mutually antagonistic allowing defence responses...

A systems biology approach for pathway level analysis

OpenAIRE

Draghici, Sorin; Khatri, Purvesh; Tarca, Adi Laurentiu; Amin, Kashyap; Done, Arina; Voichita, Calin; Georgescu, Constantin; Romero, Roberto

2007-01-01

A common challenge in the analysis of genomics data is trying to understand the underlying phenomenon in the context of all complex interactions taking place on various signaling pathways. A statistical approach using various models is universally used to identify the most relevant pathways in a given experiment. Here, we show that the existing pathway analysis methods fail to take into consideration important biological aspects and may provide incorrect results in certain situations. By usin...

A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

Science.gov (United States)

Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

2017-09-01

The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.

Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR.

Science.gov (United States)

Jakočiūnas, Tadas; Jensen, Emil D; Jensen, Michael K; Keasling, Jay D

2018-01-01

Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. CasEMBLR capitalizes on the CRISPR/Cas9 technology to generate double-strand breaks in genomic loci, thus prompting native homologous recombination (HR) machinery to integrate exogenously derived homology templates. As proof-of-principle for microbial cell factory development, CasEMBLR was used for one-step assembly and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking out two genes. This new method complements and improves the field of genome engineering in S. cerevisiae by providing a more flexible platform for rapid and precise strain building.

Integration of deep geothermal energy and woody biomass conversion pathways in urban systems

International Nuclear Information System (INIS)

Moret, Stefano; Peduzzi, Emanuela; Gerber, Léda; Maréchal, François

2016-01-01

Highlights: • Novel optimization-based methodology to integrate renewable energy systems in cities. • Multiperiod model including storage, heat integration and Life Cycle Assessment. • Case study: systematic assessment of deep geothermal and wood conversion pathways. • Identification of novel wood-geothermal hybrid systems leading to higher efficiencies. • Extensive Supplementary Material to ensure full reproducibility of the work. - Abstract: Urban systems account for about two-thirds of global primary energy consumption and energy-related greenhouse gas emissions, with a projected increasing trend. Deep geothermal energy and woody biomass can be used for the production of heat, electricity and biofuels, thus constituting a renewable alternative to fossil fuels for all end-uses in cities: heating, cooling, electricity and mobility. This paper presents a methodology to assess the potential for integrating deep geothermal energy and woody biomass in an urban energy system. The city is modeled in its entirety as a multiperiod optimization problem with the total annual cost as an objective, assessing as well the environmental impact with a Life Cycle Assessment approach. For geothermal energy, deep aquifers and Enhanced Geothermal Systems are considered for stand-alone production of heat and electricity, and for cogeneration. For biomass, besides direct combustion and cogeneration, conversion to biofuels by a set of alternative processes (pyrolysis, Fischer-Tropsch synthesis and synthetic natural gas production) is studied. With a scenario-based approach, all pathways are first individually evaluated. Secondly, all possible combinations between geothermal and biomass options are systematically compared, taking into account the possibility of hybrid systems. Results show that integrating these two resources generates configurations featuring both lower costs and environmental impacts. In particular, synergies are found in innovative hybrid systems using

Data integration for plant genomics--exemplars from the integration of Arabidopsis thaliana databases.

Science.gov (United States)

Lysenko, Artem; Lysenko, Atem; Hindle, Matthew Morritt; Taubert, Jan; Saqi, Mansoor; Rawlings, Christopher John

2009-11-01

The development of a systems based approach to problems in plant sciences requires integration of existing information resources. However, the available information is currently often incomplete and dispersed across many sources and the syntactic and semantic heterogeneity of the data is a challenge for integration. In this article, we discuss strategies for data integration and we use a graph based integration method (Ondex) to illustrate some of these challenges with reference to two example problems concerning integration of (i) metabolic pathway and (ii) protein interaction data for Arabidopsis thaliana. We quantify the degree of overlap for three commonly used pathway and protein interaction information sources. For pathways, we find that the AraCyc database contains the widest coverage of enzyme reactions and for protein interactions we find that the IntAct database provides the largest unique contribution to the integrated dataset. For both examples, however, we observe a relatively small amount of data common to all three sources. Analysis and visual exploration of the integrated networks was used to identify a number of practical issues relating to the interpretation of these datasets. We demonstrate the utility of these approaches to the analysis of groups of coexpressed genes from an individual microarray experiment, in the context of pathway information and for the combination of coexpression data with an integrated protein interaction network.

Can Cultural Behavior Have a Negative Impact on the Development of Visual Integration Pathways?

Science.gov (United States)

Pretorius, E.; Naude, H.; van Vuuren, C. J.

2002-01-01

Contends that cultural practices such as carrying the baby on the mother's back for prolonged periods can impact negatively on development of visual integration during the sensorimotor stage pathways by preventing adequate or enough crawling. Maintains that crawling is essential for cross- modality integration and that higher mental functions may…

Final report on the Pathway Analysis Task

International Nuclear Information System (INIS)

Whicker, F.W.; Kirchner, T.B.

1993-04-01

The Pathway Analysis Task constituted one of several multi-laboratory efforts to estimate radiation doses to people, considering all important pathways of exposure, from the testing of nuclear devices at the Nevada Test Site (NTS). The primary goal of the Pathway Analysis Task was to predict radionuclide ingestion by residents of Utah, Nevada, and portions of seven other adjoining western states following radioactive fallout deposition from individual events at the NTS. This report provides comprehensive documentation of the activities and accomplishments of Colorado State University's Pathway Analysis Task during the entire period of support (1979--91). The history of the project will be summarized, indicating the principal dates and milestones, personnel involved, subcontractors, and budget information. Accomplishments, both primary and auxiliary, will be summarized with general results rather than technical details being emphasized. This will also serve as a guide to the reports and open literature publications produced, where the methodological details and specific results are documented. Selected examples of results on internal dose estimates are provided in this report because the data have not been published elsewhere

Final report on the Pathway Analysis Task

Energy Technology Data Exchange (ETDEWEB)

Whicker, F.W.; Kirchner, T.B. [Colorado State Univ., Fort Collins, CO (United States)

1993-04-01

The Pathway Analysis Task constituted one of several multi-laboratory efforts to estimate radiation doses to people, considering all important pathways of exposure, from the testing of nuclear devices at the Nevada Test Site (NTS). The primary goal of the Pathway Analysis Task was to predict radionuclide ingestion by residents of Utah, Nevada, and portions of seven other adjoining western states following radioactive fallout deposition from individual events at the NTS. This report provides comprehensive documentation of the activities and accomplishments of Colorado State University`s Pathway Analysis Task during the entire period of support (1979--91). The history of the project will be summarized, indicating the principal dates and milestones, personnel involved, subcontractors, and budget information. Accomplishments, both primary and auxiliary, will be summarized with general results rather than technical details being emphasized. This will also serve as a guide to the reports and open literature publications produced, where the methodological details and specific results are documented. Selected examples of results on internal dose estimates are provided in this report because the data have not been published elsewhere.

The future use of pathway analysis in IAEA safeguards

International Nuclear Information System (INIS)

Budlong Sylvester, Kory; Pilat, J.; Murphy, Chantell

2013-01-01

Pathway analysis has the potential to play an important role in the development of a safeguards system that is more information driven, leveraging all the information available to the International Atomic Energy Agency (IAEA). Pathway analysis should be seen as an extension of traditional hypothesis testing used by the Agency in the past. The most attractive pathways based on the assessed capabilities of a given state can be identified and used in the development of state-level safeguards approaches. This ranking of pathways can be revised based on evidence of pathway use, or preparations for use, allowing limited safeguards resources to flow to the areas of highest concern. The possible uses of pathway analysis in the implementation of the IAEA's state-level concept are described along with implementation issues that will likely arise. The paper is followed by the slides of the presentation. (authors)

Integrated Pathway-Based Approach Identifies Association between Genomic Regions at CTCF and CACNB2 and Schizophrenia

NARCIS (Netherlands)

Juraeva, Dilafruz; Haenisch, Britta; Zapatka, Marc; Frank, Josef; Witt, Stephanie H.; Mühleisen, Thomas W.; Treutlein, Jens; Strohmaier, Jana; Meier, Sandra; Degenhardt, Franziska; Giegling, Ina; Ripke, Stephan; Leber, Markus; Lange, Christoph; Schulze, Thomas G.; Mössner, Rainald; Nenadic, Igor; Sauer, Heinrich; Rujescu, Dan; Maier, Wolfgang; Børglum, Anders; Ophoff, Roel; Cichon, Sven; Nöthen, Markus M.; Rietschel, Marcella; Mattheisen, Manuel; Brors, Benedikt; Kahn, René S.; Cahn, Wiepke; Linszen, Don H.; de Haan, Lieuwe; van Os, Jim; Krabbendam, Lydia; Myin-Germeys, Inez; Wiersma, Durk; Bruggeman, Richard; Mors, O.; Børglum, A. D.; Mortensen, P. B.; Pedersen, C. B.; Demontis, D.; Grove, J.; Mattheisen, M.; Hougaard, D. M.

2014-01-01

In the present study, an integrated hierarchical approach was applied to: (1) identify pathways associated with susceptibility to schizophrenia; (2) detect genes that may be potentially affected in these pathways since they contain an associated polymorphism; and (3) annotate the functional

Cleanup standards and pathways analysis methods

International Nuclear Information System (INIS)

Devgun, J.S.

1993-01-01

Remediation of a radioactively contaminated site requires that certain regulatory criteria be met before the site can be released for unrestricted future use. Since the ultimate objective of remediation is to protect the public health and safety, residual radioactivity levels remaining at a site after cleanup must be below certain preset limits or meet acceptable dose or risk criteria. Release of a decontaminated site requires proof that the radiological data obtained from the site meet the regulatory criteria for such a release. Typically release criteria consist of a composite of acceptance limits that depend on the radionuclides, the media in which they are present, and federal and local regulations. In recent years, the US Department of Energy (DOE) has developed a pathways analysis model to determine site-specific soil activity concentration guidelines for radionuclides that do not have established generic acceptance limits. The DOE pathways analysis computer code (developed by Argonne National Laboratory for the DOE) is called RESRAD (Gilbert et al. 1989). Similar efforts have been initiated by the US Nuclear Regulatory Commission (NRC) to develop and use dose-related criteria based on genetic pathways analyses rather than simplistic numerical limits on residual radioactivity. The focus of this paper is radionuclide contaminated soil. Cleanup standards are reviewed, pathways analysis methods are described, and an example is presented in which RESRAD was used to derive cleanup guidelines

Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes

Directory of Open Access Journals (Sweden)

Wufeng Fan

2017-01-01

Full Text Available In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM based on pathway interaction network (PIN which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs, and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed pathway and classification accuracy. To evaluate whether the PIN method was feasible or not, we compared the introduced method with standard network centrality measures. The pathway of RNA polymerase II pretranscription events was selected as the seed pathway. Taking this seed pathway as start, one pathway set (9 dysregulated pathways with AUC score of 1.00 was identified. Among the 5 hub pathways obtained using standard network centrality measures, 4 pathways were the common ones between the two methods. RNA polymerase II transcription and DNA replication owned a higher number of pathway genes and DEGs. These dysregulated pathways work together to influence the progression of LM infection, and they will be available as biomarkers to diagnose LM infection.

MelanomaDB: a Web Tool for Integrative Analysis of Melanoma Genomic Information to Identify Disease-Associated Molecular Pathways

Directory of Open Access Journals (Sweden)

Alexander Joseph Trevarton

2013-07-01

Full Text Available Despite on-going research, metastatic melanoma survival rates remain low and treatment options are limited. Researchers can now access a rapidly growing amount of molecular and clinical information about melanoma. This information is becoming difficult to assemble and interpret due to its dispersed nature, yet as it grows it becomes increasingly valuable for understanding melanoma. Integration of this information into a comprehensive resource to aid rational experimental design and patient stratification is needed. As an initial step in this direction, we have assembled a web-accessible melanoma database, MelanomaDB, which incorporates clinical and molecular data from publically available sources, which will be regularly updated as new information becomes available. This database allows complex links to be drawn between many different aspects of melanoma biology: genetic changes (e.g. mutations in individual melanomas revealed by DNA sequencing, associations between gene expression and patient survival, data concerning drug targets, biomarkers, druggability and clinical trials, as well as our own statistical analysis of relationships between molecular pathways and clinical parameters that have been produced using these data sets. The database is freely available at http://genesetdb.auckland.ac.nz/melanomadb/about.html . A subset of the information in the database can also be accessed through a freely available web application in the Illumina genomic cloud computing platform BaseSpace at http://www.biomatters.com/apps/melanoma-profiler-for-research . This illustrates dysregulation of specific signalling pathways, both across 310 exome-sequenced melanomas and in individual tumours and identifies novel features about the distribution of somatic variants in melanoma. We suggest that this database can provide a context in which to interpret the tumour molecular profiles of individual melanoma patients relative to biological information and available

Mechanisms and mediation in survival analysis: towards an integrated analytical framework.

LENUS (Irish Health Repository)

Haase, Trutz

2016-02-29

A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare.

Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations

International Nuclear Information System (INIS)

Kalari, Krishna R.; Rossell, David; Necela, Brian M.; Asmann, Yan W.; Nair, Asha

2012-01-01

KRAS mutations are highly prevalent in non-small cell lung cancer (NSCLC), and tumors harboring these mutations tend to be aggressive and resistant to chemotherapy. We used next-generation sequencing technology to identify pathways that are specifically altered in lung tumors harboring a KRAS mutation. Paired-end RNA-sequencing of 15 primary lung adenocarcinoma tumors (8 harboring mutant KRAS and 7 with wild-type KRAS) were performed. Sequences were mapped to the human genome, and genomic features, including differentially expressed genes, alternate splicing isoforms and single nucleotide variants, were determined for tumors with and without KRAS mutation using a variety of computational methods. Network analysis was carried out on genes showing differential expression (374 genes), alternate splicing (259 genes), and SNV-related changes (65 genes) in NSCLC tumors harboring a KRAS mutation. Genes exhibiting two or more connections from the lung adenocarcinoma network were used to carry out integrated pathway analysis. The most significant signaling pathways identified through this analysis were the NFκB, ERK1/2, and AKT pathways. A 27 gene mutant KRAS-specific sub network was extracted based on gene–gene connections from the integrated network, and interrogated for druggable targets. Our results confirm previous evidence that mutant KRAS tumors exhibit activated NFκB, ERK1/2, and AKT pathways and may be preferentially sensitive to target therapeutics toward these pathways. In addition, our analysis indicates novel, previously unappreciated links between mutant KRAS and the TNFR and PPARγ signaling pathways, suggesting that targeted PPARγ antagonists and TNFR inhibitors may be useful therapeutic strategies for treatment of mutant KRAS lung tumors. Our study is the first to integrate genomic features from RNA-Seq data from NSCLC and to define a first draft genomic landscape model that is unique to tumors with oncogenic KRAS mutations.

Separate enrichment analysis of pathways for up- and downregulated genes.

Science.gov (United States)

Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

2014-03-06

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

A strategy for evaluating pathway analysis methods.

Science.gov (United States)

Yu, Chenggang; Woo, Hyung Jun; Yu, Xueping; Oyama, Tatsuya; Wallqvist, Anders; Reifman, Jaques

2017-10-13

Researchers have previously developed a multitude of methods designed to identify biological pathways associated with specific clinical or experimental conditions of interest, with the aim of facilitating biological interpretation of high-throughput data. Before practically applying such pathway analysis (PA) methods, we must first evaluate their performance and reliability, using datasets where the pathways perturbed by the conditions of interest have been well characterized in advance. However, such 'ground truths' (or gold standards) are often unavailable. Furthermore, previous evaluation strategies that have focused on defining 'true answers' are unable to systematically and objectively assess PA methods under a wide range of conditions. In this work, we propose a novel strategy for evaluating PA methods independently of any gold standard, either established or assumed. The strategy involves the use of two mutually complementary metrics, recall and discrimination. Recall measures the consistency of the perturbed pathways identified by applying a particular analysis method to an original large dataset and those identified by the same method to a sub-dataset of the original dataset. In contrast, discrimination measures specificity-the degree to which the perturbed pathways identified by a particular method to a dataset from one experiment differ from those identifying by the same method to a dataset from a different experiment. We used these metrics and 24 datasets to evaluate six widely used PA methods. The results highlighted the common challenge in reliably identifying significant pathways from small datasets. Importantly, we confirmed the effectiveness of our proposed dual-metric strategy by showing that previous comparative studies corroborate the performance evaluations of the six methods obtained by our strategy. Unlike any previously proposed strategy for evaluating the performance of PA methods, our dual-metric strategy does not rely on any ground truth

Pathway Processor 2.0: a web resource for pathway-based analysis of high-throughput data.

Science.gov (United States)

Beltrame, Luca; Bianco, Luca; Fontana, Paolo; Cavalieri, Duccio

2013-07-15

Pathway Processor 2.0 is a web application designed to analyze high-throughput datasets, including but not limited to microarray and next-generation sequencing, using a pathway centric logic. In addition to well-established methods such as the Fisher's test and impact analysis, Pathway Processor 2.0 offers innovative methods that convert gene expression into pathway expression, leading to the identification of differentially regulated pathways in a dataset of choice. Pathway Processor 2.0 is available as a web service at http://compbiotoolbox.fmach.it/pathwayProcessor/. Sample datasets to test the functionality can be used directly from the application. duccio.cavalieri@fmach.it Supplementary data are available at Bioinformatics online.

minepath.org: a free interactive pathway analysis web server.

Science.gov (United States)

Koumakis, Lefteris; Roussos, Panos; Potamias, George

2017-07-03

( www.minepath.org ) is a web-based platform that elaborates on, and radically extends the identification of differentially expressed sub-paths in molecular pathways. Besides the network topology, the underlying MinePath algorithmic processes exploit exact gene-gene molecular relationships (e.g. activation, inhibition) and are able to identify differentially expressed pathway parts. Each pathway is decomposed into all its constituent sub-paths, which in turn are matched with corresponding gene expression profiles. The highly ranked, and phenotype inclined sub-paths are kept. Apart from the pathway analysis algorithm, the fundamental innovation of the MinePath web-server concerns its advanced visualization and interactive capabilities. To our knowledge, this is the first pathway analysis server that introduces and offers visualization of the underlying and active pathway regulatory mechanisms instead of genes. Other features include live interaction, immediate visualization of functional sub-paths per phenotype and dynamic linked annotations for the engaged genes and molecular relations. The user can download not only the results but also the corresponding web viewer framework of the performed analysis. This feature provides the flexibility to immediately publish results without publishing source/expression data, and get all the functionality of a web based pathway analysis viewer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Simplified analysis for liquid pathway studies

International Nuclear Information System (INIS)

Codell, R.B.

1984-08-01

The analysis of the potential contamination of surface water via groundwater contamination from severe nuclear accidents is routinely calculated during licensing reviews. This analysis is facilitated by the methods described in this report, which is codified into a BASIC language computer program, SCREENLP. This program performs simplified calculations for groundwater and surface water transport and calculates population doses to potential users for the contaminated water irrespective of possible mitigation methods. The results are then compared to similar analyses performed using data for the generic sites in NUREG-0440, Liquid Pathway Generic Study, to determine if the site being investigated would pose any unusual liquid pathway hazards

Functional analysis of the MAPK pathways in fungi.

Science.gov (United States)

Martínez-Soto, Domingo; Ruiz-Herrera, José

The Mitogen-Activated Protein Kinase (MAPK) signaling pathways constitute one of the most important and evolutionarily conserved mechanisms for the perception of extracellular information in all the eukaryotic organisms. The MAPK pathways are involved in the transfer to the cell of the information perceived from extracellular stimuli, with the final outcome of activation of different transcription factors that regulate gene expression in response to them. In all species of fungi, the MAPK pathways have important roles in their physiology and development; e.g. cell cycle control, mating, morphogenesis, response to different stresses, resistance to UV radiation and to temperature changes, cell wall assembly and integrity, degradation of cellular organelles, virulence, cell-cell signaling, fungus-plant interaction, and response to damage-associated molecular patterns (DAMPs). Considering the importance of the phylogenetically conserved MAPK pathways in fungi, an updated review of the knowledge on them is discussed in this article. This information reveals their importance, their distribution in fungal species evolutionarily distant and with different lifestyles, their organization and function, and the interactions occurring between different MAPK pathways, and with other signaling pathways, for the regulation of the most complex cellular processes. Copyright © 2017 Asociación Española de Micología. Publicado por Elsevier España, S.L.U. All rights reserved.

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

Science.gov (United States)

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

A Review of Pathway-Based Analysis Tools That Visualize Genetic Variants

Directory of Open Access Journals (Sweden)

Elisa Cirillo

2017-11-01

Full Text Available Pathway analysis is a powerful method for data analysis in genomics, most often applied to gene expression analysis. It is also promising for single-nucleotide polymorphism (SNP data analysis, such as genome-wide association study data, because it allows the interpretation of variants with respect to the biological processes in which the affected genes and proteins are involved. Such analyses support an interactive evaluation of the possible effects of variations on function, regulation or interaction of gene products. Current pathway analysis software often does not support data visualization of variants in pathways as an alternate method to interpret genetic association results, and specific statistical methods for pathway analysis of SNP data are not combined with these visualization features. In this review, we first describe the visualization options of the tools that were identified by a literature review, in order to provide insight for improvements in this developing field. Tool evaluation was performed using a computational epistatic dataset of gene–gene interactions for obesity risk. Next, we report the necessity to include in these tools statistical methods designed for the pathway-based analysis with SNP data, expressly aiming to define features for more comprehensive pathway-based analysis tools. We conclude by recognizing that pathway analysis of genetic variations data requires a sophisticated combination of the most useful and informative visual aspects of the various tools evaluated.

PathwaySplice: An R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

Science.gov (United States)

Yan, Aimin; Ban, Yuguang; Gao, Zhen; Chen, Xi; Wang, Lily

2018-04-24

Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the "significant" gene list in alternative splicing. We present PathwaySplice, an R package that (1) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (2) Visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (3) Supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (4) Identifies the significant genes driving pathway significance and (5) Organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph. https://bioconductor.org/packages/release/bioc/html/PathwaySplice.html. lily.wangg@gmail.com, xi.steven.chen@gmail.com.

Pan-cancer analysis of TCGA data reveals notable signaling pathways

International Nuclear Information System (INIS)

Neapolitan, Richard; Horvath, Curt M.; Jiang, Xia

2015-01-01

A signal transduction pathway (STP) is a network of intercellular information flow initiated when extracellular signaling molecules bind to cell-surface receptors. Many aberrant STPs have been associated with various cancers. To develop optimal treatments for cancer patients, it is important to discover which STPs are implicated in a cancer or cancer-subtype. The Cancer Genome Atlas (TCGA) makes available gene expression level data on cases and controls in ten different types of cancer including breast cancer, colon adenocarcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian carcinoma, rectum adenocarcinoma, and uterine corpus endometriod carcinoma. Signaling Pathway Impact Analysis (SPIA) is a software package that analyzes gene expression data to identify whether a pathway is relevant in a given condition. We present the results of a study that uses SPIA to investigate all 157 signaling pathways in the KEGG PATHWAY database. We analyzed each of the ten cancer types mentioned above separately, and we perform a pan-cancer analysis by grouping the data for all the cancer types. In each analysis several pathways were found to be markedly more significant than all the other pathways. We call them notable. Research has already established a connection between many of these pathways and the corresponding cancer type. However, some of our discovered pathways appear to be new findings. Altogether there were 37 notable findings in the separate analyses, 26 of them occurred in 7 pathways. These 7 pathways included the 4 notable pathways discovered in the pan-cancer analysis. So, our results suggest that these 7 pathways account for much of the mechanisms of cancer. Furthermore, by looking at the overlap among pathways, we identified possible regions on the pathways where the aberrant activity is occurring. We obtained 37 notable findings concerning 18 pathways. Some of them appear to be

Integrated analysis of breast cancer cell lines reveals unique signaling pathways

Energy Technology Data Exchange (ETDEWEB)

Heiser, Laura M.; Wang, Nicholas J.; Talcott, Carolyn L.; Laderoute, Keith R.; Knapp, Merrill; Guan, Yinghui; Hu, Zhi; Ziyad, Safiyyah; Weber, Barbara L.; Laquerre, Sylvie; Jackson, Jeffrey R.; Wooster, Richard F.; Kuo, Wen-Lin; Gray, Joe W.; Spellman, Paul T.

2009-03-31

Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EGFR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes. We were interested in identifying subnetworks within the EGFR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EGFR-MEK signaling. This model was comprised of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype specific subnetworks, including one that suggested PAK1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that PAK1 overexpressing cell lines would have increased sensitivity to MEK inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three MEK inhibitors. We found that PAK1 over-expressing luminal breast cancer cell lines are significantly more sensitive to MEK inhibition as compared to those that express PAK1 at low levels. This indicates that PAK1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to MEK inhibitors. All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.

Integrated analysis of breast cancer cell lines reveals unique signaling pathways.

Science.gov (United States)

Heiser, Laura M; Wang, Nicholas J; Talcott, Carolyn L; Laderoute, Keith R; Knapp, Merrill; Guan, Yinghui; Hu, Zhi; Ziyad, Safiyyah; Weber, Barbara L; Laquerre, Sylvie; Jackson, Jeffrey R; Wooster, Richard F; Kuo, Wen Lin; Gray, Joe W; Spellman, Paul T

2009-01-01

Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EgfR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes. We were interested in identifying subnetworks within the EgfR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EgfR-MAPK signaling. This model was composed of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype-specific subnetworks, including one that suggested Pak1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that Pak1 over-expressing cell lines would have increased sensitivity to Mek inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three Mek inhibitors. We found that Pak1 over-expressing luminal breast cancer cell lines are significantly more sensitive to Mek inhibition compared to those that express Pak1 at low levels. This indicates that Pak1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to Mek inhibitors. All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.

Integrating computational methods to retrofit enzymes to synthetic pathways.

Science.gov (United States)

Brunk, Elizabeth; Neri, Marilisa; Tavernelli, Ivano; Hatzimanikatis, Vassily; Rothlisberger, Ursula

2012-02-01

Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target compounds with high yields and turnover rates. We use integrated computational methods to generate and quantify the performance of novel biosynthetic routes that contain highly optimized catalysts. Engineering a novel reaction pathway entails addressing feasibility on multiple levels, which involves handling the complexity of large-scale biochemical networks while respecting the critical chemical phenomena at the atomistic scale. To pursue this multi-layer challenge, our strategy merges knowledge-based metabolic engineering methods with computational chemistry methods. By bridging multiple disciplines, we provide an integral computational framework that could accelerate the discovery and implementation of novel biosynthetic production routes. Using this approach, we have identified and optimized a novel biosynthetic route for the production of 3HP from pyruvate. Copyright © 2011 Wiley Periodicals, Inc.

RAMM: a system of computer programs for radionuclide pathway analysis calculations

International Nuclear Information System (INIS)

Lyon, R.B.

1976-09-01

A generalized system of computer programs, designated RAMM (Radioactive Materials Management) system, has been developed to assist in the analysis of the movement of radionuclides through the environment to man. RAMM incorporates the GASP IV continuous/discrete simulation system. A nodal approach is used whereby the system to be analyzed is split up into parts small enough that the distribution of nuclides within the node may be taken to be homogeneous. Pathways are defined between nodes, and appropriate transfer coefficients are input or generated. Output includes the time dependent contents of the nodes and dose rates, integrated doses and dose commitments of selected nodes. (author)

PyPathway: Python Package for Biological Network Analysis and Visualization.

Science.gov (United States)

Xu, Yang; Luo, Xiao-Chun

2018-05-01

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

Evolution of the New Pathway curriculum at Harvard Medical School: the new integrated curriculum.

Science.gov (United States)

Dienstag, Jules L

2011-01-01

In 1985, Harvard Medical School adopted a "New Pathway" curriculum, based on active, adult learning through problem-based, faculty-facilitated small-group tutorials designed to promote lifelong skills of self-directed learning. Despite the successful integration of clinically relevant material in basic science courses, the New Pathway goals were confined primarily to the preclinical years. In addition, the shifting balance in the delivery of health care from inpatient to ambulatory settings limited the richness of clinical education in clinical clerkships, creating obstacles for faculty in their traditional roles as teachers. In 2006, Harvard Medical School adopted a more integrated curriculum based on four principles that emerged after half a decade of self-reflection and planning: (1) integrate the teaching of basic/population science and clinical medicine throughout the entire student experience; (2) reestablish meaningful and intensive faculty-student interactions and reengage the faculty; (3) develop a new model of clinical education that offers longitudinal continuity of patient experience, cross-disciplinary curriculum, faculty mentoring, and student evaluation; and (4) provide opportunities for all students to pursue an in-depth, faculty-mentored scholarly project. These principles of our New Integrated Curriculum reflect our vision for a curriculum that fosters a partnership between students and faculty in the pursuit of scholarship and leadership.

Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis)

Science.gov (United States)

Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang

2015-01-01

Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology. PMID:25901577

Re-Structuring Preservice Teacher Education: Introducing the School-Community Integrated Learning (SCIL) Pathway

Science.gov (United States)

Hudson, Sue; Hudson, Peter

2013-01-01

Reviews into teacher education call for new models that develop preservice teachers' practical knowledge and skills. The study involved 9 mentor teachers and 14 mentees (final-year preservice teachers) working in a new teacher education model, the School-Community Integrated Learning (SCIL) pathway, and analysed data from a Likert survey with…

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

International Nuclear Information System (INIS)

Fukunaga, Satoki; Kakehashi, Anna; Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki; Gi, Min; Wanibuchi, Hideki

2015-01-01

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

Energy Technology Data Exchange (ETDEWEB)

Fukunaga, Satoki [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Kakehashi, Anna [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Sumida, Kayo; Kushida, Masahiko; Asano, Hiroyuki [Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558 (Japan); Gi, Min [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan); Wanibuchi, Hideki, E-mail: wani@med.osaka-cu.ac.jp [Department of Molecular Pathology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585 (Japan)

2015-08-01

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.

Mechanisms and mediation in survival analysis: towards an integrated analytical framework

Directory of Open Access Journals (Sweden)

Jonathan Pratschke

2016-02-01

Full Text Available Abstract Background A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare. Methods The authors begin by summarising debates on causal inference, mediated effects and statistical models, showing that these three strands of research have powerful synergies. They review a range of approaches which seek to extend existing survival models to obtain valid estimates of mediation effects. They then argue for an alternative strategy, which involves integrating survival outcomes within Structural Equation Models via the discrete-time survival model. This approach can provide an integrated framework for studying mediation effects in relation to survival outcomes, an issue of great relevance in applied health research. The authors provide an example of how these techniques can be used to explore whether the social class position of patients has a significant indirect effect on the hazard of death from colon cancer. Results The results suggest that the indirect effects of social class on survival are substantial and negative (-0.23 overall. In addition to the substantial direct effect of this variable (-0.60, its indirect effects account for more than one quarter of the total effect. The two main pathways for this indirect effect, via emergency admission (-0.12, on the one hand, and hospital caseload, on the other, (-0.10 are of similar size. Conclusions The discrete-time survival model provides an attractive way of integrating time-to-event data within the field of

Mechanisms and mediation in survival analysis: towards an integrated analytical framework.

Science.gov (United States)

Pratschke, Jonathan; Haase, Trutz; Comber, Harry; Sharp, Linda; de Camargo Cancela, Marianna; Johnson, Howard

2016-02-29

A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare. The authors begin by summarising debates on causal inference, mediated effects and statistical models, showing that these three strands of research have powerful synergies. They review a range of approaches which seek to extend existing survival models to obtain valid estimates of mediation effects. They then argue for an alternative strategy, which involves integrating survival outcomes within Structural Equation Models via the discrete-time survival model. This approach can provide an integrated framework for studying mediation effects in relation to survival outcomes, an issue of great relevance in applied health research. The authors provide an example of how these techniques can be used to explore whether the social class position of patients has a significant indirect effect on the hazard of death from colon cancer. The results suggest that the indirect effects of social class on survival are substantial and negative (-0.23 overall). In addition to the substantial direct effect of this variable (-0.60), its indirect effects account for more than one quarter of the total effect. The two main pathways for this indirect effect, via emergency admission (-0.12), on the one hand, and hospital caseload, on the other, (-0.10) are of similar size. The discrete-time survival model provides an attractive way of integrating time-to-event data within the field of Structural Equation Modelling. The authors demonstrate the efficacy

Critical assessment of human metabolic pathway databases: a stepping stone for future integration

Directory of Open Access Journals (Sweden)

Stobbe Miranda D

2011-10-01

Full Text Available Abstract Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison

A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.

Science.gov (United States)

Lai, En-Yu; Chen, Yi-Hau; Wu, Kun-Pin

2017-06-01

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https

Nonassociative learning as gated neural integrator and differentiator in stimulus-response pathways

Directory of Open Access Journals (Sweden)

Young Daniel L

2006-08-01

Full Text Available Abstract Nonassociative learning is a basic neuroadaptive behavior exhibited across animal phyla and sensory modalities but its role in brain intelligence is unclear. Current literature on habituation and sensitization, the classic "dual process" of nonassociative learning, gives highly incongruous accounts between varying experimental paradigms. Here we propose a general theory of nonassociative learning featuring four base modes: habituation/primary sensitization in primary stimulus-response pathways, and desensitization/secondary sensitization in secondary stimulus-response pathways. Primary and secondary modes of nonassociative learning are distinguished by corresponding activity-dependent recall, or nonassociative gating, of neurotransmission memory. From the perspective of brain computation, nonassociative learning is a form of integral-differential calculus whereas nonassociative gating is a form of Boolean logic operator – both dynamically transforming the stimulus-response relationship. From the perspective of sensory integration, nonassociative gating provides temporal filtering whereas nonassociative learning affords low-pass, high-pass or band-pass/band-stop frequency filtering – effectively creating an intelligent sensory firewall that screens all stimuli for attention and resultant internal model adaptation and reaction. This unified framework ties together many salient characteristics of nonassociative learning and nonassociative gating and suggests a common kernel that correlates with a wide variety of sensorimotor integration behaviors such as central resetting and self-organization of sensory inputs, fail-safe sensorimotor compensation, integral-differential and gated modulation of sensorimotor feedbacks, alarm reaction, novelty detection and selective attention, as well as a variety of mental and neurological disorders such as sensorimotor instability, attention deficit hyperactivity, sensory defensiveness, autism

Pathway Analysis in Attention Deficit Hyperactivity Disorder: An Ensemble Approach

Science.gov (United States)

Mooney, Michael A.; McWeeney, Shannon K.; Faraone, Stephen V.; Hinney, Anke; Hebebrand, Johannes; Nigg, Joel T.; Wilmot, Beth

2016-01-01

Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. PMID:27004716

Portuguese Older Gay Men: Pathways to Family Integrity

Directory of Open Access Journals (Sweden)

Filipa Daniela Marques

2016-08-01

Full Text Available Abstract Research in the field of older gay men remains scarce. This exploratory study examines older gay men's experiences in the construction of family integrity (versus disconnection and alienation. The family integrity approach is a developmental perspective that links ego integrity to a larger process of constructing meaning within the family system. The sample comprises ten participants (from 60 to 88 years old. A semi-structured interview was conducted and submitted to content analysis. The main findings suggest three experiences in older gay men's construction of family integrity: (i influence of homosexuality throughout life; (ii establishing a family of choice; (iii creating a legacy associated with homosexuality. Family integrity in older gay men seems to evolve from disclosure at a young age to making homosexuality a legacy in old age.

Integrative cluster analysis in bioinformatics

CERN Document Server

Abu-Jamous, Basel; Nandi, Asoke K

2015-01-01

Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o

An efficient tool for metabolic pathway construction and gene integration for Aspergillus niger.

Science.gov (United States)

Sarkari, Parveen; Marx, Hans; Blumhoff, Marzena L; Mattanovich, Diethard; Sauer, Michael; Steiger, Matthias G

2017-12-01

Metabolic engineering requires functional genetic tools for easy and quick generation of multiple pathway variants. A genetic engineering toolbox for A. niger is presented, which facilitates the generation of strains carrying heterologous expression cassettes at a defined genetic locus. The system is compatible with Golden Gate cloning, which facilitates the DNA construction process and provides high design flexibility. The integration process is mediated by a CRISPR/Cas9 strategy involving the cutting of both the genetic integration locus (pyrG) as well as the integrating plasmid. Only a transient expression of Cas9 is necessary and the carrying plasmid is readily lost using a size-reduced AMA1 variant. A high integration efficiency into the fungal genome of up to 100% can be achieved, thus reducing the screening process significantly. The feasibility of the approach was demonstrated by the integration of an expression cassette enabling the production of aconitic acid in A. niger. Copyright © 2017 Elsevier Ltd. All rights reserved.

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

Directory of Open Access Journals (Sweden)

Lockwood William W

2010-05-01

Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

Obsessive-compulsive disorder, which genes? Which functions? Which pathways? An integrated holistic view regarding OCD and its complex genetic etiology.

Science.gov (United States)

Bozorgmehr, Ali; Ghadirivasfi, Mohammad; Shahsavand Ananloo, Esmaeil

2017-09-01

Obsessive-compulsive disorder (OCD) is characterized by recurrent obtrusive and repetitive acts typically occurred following anxiety. In the last two decades, studies done on the gene sequences, large-scale and point mutations and gene-gene, gene-environment and gene-drug interactions have led to the discovery of hundreds of genes associated with OCD. Although each gene in turn is a part of the etiology of this disorder; however, OCD, like other mental disorders is complex and a comprehensive and integrated view is necessary to understand its genetic basis. In this study, through an extensive review of existing published studies, all genes associated with OCD were found. Then, in order to integrate the results, all the interactions between these genes were explored and the achievement was represented as an interactive genetic network. Furthermore, the reconstructed network was analyzed. It was found that GRIN2A, GRIN2B and GRIA2 are the most central nodes in the network. Functional and pathway enrichment analysis showed that glutamate-related pathways are the main deficient systems in patients with OCD. By studying genes shared between OCD and other diseases, it was cleared that OCD, epilepsy and some types of cancer have the most number of shared genes. The results of this study, in addition to reviewing the available results as a comprehensive and integrated manner, provide new hypotheses for future studies.

Pathway analysis for alternate low-level waste disposal methods

International Nuclear Information System (INIS)

Rao, R.R.; Kozak, M.W.; McCord, J.T.; Olague, N.E.

1992-01-01

The purpose of this paper is to evaluate a complete set of environmental pathways for disposal options and conditions that the Nuclear Regulatory Commission (NRC) may analyze for a low-level radioactive waste (LLW) license application. The regulations pertaining In the past, shallow-land burial has been used for the disposal of low-level radioactive waste. However, with the advent of the State Compact system of LLW disposal, many alternative technologies may be used. The alternative LLW disposal facilities include below- ground vault, tumulus, above-ground vault, shaft, and mine disposal This paper will form the foundation of an update of the previously developed Sandia National Laboratories (SNL)/NRC LLW performance assessment methodology. Based on the pathway assessment for alternative disposal methods, a determination will be made about whether the current methodology can satisfactorily analyze the pathways and phenomena likely to be important for the full range of potential disposal options. We have attempted to be conservative in keeping pathways in the lists that may usually be of marginal importance. In this way we can build confidence that we have spanned the range of cases likely to be encountered at a real site. Results of the pathway assessment indicate that disposal methods can be categorized in groupings based on their depth of disposal. For the deep disposal options of shaft and mine disposal, the key pathways are identical. The shallow disposal options, such as tumulus, shallow-land, and below-ground vault disposal also may be grouped together from a pathway analysis perspective. Above-ground vault disposal cannot be grouped with any of the other disposal options. The pathway analysis shows a definite trend concerning depth of disposal. The above-ground option has the largest number of significant pathways. As the waste becomes more isolated, the number of significant pathways is reduced. Similar to shallow-land burial, it was found that for all

An evaluation of the implementation of maternal obesity pathways of care: a mixed methods study with data integration.

Directory of Open Access Journals (Sweden)

Nicola Heslehurst

Full Text Available Maternal obesity has multiple associated risks and requires substantial intervention. This research evaluated the implementation of maternal obesity care pathways from multiple stakeholder perspectives.A simultaneous mixed methods model with data integration was used. Three component studies were given equal priority. 1: Semi-structured qualitative interviews explored obese pregnant women's experiences of being on the pathways. 2: A quantitative and qualitative postal survey explored healthcare professionals' experiences of delivering the pathways. 3: A case note audit quantitatively assessed pathway compliance. Data were integrated using following a thread and convergence coding matrix methods to search for agreement and disagreement between studies.Study 1: Four themes were identified: women's overall (positive and negative views of the pathways; knowledge and understanding of the pathways; views on clinical and weight management advice and support; and views on the information leaflet. Key results included positive views of receiving additional clinical care, negative experiences of risk communication, and weight management support was considered a priority. Study 2: Healthcare professionals felt the pathways were worthwhile, facilitated good practice, and increased confidence. Training was consistently identified as being required. Healthcare professionals predominantly focussed on women's response to sensitive obesity communication. Study 3: There was good compliance with antenatal clinical interventions. However, there was poor compliance with public health and postnatal interventions. There were some strong areas of agreement between component studies which can inform future development of the pathways. However, disagreement between studies included a lack of shared priorities between healthcare professionals and women, different perspectives on communication issues, and different perspectives on women's prioritisation of weight

An Evaluation of the Implementation of Maternal Obesity Pathways of Care: A Mixed Methods Study with Data Integration

Science.gov (United States)

Heslehurst, Nicola; Dinsdale, Sarah; Sedgewick, Gillian; Simpson, Helen; Sen, Seema; Summerbell, Carolyn Dawn; Rankin, Judith

2015-01-01

Objectives Maternal obesity has multiple associated risks and requires substantial intervention. This research evaluated the implementation of maternal obesity care pathways from multiple stakeholder perspectives. Study Design A simultaneous mixed methods model with data integration was used. Three component studies were given equal priority. 1: Semi-structured qualitative interviews explored obese pregnant women’s experiences of being on the pathways. 2: A quantitative and qualitative postal survey explored healthcare professionals’ experiences of delivering the pathways. 3: A case note audit quantitatively assessed pathway compliance. Data were integrated using following a thread and convergence coding matrix methods to search for agreement and disagreement between studies. Results Study 1: Four themes were identified: women’s overall (positive and negative) views of the pathways; knowledge and understanding of the pathways; views on clinical and weight management advice and support; and views on the information leaflet. Key results included positive views of receiving additional clinical care, negative experiences of risk communication, and weight management support was considered a priority. Study 2: Healthcare professionals felt the pathways were worthwhile, facilitated good practice, and increased confidence. Training was consistently identified as being required. Healthcare professionals predominantly focussed on women’s response to sensitive obesity communication. Study 3: There was good compliance with antenatal clinical interventions. However, there was poor compliance with public health and postnatal interventions. There were some strong areas of agreement between component studies which can inform future development of the pathways. However, disagreement between studies included a lack of shared priorities between healthcare professionals and women, different perspectives on communication issues, and different perspectives on women�

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

Science.gov (United States)

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

Science.gov (United States)

Scorcioni, Ruggero; Wright, Susan N; Patrick Card, J; Ascoli, Giorgio A; Barrionuevo, Germán

2008-01-01

The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE

Directory of Open Access Journals (Sweden)

Constantinos Yeles

2017-11-01

Full Text Available Ionizing radiation-induced bystander effects (RIBE encompass a number of effects with potential for a plethora of damages in adjacent non-irradiated tissue. The cascade of molecular events is initiated in response to the exposure to ionizing radiation (IR, something that may occur during diagnostic or therapeutic medical applications. In order to better investigate these complex response mechanisms, we employed a unified framework integrating statistical microarray analysis, signal normalization, and translational bioinformatics functional analysis techniques. This approach was applied to several microarray datasets from Gene Expression Omnibus (GEO related to RIBE. The analysis produced lists of differentially expressed genes, contrasting bystander and irradiated samples versus sham-irradiated controls. Furthermore, comparative molecular analysis through BioInfoMiner, which integrates advanced statistical enrichment and prioritization methodologies, revealed discrete biological processes, at the cellular level. For example, the negative regulation of growth, cellular response to Zn2+-Cd2+, and Wnt and NIK/NF-kappaB signaling, thus refining the description of the phenotypic landscape of RIBE. Our results provide a more solid understanding of RIBE cell-specific response patterns, especially in the case of high-LET radiations, like α-particles and carbon-ions.

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

International Nuclear Information System (INIS)

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2008-01-01

Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.

Science.gov (United States)

Papatheodorou, Irene; Ziehm, Matthias; Wieser, Daniela; Alic, Nazif; Partridge, Linda; Thornton, Janet M

2012-01-01

A challenge of systems biology is to integrate incomplete knowledge on pathways with existing experimental data sets and relate these to measured phenotypes. Research on ageing often generates such incomplete data, creating difficulties in integrating RNA expression with information about biological processes and the phenotypes of ageing, including longevity. Here, we develop a logic-based method that employs Answer Set Programming, and use it to infer signalling effects of genetic perturbations, based on a model of the insulin signalling pathway. We apply our method to RNA expression data from Drosophila mutants in the insulin pathway that alter lifespan, in a foxo dependent fashion. We use this information to deduce how the pathway influences lifespan in the mutant animals. We also develop a method for inferring the largest common sub-paths within each of our signalling predictions. Our comparisons reveal consistent homeostatic mechanisms across both long- and short-lived mutants. The transcriptional changes observed in each mutation usually provide negative feedback to signalling predicted for that mutation. We also identify an S6K-mediated feedback in two long-lived mutants that suggests a crosstalk between these pathways in mutants of the insulin pathway, in vivo. By formulating the problem as a logic-based theory in a qualitative fashion, we are able to use the efficient search facilities of Answer Set Programming, allowing us to explore larger pathways, combine molecular changes with pathways and phenotype and infer effects on signalling in in vivo, whole-organism, mutants, where direct signalling stimulation assays are difficult to perform. Our methods are available in the web-service NetEffects: http://www.ebi.ac.uk/thornton-srv/software/NetEffects.

A microRNA activity map of human mesenchymal tumors: connections to oncogenic pathways; an integrative transcriptomic study

Directory of Open Access Journals (Sweden)

Fountzilas Elena

2012-07-01

Full Text Available Abstract Background MicroRNAs (miRNAs are nucleic acid regulators of many human mRNAs, and are associated with many tumorigenic processes. miRNA expression levels have been used in profiling studies, but some evidence suggests that expression levels do not fully capture miRNA regulatory activity. In this study we integrate multiple gene expression datasets to determine miRNA activity patterns associated with cancer phenotypes and oncogenic pathways in mesenchymal tumors – a very heterogeneous class of malignancies. Results Using a computational method, we identified differentially activated miRNAs between 77 normal tissue specimens and 135 sarcomas and we validated many of these findings with microarray interrogation of an independent, paraffin-based cohort of 18 tumors. We also showed that miRNA activity is imperfectly correlated with miRNA expression levels. Using next-generation miRNA sequencing we identified potential base sequence alterations which may explain differential activity. We then analyzed miRNA activity changes related to the RAS-pathway and found 21 miRNAs that switch from silenced to activated status in parallel with RAS activation. Importantly, nearly half of these 21 miRNAs were predicted to regulate integral parts of the miRNA processing machinery, and our gene expression analysis revealed significant reductions of these transcripts in RAS-active tumors. These results suggest an association between RAS signaling and miRNA processing in which miRNAs may attenuate their own biogenesis. Conclusions Our study represents the first gene expression-based investigation of miRNA regulatory activity in human sarcomas, and our findings indicate that miRNA activity patterns derived from integrated transcriptomic data are reproducible and biologically informative in cancer. We identified an association between RAS signaling and miRNA processing, and demonstrated sequence alterations as plausible causes for differential miRNA activity

Impacts of agricultural land use on biological integrity: A causal analysis

Science.gov (United States)

Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

2011-01-01

Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and

Integrative analysis of the mitochondrial proteome in yeast.

Directory of Open Access Journals (Sweden)

Holger Prokisch

2004-06-01

Full Text Available In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.

KeyPathwayMiner 4.0

DEFF Research Database (Denmark)

Alcaraz, Nicolas; Pauling, Josch; Batra, Richa

2014-01-01

release of KeyPathwayMiner (version 4.0) that is not limited to analyses of single omics data sets, e.g. gene expression, but is able to directly combine several different omics data types. Version 4.0 can further integrate existing knowledge by adding a search bias towards sub-networks that contain...... (avoid) genes provided in a positive (negative) list. Finally the new release now also provides a set of novel visualization features and has been implemented as an app for the standard bioinformatics network analysis tool: Cytoscape. CONCLUSION: With KeyPathwayMiner 4.0, we publish a Cytoscape app...

Text mining in cancer gene and pathway prioritization.

Science.gov (United States)

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

Science.gov (United States)

Lee, Hyeonjeong; Shin, Miyoung

2017-01-01

The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

Directory of Open Access Journals (Sweden)

Robin Donaldson

2010-02-01

Full Text Available Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising parallel composition of instances of generic modules (with internal and external labels. Pathways are then composed by (synchronising parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways.

Patients' experiences and care needs during the diagnostic phase of an Integrated Brain Cancer Pathway

DEFF Research Database (Denmark)

Vedelø, Tina Wang; Sørensen, Jens Christian Hedemann; Delmar, Charlotte

2018-01-01

of brain cancer, not knowing what to expect and participants' perceptions of the relationship with the health care providers. The analysis revealed that participants were in risk of having unmet information needs and that contextual factors seemed to cause fragmented care that led to feelings...... that the shock of the diagnosis, combined with the multiple symptoms, affect patients' ability to understand information and express needs of care and support. Unmet needs have been reported within this group of patients, however, the experiences and care needs of patients going through the diagnostic phase...... of a standardised Integrated Brain Cancer Pathway have not previously been explored. DESIGN: A Case Study design was used to provide detailed information of the complex needs of patients being diagnosed with a malignant brain tumour. METHODS: Research interviews and direct participant observation of four patients...

Integrative analysis of circRNAs acting as ceRNAs involved in ethylene pathway in tomato.

Science.gov (United States)

Wang, Yunxiang; Wang, Qing; Gao, Lipu; Zhu, Benzhong; Luo, Yunbo; Deng, Zhiping; Zuo, Jinhua

2017-11-01

Circular RNAs (circRNAs) are a large class of non-coding endogenous RNAs that could act as competing endogenous RNAs (ceRNAs) to terminate the mRNA targets' suppression of miRNAs. To elucidate the intricate regulatory roles of circRNAs in the ethylene pathway in tomato fruit, deep sequencing and bioinformatics methods were performed. After strict screening, a total of 318 circRNAs were identified. Among these circRNAs, 282 were significantly differentially expressed among wild-type and sense-/antisense-LeERF1 transgenic tomato fruits. Besides, 1254 target genes were identified and a large amount of them were found to be involved in ethylene pathway. In addition, a sophisticated regulatory model consisting of circRNAs, target genes and ethylene was set up. Importantly, 61 circRNAs were found to be potential ceRNAs to combine with miRNAs and some of the miRNAs had been revealed to participate in the ethylene signaling pathway. This research further raised the possibility that the ethylene pathway in tomato fruit may be under the regulation of various circRNAs and provided a new perspective of the roles of circRNAs. © 2017 Scandinavian Plant Physiology Society.

Effects of clinical pathways in the joint replacement: a meta-analysis

Directory of Open Access Journals (Sweden)

Faggiano F

2009-07-01

Full Text Available Abstract Background A meta-analysis was performed to evaluate the use of clinical pathways for hip and knee joint replacements when compared with standard medical care. The impact of clinical pathways was evaluated assessing the major outcomes of in-hospital hip and knee joint replacement processes: postoperative complications, number of patients discharged at home, length of in-hospital stay and direct costs. Methods Medline, Cinahl, Embase and the Cochrane Central Register of Controlled Trials were searched. The search was performed from 1975 to 2007. Each study was assessed independently by two reviewers. The assessment of methodological quality of the included studies was based on the Jadad methodological approach and on the New Castle Ottawa Scale. Data analysis abided by the guidelines set out by The Cochrane Collaboration regarding statistical methods. Meta-analyses were performed using RevMan software, version 4.2. Results Twenty-two studies met the study inclusion criteria and were included in the meta-analysis for a total sample of 6,316 patients. The aggregate overall results showed significantly fewer patients suffering postoperative complications in the clinical pathways group when compared with the standard care group. A shorter length of stay in the clinical pathway group was also observed and lower costs during hospital stay were associated with the use of the clinical pathways. No significant differences were found in the rates of discharge to home. Conclusion The results of this meta-analysis show that clinical pathways can significantly improve the quality of care even if it is not possible to conclude that the implementation of clinical pathways is a cost-effective process, because none of the included studies analysed the cost of the development and implementation of the pathways. Based on the results we assume that pathways have impact on the organisation of care if the care process is structured in a standardised way

An integrated analysis of genes and pathways exhibiting metabolic differences between estrogen receptor positive breast cancer cells

International Nuclear Information System (INIS)

Mandal, Soma; Davie, James R

2007-01-01

The sex hormone estrogen (E2) is pivotal to normal mammary gland growth and differentiation and in breast carcinogenesis. In this in silico study, we examined metabolic differences between ER(+)ve breast cancer cells during E2 deprivation. Public repositories of SAGE and MA gene expression data generated from E2 deprived ER(+)ve breast cancer cell lines, MCF-7 and ZR75-1 were compared with normal breast tissue. We analyzed gene ontology (GO), enrichment, clustering, chromosome localization, and pathway profiles and performed multiple comparisons with cell lines and tumors with different ER status. In all GO terms, biological process (BP), molecular function (MF), and cellular component (CC), MCF-7 had higher gene utilization than ZR75-1. Various analyses showed a down-regulated immune function, an up-regulated protein (ZR75-1) and glucose metabolism (MCF-7). A greater percentage of 77 common genes localized to the q arm of all chromosomes, but in ZR75-1 chromosomes 11, 16, and 19 harbored more overexpressed genes. Despite differences in gene utilization (electron transport, proteasome, glycolysis/gluconeogenesis) and expression (ribosome) in both cells, there was an overall similarity of ZR75-1 with ER(-)ve cell lines and ER(+)ve/ER(-)ve breast tumors. This study demonstrates integral metabolic differences may exist within the same cell subtype (luminal A) in representative ER(+)ve cell line models. Selectivity of gene and pathway usage for strategies such as energy requirement minimization, sugar utilization by ZR75-1 contrasted with MCF-7 cells, expressing genes whose protein products require ATP utilization. Such characteristics may impart aggressiveness to ZR75-1 and may be prognostic determinants of ER(+)ve breast tumors

Genetic variants in two pathways influence serum urate levels and gout risk: a systematic pathway analysis.

Science.gov (United States)

Dong, Zheng; Zhou, Jingru; Xu, Xia; Jiang, Shuai; Li, Yuan; Zhao, Dongbao; Yang, Chengde; Ma, Yanyun; Wang, Yi; He, Hongjun; Ji, Hengdong; Zhang, Juan; Yuan, Ziyu; Yang, Yajun; Wang, Xiaofeng; Pang, Yafei; Jin, Li; Zou, Hejian; Wang, Jiucun

2018-03-01

The aims of this study were to identify candidate pathways associated with serum urate and to explore the genetic effect of those pathways on the risk of gout. Pathway analysis of the loci identified in genome-wide association studies (GWASs) showed that the ion transmembrane transporter activity pathway (GO: 0015075) and the secondary active transmembrane transporter activity pathway (GO: 0015291) were both associated with serum urate concentrations, with P FDR values of 0.004 and 0.007, respectively. In a Chinese population of 4,332 individuals, the two pathways were also found to be associated with serum urate (P FDR  = 1.88E-05 and 3.44E-04, separately). In addition, these two pathways were further associated with the pathogenesis of gout (P FDR  = 1.08E-08 and 2.66E-03, respectively) in the Chinese population and a novel gout-associated gene, SLC17A2, was identified (OR = 0.83, P FDR  = 0.017). The mRNA expression of candidate genes also showed significant differences among different groups at pathway level. The present study identified two transmembrane transporter activity pathways (GO: 0015075 and GO: 0015291) were associations with serum urate concentrations and the risk of gout. SLC17A2 was identified as a novel gene that influenced the risk of gout.

Application of Monte Carlo cross-validation to identify pathway cross-talk in neonatal sepsis.

Science.gov (United States)

Zhang, Yuxia; Liu, Cui; Wang, Jingna; Li, Xingxia

2018-03-01

To explore genetic pathway cross-talk in neonates with sepsis, an integrated approach was used in this paper. To explore the potential relationships between differently expressed genes between normal uninfected neonates and neonates with sepsis and pathways, genetic profiling and biologic signaling pathway were first integrated. For different pathways, the score was obtained based upon the genetic expression by quantitatively analyzing the pathway cross-talk. The paired pathways with high cross-talk were identified by random forest classification. The purpose of the work was to find the best pairs of pathways able to discriminate sepsis samples versus normal samples. The results found 10 pairs of pathways, which were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways were identified according to analysis of extensive literature. Impact statement To find the best pairs of pathways able to discriminate sepsis samples versus normal samples, an RF classifier, the DS obtained by DEGs of paired pathways significantly associated, and Monte Carlo cross-validation were applied in this paper. Ten pairs of pathways were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways ((7) IL-6 Signaling and Phospholipase C Signaling (PLC); (8) Glucocorticoid Receptor (GR) Signaling and Dendritic Cell Maturation) were identified according to analysis of extensive literature.

Chicken hepatic response to chronic heat stress using integrated transcriptome and metabolome analysis.

Directory of Open Access Journals (Sweden)

Sara F Jastrebski

Full Text Available The liver plays a central role in metabolism and is important in maintaining homeostasis throughout the body. This study integrated transcriptomic and metabolomic data to understand how the liver responds under chronic heat stress. Chickens from a rapidly growing broiler line were heat stressed for 8 hours per day for one week and liver samples were collected at 28 days post hatch. Transcriptome analysis reveals changes in genes responsible for cell cycle regulation, DNA replication, and DNA repair along with immune function. Integrating the metabolome and transcriptome data highlighted multiple pathways affected by heat stress including glucose, amino acid, and lipid metabolism along with glutathione production and beta-oxidation.

Integrated Genome-Based Studies of Shewanella Ecophysiology

Energy Technology Data Exchange (ETDEWEB)

Andrei L. Osterman, Ph.D.

2012-12-17

Integration of bioinformatics and experimental techniques was applied to mapping and characterization of the key components (pathways, enzymes, transporters, regulators) of the core metabolic machinery in Shewanella oneidensis and related species with main focus was on metabolic and regulatory pathways involved in utilization of various carbon and energy sources. Among the main accomplishments reflected in ten joint publications with other participants of Shewanella Federation are: (i) A systems-level reconstruction of carbohydrate utilization pathways in the genus of Shewanella (19 species). This analysis yielded reconstruction of 18 sugar utilization pathways including 10 novel pathway variants and prediction of > 60 novel protein families of enzymes, transporters and regulators involved in these pathways. Selected functional predictions were verified by focused biochemical and genetic experiments. Observed growth phenotypes were consistent with bioinformatic predictions providing strong validation of the technology and (ii) Global genomic reconstruction of transcriptional regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors, 8 riboswitches and 6 translational attenuators. Of those, 45 regulons were inferred directly from the genome context analysis, whereas others were propagated from previously characterized regulons in other species. Selected regulatory predictions were experimentally tested. Integration of this analysis with microarray data revealed overall consistency and provided additional layer of interactions between regulons. All the results were captured in the new database RegPrecise, which is a joint development with the LBNL team. A more detailed analysis of the individual subsystems, pathways and regulons in Shewanella spp included bioinfiormatics-based prediction and experimental characterization of: (i) N-Acetylglucosamine catabolic pathway; (ii)Lactate utilization machinery; (iii) Novel Nrt

SNP-based pathway enrichment analysis for genome-wide association studies

Directory of Open Access Journals (Sweden)

Potkin Steven G

2011-04-01

Full Text Available Abstract Background Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs, have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs. Results We describe a SNP-based pathway enrichment method for GWAS studies. The method consists of the following two main steps: 1 for a given pathway, using an adaptive truncated product statistic to identify all representative (potentially more than one SNPs of each gene, calculating the average number of representative SNPs for the genes, then re-selecting the representative SNPs of genes in the pathway based on this number; and 2 ranking all selected SNPs by the significance of their statistical association with a trait of interest, and testing if the set of SNPs from a particular pathway is significantly enriched with high ranks using a weighted Kolmogorov-Smirnov test. We applied our method to two large genetically distinct GWAS data sets of schizophrenia, one

Respiromics – An integrative analysis linking mitochondrial bioenergetics to molecular signatures

Directory of Open Access Journals (Sweden)

Ellen Walheim

2018-03-01

Full Text Available Objective: Energy metabolism is challenged upon nutrient stress, eventually leading to a variety of metabolic diseases that represent a major global health burden. Methods: Here, we combine quantitative mitochondrial respirometry (Seahorse technology and proteomics (LC-MS/MS-based total protein approach to understand how molecular changes translate to changes in mitochondrial energy transduction during diet-induced obesity (DIO in the liver. Results: The integrative analysis reveals that significantly increased palmitoyl-carnitine respiration is supported by an array of proteins enriching lipid metabolism pathways. Upstream of the respiratory chain, the increased capacity for ATP synthesis during DIO associates strongest to mitochondrial uptake of pyruvate, which is routed towards carboxylation. At the respiratory chain, robust increases of complex I are uncovered by cumulative analysis of single subunit concentrations. Specifically, nuclear-encoded accessory subunits, but not mitochondrial-encoded or core units, appear to be permissive for enhanced lipid oxidation. Conclusion: Our integrative analysis, that we dubbed “respiromics”, represents an effective tool to link molecular changes to functional mechanisms in liver energy metabolism, and, more generally, can be applied for mitochondrial analysis in a variety of metabolic and mitochondrial disease models. Keywords: Mitochondria, Respirometry, Proteomics, Mitochondrial pyruvate carrier, Liver disease, Bioenergetics, Obesity, Diabetes

In silico analysis of phytohormone metabolism and communication pathways in citrus transcriptome

Directory of Open Access Journals (Sweden)

Vera Quecini

2007-01-01

Full Text Available Plant hormones play a crucial role in integrating endogenous and exogenous signals and in determining developmental responses to form the plant body throughout its life cycle. In citrus species, several economically important processes are controlled by phytohormones, including seed germination, secondary growth, fruit abscission and ripening. Integrative genomics is a powerful tool for linking newly researched organisms, such as tropical woody species, to functional studies already carried out on established model organisms. Based on gene orthology analyses and expression patterns, we searched the Citrus Genome Sequencing Consortium (CitEST database for Expressed Sequence Tags (EST consensus sequences sharing similarity to known components of hormone metabolism and signaling pathways in model species. More than 600 homologs of functionally characterized hormone metabolism and signal transduction members from model species were identified in citrus, allowing us to propose a framework for phytohormone signaling mechanisms in citrus. A number of components from hormone-related metabolic pathways were absent in citrus, suggesting the presence of distinct metabolic pathways. Our results demonstrated the power of comparative genomics between model systems and economically important crop species to elucidate several aspects of plant physiology and metabolism.

PathwayAccess: CellDesigner plugins for pathway databases.

Science.gov (United States)

Van Hemert, John L; Dickerson, Julie A

2010-09-15

CellDesigner provides a user-friendly interface for graphical biochemical pathway description. Many pathway databases are not directly exportable to CellDesigner models. PathwayAccess is an extensible suite of CellDesigner plugins, which connect CellDesigner directly to pathway databases using respective Java application programming interfaces. The process is streamlined for creating new PathwayAccess plugins for specific pathway databases. Three PathwayAccess plugins, MetNetAccess, BioCycAccess and ReactomeAccess, directly connect CellDesigner to the pathway databases MetNetDB, BioCyc and Reactome. PathwayAccess plugins enable CellDesigner users to expose pathway data to analytical CellDesigner functions, curate their pathway databases and visually integrate pathway data from different databases using standard Systems Biology Markup Language and Systems Biology Graphical Notation. Implemented in Java, PathwayAccess plugins run with CellDesigner version 4.0.1 and were tested on Ubuntu Linux, Windows XP and 7, and MacOSX. Source code, binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv.

Integrated GWAS and Pathway profiling for feed efficiency traits in pigs leads to novel genes and their molecular pathways

DEFF Research Database (Denmark)

Do, Duy Ngoc; Ostersen, Tage; Strathe, Anders Bjerring

2013-01-01

Genome wide association studies (GWAS) are being extensively used in revealing genetic architecture of complex traits. However, GWAS offer limited understanding of the biological role of significant single nucleotide polymorphisms (SNPs) affecting complex traits. Pathway analysis using GWAS results...... is an important step where we firstly detect genes located near GWAS-detected SNPs and subsequently we detect enrichment of these genes in various biological processes and pathways. The objective of this study was to apply these steps to identify relevant pathways involved in residual feed intake (RFI) in pigs....... Residual feed intake is a feed efficiency measure and is highly economically important in animal production. In our study, a total of 596 Yorkshire boars had phenotypic and genotypic records. After quality control, 37,915 SNPs were available for GWAS which was implemented in the DMU software package...

Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

Directory of Open Access Journals (Sweden)

Yingrong Chen

2015-01-01

Full Text Available Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that glycerophospho-N-arachidonoyl ethanolamine (GpAEA and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer.

Pathways and impacts of nitrogen in water bodies: establishing a framework for integrated assessment modelling of management benefits

DEFF Research Database (Denmark)

Andersen, Mikael Skou; Kronvang, Brian; Carstensen, Jacob

Monetization of environmental benefits has become relevant as an element of proportionality tests required for justifications under the EU’s Water Framework Directive article 4 (relating to benefits andcosts of measures). This study extends an impact pathway approach to analysis of aquatic...... the study demonstrates how state-of-the-art environmental modelling can be linked with valuation to provide an adequate cross-media assessment framework relevant to integrated water quality management. The results must be regarded as illustrative and more research is required in several areas to consolidate...... relationships relating to exposures. The findings nevertheless suggest the significance of health effects for overall monetary benefits related to ecological quality objectives for water....

Convergent and divergent pathways decoding hierarchical additive mechanisms in treating cerebral ischemia-reperfusion injury.

Science.gov (United States)

Zhang, Ying-Ying; Li, Hai-Xia; Chen, Yin-Ying; Fang, Hong; Yu, Ya-Nan; Liu, Jun; Jing, Zhi-Wei; Wang, Zhong; Wang, Yong-Yan

2014-03-01

Cerebral ischemia is considered to be a highly complex disease resulting from the complicated interplay of multiple pathways. Disappointedly, most of the previous studies were limited to a single gene or a single pathway. The extent to which all involved pathways are translated into fusing mechanisms of a combination therapy is of fundamental importance. We report an integrative strategy to reveal the additive mechanism that a combination (BJ) of compound baicalin (BA) and jasminoidin (JA) fights against cerebral ischemia based on variation of pathways and functional communities. We identified six pathways of BJ group that shared diverse additive index from 0.09 to 1, which assembled broad cross talks from seven pathways of BA and 16 pathways of JA both at horizontal and vertical levels. Besides a total of 60 overlapping functions as a robust integration background among the three groups based on significantly differential subnetworks, additive mechanism with strong confidence by networks altered functions. These results provide strong evidence that the additive mechanism is more complex than previously appreciated, and an integrative analysis of pathways may suggest an important paradigm for revealing pharmacological mechanisms underlying drug combinations. © 2013 John Wiley & Sons Ltd.

Integrative Analysis of Omics Big Data.

Science.gov (United States)

Yu, Xiang-Tian; Zeng, Tao

2018-01-01

The diversity and huge omics data take biology and biomedicine research and application into a big data era, just like that popular in human society a decade ago. They are opening a new challenge from horizontal data ensemble (e.g., the similar types of data collected from different labs or companies) to vertical data ensemble (e.g., the different types of data collected for a group of person with match information), which requires the integrative analysis in biology and biomedicine and also asks for emergent development of data integration to address the great changes from previous population-guided to newly individual-guided investigations.Data integration is an effective concept to solve the complex problem or understand the complicate system. Several benchmark studies have revealed the heterogeneity and trade-off that existed in the analysis of omics data. Integrative analysis can combine and investigate many datasets in a cost-effective reproducible way. Current integration approaches on biological data have two modes: one is "bottom-up integration" mode with follow-up manual integration, and the other one is "top-down integration" mode with follow-up in silico integration.This paper will firstly summarize the combinatory analysis approaches to give candidate protocol on biological experiment design for effectively integrative study on genomics and then survey the data fusion approaches to give helpful instruction on computational model development for biological significance detection, which have also provided newly data resources and analysis tools to support the precision medicine dependent on the big biomedical data. Finally, the problems and future directions are highlighted for integrative analysis of omics big data.

Chiropractic Integrated Care Pathway for Low Back Pain in Veterans: Results of a Delphi Consensus Process.

Science.gov (United States)

Lisi, Anthony J; Salsbury, Stacie A; Hawk, Cheryl; Vining, Robert D; Wallace, Robert B; Branson, Richard; Long, Cynthia R; Burgo-Black, A Lucille; Goertz, Christine M

2018-02-01

The purpose of this study was to develop an integrated care pathway for doctors of chiropractic, primary care providers, and mental health professionals who manage veterans with low back pain, with or without mental health comorbidity, within Department of Veterans Affairs health care facilities. The research method used was a consensus process. A multidisciplinary investigative team reviewed clinical guidelines and Veterans Affairs pain and mental health initiatives to develop seed statements and care algorithms to guide chiropractic management and collaborative care of veterans with low back pain. A 5-member advisory committee approved initial recommendations. Veterans Affairs-based panelists (n = 58) evaluated the pathway via e-mail using a modified RAND/UCLA methodology. Consensus was defined as agreement by 80% of panelists. The modified Delphi process was conducted in July to December 2016. Most (93%) seed statements achieved consensus during the first round, with all statements reaching consensus after 2 rounds. The final care pathway addressed the topics of informed consent, clinical evaluation including history and examination, screening for red flags, documentation, diagnostic imaging, patient-reported outcomes, adverse event reporting, chiropractic treatment frequency and duration standards, tailored approaches to chiropractic care in veteran populations, and clinical presentation of common mental health conditions. Care algorithms outlined chiropractic case management and interprofessional collaboration and referrals between doctors of chiropractic and primary care and mental health providers. This study offers an integrative care pathway that includes chiropractic care for veterans with low back pain. Copyright © 2018. Published by Elsevier Inc.

Integrated genetic analysis microsystems

International Nuclear Information System (INIS)

Lagally, Eric T; Mathies, Richard A

2004-01-01

With the completion of the Human Genome Project and the ongoing DNA sequencing of the genomes of other animals, bacteria, plants and others, a wealth of new information about the genetic composition of organisms has become available. However, as the demand for sequence information grows, so does the workload required both to generate this sequence and to use it for targeted genetic analysis. Microfabricated genetic analysis systems are well poised to assist in the collection and use of these data through increased analysis speed, lower analysis cost and higher parallelism leading to increased assay throughput. In addition, such integrated microsystems may point the way to targeted genetic experiments on single cells and in other areas that are otherwise very difficult. Concomitant with these advantages, such systems, when fully integrated, should be capable of forming portable systems for high-speed in situ analyses, enabling a new standard in disciplines such as clinical chemistry, forensics, biowarfare detection and epidemiology. This review will discuss the various technologies available for genetic analysis on the microscale, and efforts to integrate them to form fully functional robust analysis devices. (topical review)

Pathway Analysis of miR-181a in Hypopharyngeal Squamous Cell ...

African Journals Online (AJOL)

syakima

2012-03-15

Mar 15, 2012 ... Key words: MicroRNA, head and neck cancer, miR-181a, pathway analysis, luciferase assay, FaDu cell line, transfection ..... prostate carcinoma and glioblastoma cells. Nucleic Acids .... WNT pathway in oral cancer: epigenetic.

CRITICAL RADIONUCLIDE AND PATHWAY ANALYSIS FOR THE SAVANNAH RIVER SITE

Energy Technology Data Exchange (ETDEWEB)

Jannik, T.

2011-08-30

This report is an update to the analysis, Assessment of SRS Radiological Liquid and Airborne Contaminants and Pathways, that was performed in 1997. An electronic version of this large original report is included in the attached CD to this report. During the operational history (1954 to the present) of the Savannah River Site (SRS), many different radionuclides have been released to the environment from the various production facilities. However, as will be shown by this updated radiological critical contaminant/critical pathway analysis, only a small number of the released radionuclides have been significant contributors to potential doses and risks to offsite people. The analysis covers radiological releases to the atmosphere and to surface waters, the principal media that carry contaminants offsite. These releases potentially result in exposure to offsite people. The groundwater monitoring performed at the site shows that an estimated 5 to 10% of SRS has been contaminated by radionuclides, no evidence exists from the extensive monitoring performed that groundwater contaminated with these constituents has migrated off the site (SRS 2011). Therefore, with the notable exception of radiological source terms originating from shallow surface water migration into site streams, onsite groundwater was not considered as a potential exposure pathway to offsite people. In addition, in response to the Department of Energy's (DOE) Order 435.1, several Performance Assessments (WSRC 2008; LWO 2009; SRR 2010; SRR 2011) and a Comprehensive SRS Composite Analysis (SRNO 2010) have recently been completed at SRS. The critical radionuclides and pathways identified in these extensive reports are discussed and, where applicable, included in this analysis.

Energy pathway analysis - a hydrogen fuel cycle framework for system studies

International Nuclear Information System (INIS)

Badin, J.S.; Tagore, S.

1997-01-01

An analytical framework has been developed that can be used to estimate a range of life-cycle costs and impacts that result from the incremental production, storage, transport, and use of different fuels or energy carriers, such as hydrogen, electricity, natural gas, and gasoline. This information is used in a comparative analysis of energy pathways. The pathways provide the U.S. Department of Energy (DOE) with an indication of near-, mid-, and long-term technologies that have the greatest potential for advancement and can meet the cost goals. The methodology and conceptual issues are discussed. Also presented are results for selected pathways from the E3 (Energy, Economics, Emissions) Pathway Analysis Model. This model will be expanded to consider networks of pathways and to be compatible with a linear programming optimization processor. Scenarios and sets of constraints (energy demands, sources, emissions) will be defined so the effects on energy transformation activities included in the solution and on the total optimized system cost can be investigated. This evaluation will be used as a guide to eliminate technically feasible pathways if they are not cost effective or do not meet the threshold requirements for the market acceptance. (Author)

Metabolic reconstruction of Setaria italica: a systems biology approach for integrating tissue-specific omics and pathway analysis of bioenergy grasses

Directory of Open Access Journals (Sweden)

Cristiana Gomes De Oliveira Dal'molin

2016-08-01

Full Text Available The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica, as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S.italica. mRNA, protein and metabolite abundances, were measured in mature and immature stem/leaf phytomers and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME. Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study

Metabolic Reconstruction of Setaria italica: A Systems Biology Approach for Integrating Tissue-Specific Omics and Pathway Analysis of Bioenergy Grasses.

Science.gov (United States)

de Oliveira Dal'Molin, Cristiana G; Orellana, Camila; Gebbie, Leigh; Steen, Jennifer; Hodson, Mark P; Chrysanthopoulos, Panagiotis; Plan, Manuel R; McQualter, Richard; Palfreyman, Robin W; Nielsen, Lars K

2016-01-01

The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica), as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S. italica. mRNA, protein, and metabolite abundances, were measured in mature and immature stem/leaf phytomers, and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME). Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin, and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study, we demonstrated

PathNet: a tool for pathway analysis using topological information

Directory of Open Access Journals (Sweden)

Dutta Bhaskar

2012-09-01

Full Text Available Abstract Background Identification of canonical pathways through enrichment of differentially expressed genes in a given pathway is a widely used method for interpreting gene lists generated from high-throughput experimental studies. However, most algorithms treat pathways as sets of genes, disregarding any inter- and intra-pathway connectivity information, and do not provide insights beyond identifying lists of pathways. Results We developed an algorithm (PathNet that utilizes the connectivity information in canonical pathway descriptions to help identify study-relevant pathways and characterize non-obvious dependencies and connections among pathways using gene expression data. PathNet considers both the differential expression of genes and their pathway neighbors to strengthen the evidence that a pathway is implicated in the biological conditions characterizing the experiment. As an adjunct to this analysis, PathNet uses the connectivity of the differentially expressed genes among all pathways to score pathway contextual associations and statistically identify biological relations among pathways. In this study, we used PathNet to identify biologically relevant results in two Alzheimer’s disease microarray datasets, and compared its performance with existing methods. Importantly, PathNet identified de-regulation of the ubiquitin-mediated proteolysis pathway as an important component in Alzheimer’s disease progression, despite the absence of this pathway in the standard enrichment analyses. Conclusions PathNet is a novel method for identifying enrichment and association between canonical pathways in the context of gene expression data. It takes into account topological information present in pathways to reveal biological information. PathNet is available as an R workspace image from http://www.bhsai.org/downloads/pathnet/.

Integrated QSAR study for inhibitors of Hedgehog Signal Pathway against multiple cell lines:a collaborative filtering method.

Science.gov (United States)

Gao, Jun; Che, Dongsheng; Zheng, Vincent W; Zhu, Ruixin; Liu, Qi

2012-07-31

The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

Science.gov (United States)

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To

Integrating nitric oxide into salicylic acid and jasmonic acid/ ethylene plant defense pathways.

Science.gov (United States)

Mur, Luis A J; Prats, Elena; Pierre, Sandra; Hall, Michael A; Hebelstrup, Kim H

2013-01-01

Plant defense against pests and pathogens is known to be conferred by either salicylic acid (SA) or jasmonic acid (JA)/ethylene (ET) pathways, depending on infection or herbivore-grazing strategy. It is well attested that SA and JA/ET pathways are mutually antagonistic allowing defense responses to be tailored to particular biotic stresses. Nitric oxide (NO) has emerged as a major signal influencing resistance mediated by both signaling pathways but no attempt has been made to integrate NO into established SA/JA/ET interactions. NO has been shown to act as an inducer or suppressor of signaling along each pathway. NO will initiate SA biosynthesis and nitrosylate key cysteines on TGA-class transcription factors to aid in the initiation of SA-dependent gene expression. Against this, S-nitrosylation of NONEXPRESSOR OF PATHOGENESIS-RELATED PROTEINS1 (NPR1) will promote the NPR1 oligomerization within the cytoplasm to reduce TGA activation. In JA biosynthesis, NO will initiate the expression of JA biosynthetic enzymes, presumably to over-come any antagonistic effects of SA on JA-mediated transcription. NO will also initiate the expression of ET biosynthetic genes but a suppressive role is also observed in the S-nitrosylation and inhibition of S-adenosylmethionine transferases which provides methyl groups for ET production. Based on these data a model for NO action is proposed but we have also highlighted the need to understand when and how inductive and suppressive steps are used.

Pathway analysis of kidney cancer using proteomics and metabolic profiling

Directory of Open Access Journals (Sweden)

Fiehn Oliver

2006-11-01

Full Text Available Abstract Background Renal cell carcinoma (RCC is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. Approximately one-third of patients present with disease which is already metastatic and for which there is currently no adequate treatment, and no biofluid screening tests exist for RCC. In this study, we have undertaken a comprehensive proteomic analysis and subsequently a pathway and network approach to identify biological processes involved in clear cell RCC (ccRCC. We have used these data to investigate urinary markers of RCC which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease. Results Using 2-dimensional electrophoresis and mass spectrometric analysis, we identified 31 proteins which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non-malignant tissue, and we confirmed some of these by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. When evaluated by several pathway and biological process analysis programs, these proteins are demonstrated to be involved with a high degree of confidence (p values Conclusion Extensive pathway and network analysis allowed for the discovery of highly significant pathways from a set of clear cell RCC samples. Knowledge of activation of these processes will lead to novel assays identifying their proteomic and/or metabolomic signatures in biofluids of patient at high risk for this disease; we provide pilot data for such a urinary bioassay. Furthermore, we demonstrate how the knowledge of networks, processes, and pathways altered in kidney cancer may be used to influence the choice of optimal therapy.

Integration of Pathway Knowledge and Dynamic Bayesian Networks for the Prediction of Oral Cancer Recurrence.

Science.gov (United States)

Kourou, Konstantina; Papaloukas, Costas; Fotiadis, Dimitrios I

2017-03-01

Oral squamous cell carcinoma has been characterized as a complex disease which involves dynamic genomic changes at the molecular level. These changes indicate the worth to explore the interactions of the molecules and especially of differentially expressed genes that contribute to cancer progression. Moreover, based on this knowledge the identification of differentially expressed genes and related molecular pathways is of great importance. In the present study, we exploit differentially expressed genes in order to further perform pathway enrichment analysis. According to our results we found significant pathways in which the disease associated genes have been identified as strongly enriched. Furthermore, based on the results of the pathway enrichment analysis we propose a methodology for predicting oral cancer recurrence using dynamic Bayesian networks. The methodology takes into consideration time series gene expression data in order to predict a disease recurrence. Subsequently, we are able to conjecture about the causal interactions between genes in consecutive time intervals. Concerning the performance of the predictive models, the overall accuracy of the algorithm is 81.8% and the area under the ROC curve 89.2% regarding the knowledge from the overrepresented pre-NOTCH Expression and processing pathway.

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis.

Science.gov (United States)

Song, Zhenhua; Zhang, Chi; He, Lingxiao; Sui, Yanfang; Lin, Xiafei; Pan, Jingjing

2018-05-01

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes. Copyright © 2018 Elsevier Inc. All rights reserved.

Evidence-based educational pathway for the integration of first aid training in school curricula.

Science.gov (United States)

De Buck, Emmy; Van Remoortel, Hans; Dieltjens, Tessa; Verstraeten, Hans; Clarysse, Matthieu; Moens, Olaf; Vandekerckhove, Philippe

2015-09-01

"Calling for help, performing first aid and providing Cardiopulmonary Resuscitation (CPR)" is part of the educational goals in secondary schools in Belgium (Flanders). However, for teachers it is not always clear at what age children can be taught which aspects of first aid. In addition, it is not clear what constitutes "performing first aid" and we strongly advocate that the first aid curriculum is broader than CPR training alone. To develop an evidence-based educational pathway to enable the integration of first aid into the school curriculum by defining the goals to be achieved for knowledge, skills and attitudes, for different age groups. Studies were identified through electronic databases research (The Cochrane Library, MEDLINE, Embase). We included studies on first aid education for children and adolescents up to 18 years old. A multidisciplinary expert panel formulated their practice experience and expert opinion and discussed the available evidence. We identified 5822 references and finally retained 30 studies (13 experimental and 17 observational studies), including studies concerning emergency call (7 studies), cardiopulmonary resuscitation (18 studies), AED (Automated External Defibrillator) use (6 studies), recovery position (5 studies), choking (2 studies), injuries (5 studies), and poisoning (2 studies). Recommendations (educational goals) were derived after carefully discussing the currently available evidence in the literature and balancing the skills and attitudes of children of different ages. An evidence-based educational pathway with educational goals concerning learning first aid for each age group was developed. This educational pathway can be used for the integration of first aid training in school curricula. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Comparative study on gene set and pathway topology-based enrichment methods.

Science.gov (United States)

Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim

2015-10-22

Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

Science.gov (United States)

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Integrative miRNA and mRNA analysis in penile carcinomas reveals markers and pathways with potential clinical impact

DEFF Research Database (Denmark)

Kuasne, Hellen; Barros-Filho, Mateus Camargo; Busso-Lopes, Ariane F

2017-01-01

Penile carcinoma (PeCa) is an important public health issue in poor and developing countries, and has only recently been explored in terms of genetic and epigenetic studies. Integrative data analysis is a powerful method for the identification of molecular drivers involved in cancer development...

Pathway analysis concepts for radiological impact assessment

International Nuclear Information System (INIS)

Moroney, J.R.

1992-06-01

The concepts underlying exposure pathways analysis are outlined with reference to the features of the two broad types of radionuclide transport models now in use - dynamic and steady-state - and the methods for constructing and developing them. By way of illustration, representative radiation doses are estimated for the four main exposure pathways likely to be involved in the land application of effluent water from Retention Pond 2 of Ranger Uranium Mines. These include: external irradiation by 226 Ra and natural uranium (Un at) in soil, ingestion of 226 Ra and Un at in food, inhalation of 222 Rn daughter products from 226 Rn in soil, and inhalation of 226 Ra and Un at in airborne dust resuspended from soil. Consideration has been given to local residents pursuing a traditional lifestyle on conclusion of the land application program. Because of the possible importance of the contribution from resuspended dust, currently available data are explored in refining the methodology for the pathway and developing a more appropriate model for it. 37 refs., 9 tabs., 6 figs

Combined Transcriptomic Analysis Revealed AKR1B10 Played an Important Role in Psoriasis through the Dysregulated Lipid Pathway and Overproliferation of Keratinocyte

Directory of Open Access Journals (Sweden)

Yunlu Gao

2017-01-01

Full Text Available RNA-seq has enabled in-depth analysis of the pathogenesis of psoriasis on the transcriptomic level, and many biomarkers have been discovered to be related to the immune response, lipid metabolism, and keratinocyte proliferation. However, few studies have combined analysis from various datasets. In this study, we integrated different psoriasis RNA-seq datasets to reveal the pathogenesis of psoriasis through the analysis of differentially expressed genes (DEGs, pathway analysis, and functional annotation. The revealed biomarkers were further validated through proliferation phenotypes. The results showed that DEGs were functionally related to lipid metabolism and keratinocyte differentiation dysregulation. The results also showed new biomarkers, such as AKR1B10 and PLA2G gene families, as well as pathways that include the PPAR signaling pathway, cytokine-cytokine receptor interaction, alpha-linoleic acid metabolism, and glycosphingolipid biosynthesis. Using siRNA knockdown assays, we further validated the role that the AKR1B10 gene plays in proliferation. Our study demonstrated not only the dysfunction of the AKR1B10 gene in lipid metabolizing but also its important role in the overproliferation and migration of keratinocyte, which provided evidence for further therapeutic uses for psoriasis.

A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

Directory of Open Access Journals (Sweden)

Bai Chunyan

2009-09-01

Full Text Available Abstract Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies.

A case study to illustrate the utility of the Aggregate Exposure Pathway and Adverse Outcome Pathway frameworks for integrating human health and ecological data into cumulative risk assessment

Science.gov (United States)

Cumulative risk assessment (CRA) methods, which evaluate the risk of multiple adverse outcomes (AOs) from multiple chemicals, promote the use of a conceptual site model (CSM) to integrate risk from relevant stressors. The Adverse Outcome Pathway (AOP) framework can inform these r...

Proteomics-based network analysis characterizes biological processes and pathways activated by preconditioned mesenchymal stem cells in cardiac repair mechanisms.

Science.gov (United States)

Di Silvestre, Dario; Brambilla, Francesca; Scardoni, Giovanni; Brunetti, Pietro; Motta, Sara; Matteucci, Marco; Laudanna, Carlo; Recchia, Fabio A; Lionetti, Vincenzo; Mauri, Pierluigi

2017-05-01

We have demonstrated that intramyocardial delivery of human mesenchymal stem cells preconditioned with a hyaluronan mixed ester of butyric and retinoic acid (MSCp + ) is more effective in preventing the decay of regional myocardial contractility in a swine model of myocardial infarction (MI). However, the understanding of the role of MSCp + in proteomic remodeling of cardiac infarcted tissue is not complete. We therefore sought to perform a comprehensive analysis of the proteome of infarct remote (RZ) and border zone (BZ) of pigs treated with MSCp + or unconditioned stem cells. Heart tissues were analyzed by MudPIT and differentially expressed proteins were selected by a label-free approach based on spectral counting. Protein profiles were evaluated by using PPI networks and their topological analysis. The proteomic remodeling was largely prevented in MSCp + group. Extracellular proteins involved in fibrosis were down-regulated, while energetic pathways were globally up-regulated. Cardioprotectant pathways involved in the production of keto acid metabolites were also activated. Additionally, we found that new hub proteins support the cardioprotective phenotype characterizing the left ventricular BZ treated with MSCp + . In fact, the up-regulation of angiogenic proteins NCL and RAC1 can be explained by the increase of capillary density induced by MSCp + . Our results show that angiogenic pathways appear to be uniquely positioned to integrate signaling with energetic pathways involving cardiac repair. Our findings prompt the use of proteomics-based network analysis to optimize new approaches preventing the post-ischemic proteomic remodeling that may underlie the limited self-repair ability of adult heart. Copyright © 2017 Elsevier B.V. All rights reserved.

IT-supported integrated care pathways for diabetes: A compilation and review of good practices.

Science.gov (United States)

Vrijhoef, Hubertus Jm; de Belvis, Antonio Giulio; de la Calle, Matias; de Sabata, Maria Stella; Hauck, Bastian; Montante, Sabrina; Moritz, Annette; Pelizzola, Dario; Saraheimo, Markku; Guldemond, Nick A

2017-06-01

Integrated Care Pathways (ICPs) are a method for the mutual decision-making and organization of care for a well-defined group of patients during a well-defined period. The aim of a care pathway is to enhance the quality of care by improving patient outcomes, promoting patient safety, increasing patient satisfaction, and optimizing the use of resources. To describe this concept, different names are used, e.g. care pathways and integrated care pathways. Modern information technologies (IT) can support ICPs by enabling patient empowerment, better management, and the monitoring of care provided by multidisciplinary teams. This study analyses ICPs across Europe, identifying commonalities and success factors to establish good practices for IT-supported ICPs in diabetes care. A mixed-method approach was applied, combining desk research on 24 projects from the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) with follow-up interviews of project participants, and a non-systematic literature review. We applied a Delphi technique to select process and outcome indicators, derived from different literature sources which were compiled and applied for the identification of successful good practices. Desk research identified sixteen projects featuring IT-supported ICPs, mostly derived from the EIP on AHA, as good practices based on our criteria. Follow-up interviews were then conducted with representatives from 9 of the 16 projects to gather information not publicly available and understand how these projects were meeting the identified criteria. In parallel, the non-systematic literature review of 434 PubMed search results revealed a total of eight relevant projects. On the basis of the selected EIP on AHA project data and non-systematic literature review, no commonalities with regard to defined process or outcome indicators could be identified through our approach. Conversely, the research produced a heterogeneous picture in all aspects of the projects

Critical Radionuclide and Pathway Analysis for the Savannah River Site, 2016 Update

Energy Technology Data Exchange (ETDEWEB)

Jannik, Tim [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Hartman, Larry [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2016-09-08

During the operational history of Savannah River Site, many different radionuclides have been released from site facilities. However, as shown in this analysis, only a relatively small number of the released radionuclides have been significant contributors to doses to the offsite public. This report is an update to the 2011 analysis, Critical Radionuclide and Pathway Analysis for the Savannah River Site. SRS-based Performance Assessments for E-Area, Saltstone, F-Tank Farm, H-Tank Farm, and a Comprehensive SRS Composite Analysis have been completed. The critical radionuclides and pathways identified in those extensive reports are also detailed and included in this analysis.

Evaluation of additional biogeochemical impacts on mitigation pathways in an energy sytem integrated assessment model.

Science.gov (United States)

Dessens, O.

2017-12-01

Within the last IPCC AR5 a large and systematic sensitivity study around available technologies and timing of policies applied in IAMs to achieve the 2°C target has been conducted. However the simple climate representations included in IAMs are generally tuned to the results of ensemble means. This may result in hiding within the ensemble mean results possible challenging mitigation pathways for the economy or the technology future scenarios. This work provides new insights on the sensitivity of the socio-economic response to different climate factors under a 2°C climate change target in order to help guide future efforts to reduce uncertainty in the climate mitigation decisions. The main objective is to understand and bring new insights on how future global warming will affect the natural biochemical feedbacks on the climate system and what could be the consequences of these feedbacks on the anthropogenic emission pathways with a specific focus on the energy-economy system. It specifically focuses on three issues of the climate representation affecting the energy system transformation and GHG emissions pathways: 1- Impacts of the climate sensitivity (or TCR); 2- Impacts of warming on the radiative forcing (cloudiness,...); 3- Impacts of warming on the carbon cycle (carbon cycle feedback). We use the integrated assessment model TIAM-UCL to examine the mitigation pathways compatible with the 2C target depending on assumptions regarding the 3 issues of the climate representation introduced above. The following key conclusions drawn from this study are that mitigation to 2°C is still possible under strong climate sensitivity (TCR), strong carbon cycle amplification or positive radiative forcing feedback. However, this level of climate mitigation will require a significant transformation in the way we produce and consume energy. Carbon capture and sequestration on electricity generation, industry and biomass is part of the technology pool needed to achieve this

Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution.

Science.gov (United States)

Ou, Yang; Shi, Wenjing; Smith, Steven J; Ledna, Catherine M; West, J Jason; Nolte, Christopher G; Loughlin, Daniel H

2018-04-15

There are many technological pathways that can lead to reduced carbon dioxide emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the energy system to compare environmental impacts of alternative low-carbon pathways for the United States. One set of pathways emphasizes nuclear energy and carbon capture and storage, while another set emphasizes renewable energy, including wind, solar, geothermal power, and bioenergy. These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter smaller than 2.5 μm in diameter, and energy-related water demands are evaluated for 50% and 80% carbon dioxide reduction targets in 2050. The renewable low-carbon pathways require less water withdrawal and consumption than the nuclear and carbon capture pathways. However, the renewable low-carbon pathways modeled in this study produce higher particulate matter-related mortality costs due to greater use of biomass in residential heating. Environmental co-benefits differ among states because of factors such as existing technology stock, resource availability, and environmental and energy policies.

Integrated Transcriptomic and Epigenomic Analysis of Primary Human Lung Epithelial Cell Differentiation

Science.gov (United States)

Marconett, Crystal N.; Zhou, Beiyun; Rieger, Megan E.; Selamat, Suhaida A.; Dubourd, Mickael; Fang, Xiaohui; Lynch, Sean K.; Stueve, Theresa Ryan; Siegmund, Kimberly D.; Berman, Benjamin P.

2013-01-01

Elucidation of the epigenetic basis for cell-type specific gene regulation is key to gaining a full understanding of how the distinct phenotypes of differentiated cells are achieved and maintained. Here we examined how epigenetic changes are integrated with transcriptional activation to determine cell phenotype during differentiation. We performed epigenomic profiling in conjunction with transcriptomic profiling using in vitro differentiation of human primary alveolar epithelial cells (AEC). This model recapitulates an in vivo process in which AEC transition from one differentiated cell type to another during regeneration following lung injury. Interrogation of histone marks over time revealed enrichment of specific transcription factor binding motifs within regions of changing chromatin structure. Cross-referencing of these motifs with pathways showing transcriptional changes revealed known regulatory pathways of distal alveolar differentiation, such as the WNT and transforming growth factor beta (TGFB) pathways, and putative novel regulators of adult AEC differentiation including hepatocyte nuclear factor 4 alpha (HNF4A), and the retinoid X receptor (RXR) signaling pathways. Inhibition of the RXR pathway confirmed its functional relevance for alveolar differentiation. Our incorporation of epigenetic data allowed specific identification of transcription factors that are potential direct upstream regulators of the differentiation process, demonstrating the power of this approach. Integration of epigenomic data with transcriptomic profiling has broad application for the identification of regulatory pathways in other models of differentiation. PMID:23818859

A Pathway-Centered Analysis of Pig Domestication and Breeding in Eurasia

Directory of Open Access Journals (Sweden)

Jordi Leno-Colorado

2017-07-01

Full Text Available Ascertaining the molecular and physiological basis of domestication and breeding is an active area of research. Due to the current wide distribution of its wild ancestor, the wild boar, the pig (Sus scrofa is an excellent model to study these processes, which occurred independently in East Asia and Europe ca. 9000 yr ago. Analyzing genome variability patterns in terms of metabolic pathways is attractive since it considers the impact of interrelated functions of genes, in contrast to genome-wide scans that treat genes or genome windows in isolation. To that end, we studied 40 wild boars and 123 domestic pig genomes from Asia and Europe when metabolic pathway was the unit of analysis. We computed statistical significance for differentiation (Fst and linkage disequilibrium (nSL statistics at the pathway level. In terms of Fst, we found 21 and 12 pathways significantly differentiated at a q-value 10 significant pathways (in terms of Fst, comprising genes involved in the transduction of a large number of signals, like phospholipase PCLB1, which is expressed in the brain, or ITPR3, which has an important role in taste transduction. In terms of nSL, significant pathways were mainly related to reproductive performance (ovarian steroidogenesis, a similarly important target trait during domestication and modern animal breeding. Different levels of recombination cannot explain these results, since we found no correlation between Fst and recombination rate. However, we did find an increased ratio of deleterious mutations in domestic vs. wild populations, suggesting a relaxed functional constraint associated with the domestication and breeding processes. Purifying selection was, nevertheless, stronger in significantly differentiated pathways than in random pathways, mainly in Europe. We conclude that pathway analysis facilitates the biological interpretation of genome-wide studies. Notably, in the case of pig, behavior played an important role, among other

A Pathway-Centered Analysis of Pig Domestication and Breeding in Eurasia.

Science.gov (United States)

Leno-Colorado, Jordi; Hudson, Nick J; Reverter, Antonio; Pérez-Enciso, Miguel

2017-07-05

Ascertaining the molecular and physiological basis of domestication and breeding is an active area of research. Due to the current wide distribution of its wild ancestor, the wild boar, the pig ( Sus scrofa ) is an excellent model to study these processes, which occurred independently in East Asia and Europe ca. 9000 yr ago. Analyzing genome variability patterns in terms of metabolic pathways is attractive since it considers the impact of interrelated functions of genes, in contrast to genome-wide scans that treat genes or genome windows in isolation. To that end, we studied 40 wild boars and 123 domestic pig genomes from Asia and Europe when metabolic pathway was the unit of analysis. We computed statistical significance for differentiation (Fst) and linkage disequilibrium (nSL) statistics at the pathway level. In terms of Fst, we found 21 and 12 pathways significantly differentiated at a q -value 10 significant pathways (in terms of Fst), comprising genes involved in the transduction of a large number of signals, like phospholipase PCLB1, which is expressed in the brain, or ITPR3, which has an important role in taste transduction. In terms of nSL, significant pathways were mainly related to reproductive performance (ovarian steroidogenesis), a similarly important target trait during domestication and modern animal breeding. Different levels of recombination cannot explain these results, since we found no correlation between Fst and recombination rate. However, we did find an increased ratio of deleterious mutations in domestic vs. wild populations, suggesting a relaxed functional constraint associated with the domestication and breeding processes. Purifying selection was, nevertheless, stronger in significantly differentiated pathways than in random pathways, mainly in Europe. We conclude that pathway analysis facilitates the biological interpretation of genome-wide studies. Notably, in the case of pig, behavior played an important role, among other physiological

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma.

Science.gov (United States)

Li, Chaoxing; Liu, Li; Dinu, Valentin

2018-01-01

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes

Endocrine-disrupting Chemicals: Review of Toxicological Mechanisms Using Molecular Pathway Analysis

Science.gov (United States)

Yang, Oneyeol; Kim, Hye Lim; Weon, Jong-Il; Seo, Young Rok

2015-01-01

Endocrine disruptors are known to cause harmful effects to human through various exposure routes. These chemicals mainly appear to interfere with the endocrine or hormone systems. As importantly, numerous studies have demonstrated that the accumulation of endocrine disruptors can induce fatal disorders including obesity and cancer. Using diverse biological tools, the potential molecular mechanisms related with these diseases by exposure of endocrine disruptors. Recently, pathway analysis, a bioinformatics tool, is being widely used to predict the potential mechanism or biological network of certain chemicals. In this review, we initially summarize the major molecular mechanisms involved in the induction of the above mentioned diseases by endocrine disruptors. Additionally, we provide the potential markers and signaling mechanisms discovered via pathway analysis under exposure to representative endocrine disruptors, bisphenol, diethylhexylphthalate, and nonylphenol. The review emphasizes the importance of pathway analysis using bioinformatics to finding the specific mechanisms of toxic chemicals, including endocrine disruptors. PMID:25853100

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

Science.gov (United States)

McGuire, Mary F; Sriram Iyengar, M; Mercer, David W

2012-04-01

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction

Life Cycle Greenhouse Gas Analysis of Multiple Vehicle Fuel Pathways in China

Directory of Open Access Journals (Sweden)

Tianduo Peng

2017-11-01

Full Text Available The Tsinghua University Life Cycle Analysis Model (TLCAM is applied to calculate the life cycle fossil energy consumption and greenhouse gas (GHG emissions for more than 20 vehicle fuel pathways in China. In addition to conventional gasoline and diesel, these include coal- and gas-based vehicle fuels, and electric vehicle (EV pathways. The results indicate the following. (1 China’s current dependence on coal and relative low-efficiency processes limits the potential for most alternative fuel pathways to decrease energy consumption and emissions; (2 Future low-carbon electricity pathways offer more obvious advantages, with coal-based pathways needing to adopt carbon dioxide capture and storage technology to compete; (3 A well-to-wheels analysis of the fossil energy consumption of vehicles fueled by compressed natural gas and liquefied natural gas (LNG showed that they are comparable to conventional gasoline vehicles. However, importing rather than domestically producing LNG for vehicle use can decrease domestic GHG emissions by 35% and 31% compared with those of conventional gasoline and diesel vehicles, respectively; (4 The manufacturing and recovery of battery and vehicle in the EV analysis has significant impact on the overall ability of EVs to decrease fossil energy consumption and GHG emissions from ICEVs.

Analysis of Geothermal Pathway in the Metamorphic Area, Northeastern Taiwan

Science.gov (United States)

Wang, C.; Wu, M. Y.; Song, S. R.; Lo, W.

2016-12-01

A quantitative measure by play fairway analysis in geothermal energy development is an important tool that can present the probability map of potential resources through the uncertainty studies in geology for early phase decision making purpose in the related industries. While source, pathway, and fluid are the three main geologic factors in traditional geothermal systems, identifying the heat paths is critical to reduce drilling cost. Taiwan is in East Asia and the western edge of Pacific Ocean, locating on the convergent boundary of Eurasian Plate and Philippine Sea Plate with many earthquake activities. This study chooses a metamorphic area in the western corner of Yi-Lan plain in northeastern Taiwan with high geothermal potential and several existing exploration sites. Having high subsurface temperature gradient from the mountain belts, and plenty hydrologic systems through thousands of millimeters annual precipitation that would bring up heats closer to the surface, current geothermal conceptual model indicates the importance of pathway distribution which affects the possible concentration of extractable heat location. The study conducts surface lineation analysis using analytic hierarchy process to determine weights among various fracture types for their roles in geothermal pathways, based on the information of remote sensing data, published geologic maps and field work measurements, to produce regional fracture distribution probability map. The results display how the spatial distribution of pathways through various fractures could affect geothermal systems, identify the geothermal plays using statistical data analysis, and compare against the existing drilling data.

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

Science.gov (United States)

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

Directory of Open Access Journals (Sweden)

Kazuhide Watanabe

Full Text Available Deregulation of canonical Wnt/CTNNB1 (beta-catenin pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells.We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis.Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Pathway Distiller - multisource biological pathway consolidation.

Science.gov (United States)

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow

Proteomic Assessment of Biochemical Pathways That Are Critical to Nickel-Induced Toxicity Responses in Human Epithelial Cells

Science.gov (United States)

Ge, Yue; Bruno, Maribel; Haykal-Coates, Najwa; Wallace, Kathleen; Andrews, Debora; Swank, Adam; Winnik, Witold; Ross, Jeffrey A.

2016-01-01

Understanding the mechanisms underlying toxicity initiated by nickel, a ubiquitous environmental contaminant and known human carcinogen is necessary for proper assessment of its risks to human and environment. Among a variety of toxic mechanisms, disruption of protein responses and protein response-based biochemical pathways represents a key mechanism through which nickel induces cytotoxicity and carcinogenesis. To identify protein responses and biochemical pathways that are critical to nickel-induced toxicity responses, we measured cytotoxicity and changes in expression and phosphorylation status of 14 critical biochemical pathway regulators in human BEAS-2B cells exposed to four concentrations of nickel using an integrated proteomic approach. A subset of the pathway regulators, including interleukin-6, and JNK, were found to be linearly correlated with cell viability, and may function as molecular determinants of cytotoxic responses of BEAS-2B cells to nickel exposures. In addition, 128 differentially expressed proteins were identified by two dimensional electrophoresis (2-DE) and mass spectrometry. Principal component analysis, hierarchical cluster analyses, and ingenuity signaling pathway analysis (IPA) identified putative nickel toxicity pathways. Some of the proteins and pathways identified have not previously been linked to nickel toxicity. Based on the consistent results obtained from both ELISA and 2-DE proteomic analysis, we propose a core signaling pathway regulating cytotoxic responses of human BEAS-2B cells to nickel exposures, which integrates a small set of proteins involved in glycolysis and gluconeogenesis pathways, apoptosis, protein degradation, and stress responses including inflammation and oxidative stress. PMID:27626938

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

Science.gov (United States)

Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

2016-01-12

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of

Diagnostic pathway of integrated SPECT/CT for coronary artery disease

International Nuclear Information System (INIS)

Slart, Riemer H.J.A.; Tio, Rene A.; Zijlstra, Felix; Dierckx, Rudi A.

2009-01-01

. The development of SPECT/CT hybrid systems is therefore of important value for the nuclear cardiology armamentarium. This editorial commentary outlines a diagnostic pathway of integrated SPECT/CT for CAD assessment in symptomatic patients at intermediate risk for CAD. (orig.)

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

Science.gov (United States)

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

The School-Community Integrated Learning Pathway: Exploring a New Way to Prepare and Induct Final-Year Preservice Teachers

Science.gov (United States)

Hudson, Suzanne; Hudson, Peter; Adie, Lenore

2015-01-01

Universities and teacher employment bodies seek new, cost-effective ways for graduating classroom-ready teachers. This study involved 32 final-year preservice teachers in an innovative school--university partnership teacher education programme titled, the School-Community Integrated Learning (SCIL) pathway. Data were collected using a five-part…

Environmental-pathways analysis for evaluation of a low-level waste disposal site

International Nuclear Information System (INIS)

Lee, D.W.; Ketelle, R.H.; Pin, F.G.; Hill, G.S.

1983-01-01

The suitability of a site for the shallow land burial of low-level waste is evaluated by an environmental-pathways analysis. The environmental-pathways analysis considers the probable paths for the transport of contamination to man and models the long-term transport of contamination to determine the resulting dose-to-man. The model of the long-term transport of contamination is developed for a proposed site using data obtained from a comprehensive laboratory and field investigation. The proposed site is located at the US Department of Energy Portsmouth Reservation, Piketon, Ohio and is planned to accept low-level radioactive waste generated by the enrichment of uranium. Laboratory studies were performed to characterize the waste and determine the wastes' leaching and retardation characteristics with site soils and groundwater. Comprehensive drilling, sampling and laboratory investigations were performed to provide the necessary information for interpreting the site's geology and hydrology. Field tests were performed to further quantify the site's hydrology. The pathway of greatest concern is the migration of contaminated groundwater and subsequent consumption by man. This pathway was modeled using a numerical simulation of the long-term transport of contamination. Conservative scenarios were developed for leachate generation and migration through the geohydrologic system. The dose-to-man determined from the pathways analysis formed the basis for evaluating site acceptability and providing recommendations for site design and development

Environmental pathways analysis for evaluation of a low-level waste disposal site

International Nuclear Information System (INIS)

Lee, D.W.; Ketelle, R.H.; Pin, F.G.; Hill, G.S.

1984-01-01

The suitability of a site for the shallow land burial of low-level waste is evaluated by an environmental pathways analysis. The environmental pathways analysis considers the probable paths for the transport of contamination to man and models the long-term transport of contamination to determine the resulting dose to man. The model of the long-term transport of contamination is developed for a proposed site using data obtained from a comprehensive laboratory and field investigation. The proposed site is located at the US Department of Energy Portsmouth Reservation, Piketon, Ohio, and is planned to accept low-level radioactive waste generated by the enrichment of uranium. Laboratory studies were performed to characterize the waste and determine the wastes' leaching and retardation characteristics with site soils and groundwater. Comprehensive drilling, sampling and laboratory investigations were performed to provide the necessary information for interpreting the site's geology and hydrology. Field tests were performed to further quantify the site's hydrology. The pathway of greatest concern is the migration of contaminated groundwater and subsequent consumption by man. This pathway was modelled using a numerical simulation of the long-term transport of contamination. Conservative scenarios were developed for leachate generation and migration through the geohydrologic system. The dose to man determined from the pathways analysis formed the basis for evaluating site acceptability and providing recommendations for site design and development. (author)

Integrative genomic analysis identifies isoleucine and CodY as regulators of Listeria monocytogenes virulence.

Directory of Open Access Journals (Sweden)

Lior Lobel

2012-09-01

Full Text Available Intracellular bacterial pathogens are metabolically adapted to grow within mammalian cells. While these adaptations are fundamental to the ability to cause disease, we know little about the relationship between the pathogen's metabolism and virulence. Here we used an integrative Metabolic Analysis Tool that combines transcriptome data with genome-scale metabolic models to define the metabolic requirements of Listeria monocytogenes during infection. Twelve metabolic pathways were identified as differentially active during L. monocytogenes growth in macrophage cells. Intracellular replication requires de novo synthesis of histidine, arginine, purine, and branch chain amino acids (BCAAs, as well as catabolism of L-rhamnose and glycerol. The importance of each metabolic pathway during infection was confirmed by generation of gene knockout mutants in the respective pathways. Next, we investigated the association of these metabolic requirements in the regulation of L. monocytogenes virulence. Here we show that limiting BCAA concentrations, primarily isoleucine, results in robust induction of the master virulence activator gene, prfA, and the PrfA-regulated genes. This response was specific and required the nutrient responsive regulator CodY, which is known to bind isoleucine. Further analysis demonstrated that CodY is involved in prfA regulation, playing a role in prfA activation under limiting conditions of BCAAs. This study evidences an additional regulatory mechanism underlying L. monocytogenes virulence, placing CodY at the crossroads of metabolism and virulence.

Pathways of topological rank analysis (PoTRA: a novel method to detect pathways involved in hepatocellular carcinoma

Directory of Open Access Journals (Sweden)

Chaoxing Li

2018-04-01

Full Text Available Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several

A techno-economic analysis of EU renewable electricity policy pathways in 2030

International Nuclear Information System (INIS)

Río, Pablo del; Resch, Gustav; Ortner, Andre; Liebmann, Lukas; Busch, Sebastian; Panzer, Christian

2017-01-01

The aim of this paper is to assess several pathways of a harmonised European policy framework for supporting renewable electricity (RES-E) in a 2030 horizon according to different criteria. The pathways combine two main dimensions: degrees of harmonisation and instruments and design elements. A quantitative model-based analysis with the Green-X model is provided. The results of the simulations show that there are small differences between the evaluated cases regarding effectiveness. All the policy pathways score similarly with respect to RES-E deployment, i.e., with different degrees of harmonisation and whether using a feed-in tariff, a feed-in premium, a quota system with banding or a quota without banding scheme. In contrast, the policy costs clearly differ across the pathways, but the differences can mostly be attributed to the instruments rather than to the degrees of harmonisation. This is also the case with other criteria (static and dynamic efficiency and the socioeconomic and environmental benefits in terms of CO2 emissions and fossil fuels avoided). Both the degree of harmonisation and the choice of instrument influence the distribution of support costs across countries. Finally, our findings suggest that keeping strengthened national support leads to similar results to other policy pathways. - Highlights: • Pathways of a harmonised European policy framework for renewable electricity in 2030. • Two main dimensions: degrees of harmonisation and instruments. • A quantitative model-based analysis based on the Green-X model. • Small differences between the pathways regarding the effectiveness criterion. • Important differences between pathways regarding other assessment criteria.

Functions of the Drosophila JAK-STAT pathway

Science.gov (United States)

Amoyel, Marc; Bach, Erika A.

2012-01-01

JAK-STAT signaling has been proposed to act in numerous stem cells in a variety of organisms. Here we provide an overview of its roles in three well characterized stem cell populations in Drosophila, in the intestine, lymph gland and testis. In flies, there is a single JAK and a single STAT, which has made the genetic dissection of pathway function considerably easier and facilitated the analysis of communication between stem cells, their niches and offspring. Studies in flies have revealed roles for this pathway as diverse as regulating bona fide intrinsic self-renewal, integrating response to environmental cues that control quiescence and promoting mitogenic responses to stress. PMID:24058767

Importance of Mediator complex in the regulation and integration of diverse signaling pathways in plants

Directory of Open Access Journals (Sweden)

Subhasis eSamanta

2015-09-01

Full Text Available Basic transcriptional machinery in eukaryotes is assisted by a number of cofactors, which either increase or decrease the rate of transcription. Mediator complex is one such cofactor, and recently has drawn a lot of interest because of its integrative power to converge different signaling pathways before channelling the transcription instructions to the RNA polymerase II machinery. Like yeast and metazoans, plants do possess the Mediator complex across the kingdom, and its isolation and subunit analyses have been reported from the model plant, Arabidopsis. Genetic and molecular analyses have unravelled important regulatory roles of Mediator subunits at every stage of plant life cycle starting from flowering to embryo and organ development, to even size determination. It also contributes immensely to the survival of plants against different environmental vagaries by the timely activation of its resistance mechanisms. Here, we have provided an overview of plant Mediator complex starting from its discovery to regulation of stoichiometry of its subunits. We have also reviewed involvement of different Mediator subunits in different processes and pathways including defense response pathways evoked by diverse biotic cues. Wherever possible, attempts have been made to provide mechanistic insight of Mediator’s involvement in these processes.

Importance of Mediator complex in the regulation and integration of diverse signaling pathways in plants.

Science.gov (United States)

Samanta, Subhasis; Thakur, Jitendra K

2015-01-01

Basic transcriptional machinery in eukaryotes is assisted by a number of cofactors, which either increase or decrease the rate of transcription. Mediator complex is one such cofactor, and recently has drawn a lot of interest because of its integrative power to converge different signaling pathways before channeling the transcription instructions to the RNA polymerase II machinery. Like yeast and metazoans, plants do possess the Mediator complex across the kingdom, and its isolation and subunit analyses have been reported from the model plant, Arabidopsis. Genetic, and molecular analyses have unraveled important regulatory roles of Mediator subunits at every stage of plant life cycle starting from flowering to embryo and organ development, to even size determination. It also contributes immensely to the survival of plants against different environmental vagaries by the timely activation of its resistance mechanisms. Here, we have provided an overview of plant Mediator complex starting from its discovery to regulation of stoichiometry of its subunits. We have also reviewed involvement of different Mediator subunits in different processes and pathways including defense response pathways evoked by diverse biotic cues. Wherever possible, attempts have been made to provide mechanistic insight of Mediator's involvement in these processes.

Problems in mathematical analysis III integration

CERN Document Server

Kaczor, W J

2003-01-01

We learn by doing. We learn mathematics by doing problems. This is the third volume of Problems in Mathematical Analysis. The topic here is integration for real functions of one real variable. The first chapter is devoted to the Riemann and the Riemann-Stieltjes integrals. Chapter 2 deals with Lebesgue measure and integration. The authors include some famous, and some not so famous, integral inequalities related to Riemann integration. Many of the problems for Lebesgue integration concern convergence theorems and the interchange of limits and integrals. The book closes with a section on Fourier series, with a concentration on Fourier coefficients of functions from particular classes and on basic theorems for convergence of Fourier series. The book is primarily geared toward students in analysis, as a study aid, for problem-solving seminars, or for tutorials. It is also an excellent resource for instructors who wish to incorporate problems into their lectures. Solutions for the problems are provided in the boo...

Integrated analysis of transportation demand pathway options for hydrogen production, storage, and distribution

Energy Technology Data Exchange (ETDEWEB)

Thomas, C.E.S. [Directed Technologies Inc., Arlington, VA (United States)

1996-10-01

Directed Technologies, Inc. has begun the development of a computer model with the goal of providing guidance to the Hydrogen Program Office regarding the most cost effective use of limited resources to meet national energy security and environmental goals through the use of hydrogen as a major energy carrier. The underlying assumption of this programmatic pathway model is that government and industry must work together to bring clean hydrogen energy devices into the marketplace. Industry cannot provide the long term resources necessary to overcome technological, regulatory, institutional, and perceptual barriers to the use of hydrogen as an energy carrier, and government cannot provide the substantial investments required to develop hydrogen energy products and increased hydrogen production capacity. The computer model recognizes this necessary government/industry partnership by determining the early investments required by government to bring hydrogen energy end uses within the time horizon and profitability criteria of industry, and by estimating the subsequent investments required by industry. The model then predicts the cost/benefit ratio for government, based on contributions of each hydrogen project to meeting societal goals, and it predicts the return on investment for industry. Sensitivity analyses with respect to various government investments such as hydrogen research and development and demonstration projects will then provide guidance as to the most cost effective mix of government actions. The initial model considers the hydrogen transportation market, but this programmatic pathway methodology will be extended to other market segments in the future.

Identification of pathogenic genes related to rheumatoid arthritis through integrated analysis of DNA methylation and gene expression profiling.

Science.gov (United States)

Zhang, Lei; Ma, Shiyun; Wang, Huailiang; Su, Hang; Su, Ke; Li, Longjie

2017-11-15

The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA. Copyright © 2017. Published by Elsevier B.V.

Integrated analysis of the molecular action of Vorinostat identifies epi-sensitised targets for combination therapy.

Science.gov (United States)

Hay, Jodie F; Lappin, Katrina; Liberante, Fabio; Kettyle, Laura M; Matchett, Kyle B; Thompson, Alexander; Mills, Ken I

2017-09-15

Several histone deacetylase inhibitors including Vorinostat have received FDA approval for the treatment of haematological malignancies. However, data from these trials indicate that Vorinostat has limited efficacy as a monotherapy, prompting the need for rational design of combination therapies. A number of epi-sensitised pathways, including sonic hedgehog (SHH), were identified in AML cells by integration of global patterns of histone H3 lysine 9 (H3K9) acetylation with transcriptomic analysis following Vorinostat-treatment. Direct targeting of the SHH pathway with SANT-1, following Vorinostat induced epi-sensitisation, resulted in synergistic cell death of AML cells. In addition, xenograft studies demonstrated that combination therapy induced a marked reduction in leukemic burden compared to control or single agents. Together, the data supports epi-sensitisation as a potential component of the strategy for the rational development of combination therapies in AML.

An integrated approach for a dynamic energy and environmental system analysis of biogas production pathways

NARCIS (Netherlands)

Pierie, Frank; Liu, Wen; Moll, Henri C.

2014-01-01

Abstract written to Biogas Science for oral presentation. Regarding a new methodology for determining the energy efficiency, carbon footprint and environmental impact of anaerobic biogas production pathways. Additionally, results are given regarding the impacts of energy crops and waste products

A novel approach to select differential pathways associated with hypertrophic cardiomyopathy based on gene co‑expression analysis.

Science.gov (United States)

Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min

2017-07-01

The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.

Chapter 7. Cloning and analysis of natural product pathways.

Science.gov (United States)

Gust, Bertolt

2009-01-01

The identification of gene clusters of natural products has lead to an enormous wealth of information about their biosynthesis and its regulation, and about self-resistance mechanisms. Well-established routine techniques are now available for the cloning and sequencing of gene clusters. The subsequent functional analysis of the complex biosynthetic machinery requires efficient genetic tools for manipulation. Until recently, techniques for the introduction of defined changes into Streptomyces chromosomes were very time-consuming. In particular, manipulation of large DNA fragments has been challenging due to the absence of suitable restriction sites for restriction- and ligation-based techniques. The homologous recombination approach called recombineering (referred to as Red/ET-mediated recombination in this chapter) has greatly facilitated targeted genetic modifications of complex biosynthetic pathways from actinomycetes by eliminating many of the time-consuming and labor-intensive steps. This chapter describes techniques for the cloning and identification of biosynthetic gene clusters, for the generation of gene replacements within such clusters, for the construction of integrative library clones and their expression in heterologous hosts, and for the assembly of entire biosynthetic gene clusters from the inserts of individual library clones. A systematic approach toward insertional mutation of a complete Streptomyces genome is shown by the use of an in vitro transposon mutagenesis procedure.

A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer

Directory of Open Access Journals (Sweden)

Mary Qu Yang

Full Text Available Clear cell renal cell carcinoma (ccRCC is the most common and most aggressive form of renal cell cancer (RCC. The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1, as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways. Keywords: ccRCC, Causative mutation, Pathways, Protein-protein interaction, Gene module, eQTL

Energy Systems Integration: A Convergence of Ideas

Energy Technology Data Exchange (ETDEWEB)

Kroposki, B.; Garrett, B.; MacMillan, S.; Rice, B.; Komomua, C.; O' Malley, M.; Zimmerle, D.

2012-07-01

Energy systems integration (ESI) enables the effective analysis, design, and control of these interactions and interdependencies along technical, economic, regulatory, and social dimensions. By focusing on the optimization of energy from all systems, across all pathways, and at all scales, we can better understand and make use of the co-benefits that result to increase reliability and performance, reduce cost, and minimize environmental impacts. This white paper discusses systems integration and the research in new control architectures that are optimized at smaller scales but can be aggregated to optimize energy systems at any scale and would allow replicable energy solutions across boundaries of existing and new energy pathways.

Metabolic-flux analysis of hydrogen production pathway in Citrobacter amalonaticus Y19

Energy Technology Data Exchange (ETDEWEB)

Oh, You-Kwan; Kim, Mi-Sun [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-343 (Korea); Kim, Heung-Joo; Park, Sunghoon [Department of Chemical and Biochemical Engineering and Institute for Environmental Technology and Industry, Pusan National University, Busan 609-735 (Korea); Ryu, Dewey D.Y. [Biochemical Engineering Program, Department of Chemical Engineering and Material Science, University of California, Davis, CA 95616 (United States)

2008-03-15

For the newly isolated chemoheterotrophic bacterium Citrobacter amalonaticus Y19, anaerobic glucose metabolism and hydrogen (H{sub 2}) production pathway were studied using batch cultivation and an in silico metabolic-flux analysis. Batch cultivation was conducted under varying initial glucose concentration between 1.5 and 9.5 g/L with quantitative measurement of major metabolites to obtain accurate carbon material balance. The metabolic flux of Y19 was analyzed using a metabolic-pathway model which was constructed from 81 biochemical reactions. The linear optimization program MetaFluxNet was employed for the analysis. When the specific growth rate of cells was chosen as an objective function, the model described the batch culture characteristics of Ci. amalonaticus Y19 reasonably well. When the specific H{sub 2} production rate was selected as an objective function, on the other hand, the achievable maximal H{sub 2} production yield (8.7molH{sub 2}/mol glucose) and the metabolic pathway enabling the high H{sub 2} yield were identified. The pathway involved non-native NAD(P)-linked hydrogenase and H{sub 2} production from NAD(P)H which were supplied at a high rate from glucose degradation through the pentose phosphate pathway. (author)

Pathway-based Analysis of the Hidden Genetic Heterogeneities in Cancers

Directory of Open Access Journals (Sweden)

Xiaolei Zhao

2014-02-01

Full Text Available Many cancers apparently showing similar phenotypes are actually distinct at the molecular level, leading to very different responses to the same treatment. It has been recently demonstrated that pathway-based approaches are robust and reliable for genetic analysis of cancers. Nevertheless, it remains unclear whether such function-based approaches are useful in deciphering molecular heterogeneities in cancers. Therefore, we aimed to test this possibility in the present study. First, we used a NCI60 dataset to validate the ability of pathways to correctly partition samples. Next, we applied the proposed method to identify the hidden subtypes in diffuse large B-cell lymphoma (DLBCL. Finally, the clinical significance of the identified subtypes was verified using survival analysis. For the NCI60 dataset, we achieved highly accurate partitions that best fit the clinical cancer phenotypes. Subsequently, for a DLBCL dataset, we identified three hidden subtypes that showed very different 10-year overall survival rates (90%, 46% and 20% and were highly significantly (P = 0.008 correlated with the clinical survival rate. This study demonstrated that the pathway-based approach is promising for unveiling genetic heterogeneities in complex human diseases.

Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution

Energy Technology Data Exchange (ETDEWEB)

Ou, Yang; Shi, Wenjing; Smith, Steven J.; Ledna, Catherine M.; West, J. Jason; Nolte, Christopher G.; Loughlin, Daniel H.

2018-04-01

There are many technological pathways that can lead to reduced carbon dioxide (CO₂) emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the U.S. energy system to compare environmental impacts of alternative low-carbon pathways. One set of pathways emphasizes nuclear energy and carbon capture and storage (NUC/CCS), while another set emphasizes renewable energy (RE). These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter less than 2.5 microns in diameter (PM2.5), and energy-related water demands are evaluated for 50% and 80% CO₂ reduction targets in the U.S. in 2050. The RE low-carbon pathways require less water withdrawal and consumption than the NUC/CCS pathways because of the large cooling demands of nuclear power and CCS. However, the NUC/CCS low-carbon pathways produce greater health benefits, mainly because the NUC/CCS assumptions result in less primary PM2.5 emissions from residential wood combustion. Environmental co-benefits differ among states because of factors such as existing technology stock, resource availability, and environmental and energy policies. An important finding is that biomass in the building sector can offset some of the health co-benefits of the low-carbon pathways even though it plays only a minor role in reducing CO₂ emissions.

Integrated Radiation Analysis and Design Tools

Data.gov (United States)

National Aeronautics and Space Administration — The Integrated Radiation Analysis and Design Tools (IRADT) Project develops and maintains an integrated tool set that collects the current best practices, databases,...

The Vehicle Integrated Performance Analysis Experience: Reconnecting With Technical Integration

Science.gov (United States)

McGhee, D. S.

2006-01-01

Very early in the Space Launch Initiative program, a small team of engineers at MSFC proposed a process for performing system-level assessments of a launch vehicle. Aimed primarily at providing insight and making NASA a smart buyer, the Vehicle Integrated Performance Analysis (VIPA) team was created. The difference between the VIPA effort and previous integration attempts is that VIPA a process using experienced people from various disciplines, which focuses them on a technically integrated assessment. The foundations of VIPA s process are described. The VIPA team also recognized the need to target early detailed analysis toward identifying significant systems issues. This process is driven by the T-model for technical integration. VIPA s approach to performing system-level technical integration is discussed in detail. The VIPA process significantly enhances the development and monitoring of realizable project requirements. VIPA s assessment validates the concept s stated performance, identifies significant issues either with the concept or the requirements, and then reintegrates these issues to determine impacts. This process is discussed along with a description of how it may be integrated into a program s insight and review process. The VIPA process has gained favor with both engineering and project organizations for being responsive and insightful

Integrated marketing communications:pathway for enhancing client-costomer relationships

Directory of Open Access Journals (Sweden)

Kehinde Oladele Joseph

2010-12-01

Full Text Available The strategic coordination of marketing communication tools is vital and highly crucial for every result driven organization today. Companies must be able to deliver the right message to their target audience in order to elicit the right results. The objectives of this paper amongst others are to: (i ascertain whether proper implementation of Integrated Marketing Communications can help reduce the cost of marketing communication or promotional budget. (ii Establish whether the use of integrated marketing communications by firm through its advertising agencies can bring about profitable long-term client-customer relationships. The paper raises two hypotheses, which are stated in the null form. These are: The more an organization adopts Integrated Marketing communications, the more fund it will spend on promotional activities in the long run, and the less an organization adopts IMC principles, the more profitable Client-Customer relationship it will build. The paper uses survey method with structured questionnaire to obtain data that were later analyzed with correlation coefficient and analysis of variance test statistics. (ANOVA. Findings show that company will be able to save cost on marketing communication and promote lasting long-term client-customer relationships, if they properly adopt integrated marketing communication principles. The paper makes valuable recommendations which users of IMC will find useful in the ever dynamic and highly competitive world of marketing

BiologicalNetworks 2.0 - an integrative view of genome biology data

Directory of Open Access Journals (Sweden)

Ponomarenko Julia

2010-12-01

Full Text Available Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other and their relations (interactions, co-expression, co-citations, and other. The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.

Genes and (Common) Pathways Underlying Drug Addiction

Science.gov (United States)

Li, Chuan-Yun; Mao, Xizeng; Wei, Liping

2008-01-01

Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn), the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction. PMID:18179280

Genes and (common pathways underlying drug addiction.

Directory of Open Access Journals (Sweden)

Chuan-Yun Li

2008-01-01

Full Text Available Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn, the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction.

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

Science.gov (United States)

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

Directory of Open Access Journals (Sweden)

Bing Jiang

2017-01-01

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

Higher integrity of the motor and visual pathways in long-term video game players.

Science.gov (United States)

Zhang, Yang; Du, Guijin; Yang, Yongxin; Qin, Wen; Li, Xiaodong; Zhang, Quan

2015-01-01

Long term video game players (VGPs) exhibit superior visual and motor skills compared with non-video game control subjects (NVGCs). However, the neural basis underlying the enhanced behavioral performance remains largely unknown. To clarify this issue, the present study compared the whiter matter integrity within the corticospinal tracts (CST), the superior longitudinal fasciculus (SLF), the inferior longitudinal fasciculus (ILF), and the inferior fronto-occipital fasciculus (IFOF) between the VGPs and the NVGCs using diffusion tensor imaging. Compared with the NVGCs, voxel-wise comparisons revealed significantly higher fractional anisotropy (FA) values in some regions within the left CST, left SLF, bilateral ILF, and IFOF in VGPs. Furthermore, higher FA values in the left CST at the level of cerebral peduncle predicted a faster response in visual attention tasks. These results suggest that higher white matter integrity in the motor and higher-tier visual pathways is associated with long-term video game playing, which may contribute to the understanding on how video game play influences motor and visual performance.

Solution of fractional kinetic equation by a class of integral transform of pathway type

Science.gov (United States)

Kumar, Dilip

2013-04-01

Solutions of fractional kinetic equations are obtained through an integral transform named Pα-transform introduced in this paper. The Pα-transform is a binomial type transform containing many class of transforms including the well known Laplace transform. The paper is motivated by the idea of pathway model introduced by Mathai [Linear Algebra Appl. 396, 317-328 (2005), 10.1016/j.laa.2004.09.022]. The composition of the transform with differential and integral operators are proved along with convolution theorem. As an illustration of applications to the general theory of differential equations, a simple differential equation is solved by the new transform. Being a new transform, the Pα-transform of some elementary functions as well as some generalized special functions such as H-function, G-function, Wright generalized hypergeometric function, generalized hypergeometric function, and Mittag-Leffler function are also obtained. The results for the classical Laplace transform is retrieved by letting α → 1.

2050 pathway to an active renewable energy scenario for Jiangsu province

International Nuclear Information System (INIS)

Hong, Lixuan; Lund, Henrik; Mathiesen, Brian Vad; Möller, Bernd

2013-01-01

In 2009, Jiangsu province of China supplied 99.6 percent of its total energy consumption with fossil fuels, of which 82 percent was imported from other provinces and countries. With rising energy demand, frequent energy shortages, and increasing pollution, it is essential for Jiangsu to put more emphasis on improving its energy efficiency and utilizing its renewable resources in the future. This paper presents the integrated energy pathway for Jiangsu during its social and economic transformation until 2050. EnergyPLAN is the chosen energy system analysis tool, since it accounts for all sectors of the energy system that needs to be considered when integrating large-scale renewable energy. A current policy scenario (CPS) based on current energy policies and an ambitious policy scenario (APS) based on large-scale integration of renewable energy and ambitious measures of energy efficiency improvement are proposed. The two energy pathways are modeled and compared in terms of technology combination, non-fossil fuel shares of primary energy supply, socioeconomic costs, and CO 2 emissions. The insights from these pathways can provide valuable input for Jiangsu's future energy policies. - Highlights: ► An integrated energy pathway is designed for Jiangsu province by 2050. ► A current policy scenario and an ambitious policy scenario are modeled and assessed. ► The ambitious policy scenario can help stabilize CO 2 emissions and achieve better economy. ► The next 5–10 years would be a key period for Jiangsu's energy system transition. ► Several policy suggestions have been proposed.

Meta-analysis of global transcriptomics reveals conserved genetic pathways of Quercetin and Tannic acid mediated longevity in C. elegans

Directory of Open Access Journals (Sweden)

Kerstin ePietsch

2012-04-01

Full Text Available Recent research has highlighted that the polyphenols Quercetin and Tannic acid are capable of extending the lifespan of C. elegans. To gain a deep understanding of the underlying molecular genetics, we analyzed the global transcriptional patterns of nematodes exposed to Quercetin or Tannic acid concentrations that are non-effective (in lifespan extension, lifespan extending or toxic. By means of an intricate meta-analysis it was possible to compare the transcriptomes of polyphenol exposure to recently published data sets derived from i longevity mutants or ii infection. This detailed comparative in silico analysis facilitated the identification of compound specific and overlapping transcriptional profiles and allowed the formulation of mechanistic models of Quercetin and Tannic acid mediated longevity. Lifespan extension due to Quercetin was predominantly driven by the metabolome, TGF-beta signaling, Insulin-like signaling and the p38 MAPK pathway and Tannic acid’s impact involved, in part, the amino acid metabolism and was modulated by the TGF-beta and the p38 MAPK pathways. DAF-12, which integrates TGF-beta and Insulin-like downstream signaling, therefore seems to be a crucial regulator for both polyphenols.

Pathway Analysis of Metabolic Syndrome Using a Genome-Wide Association Study of Korea Associated Resource (KARE Cohorts

Directory of Open Access Journals (Sweden)

Unjin Shim

2014-12-01

Full Text Available Metabolic syndrome (MetS is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs, important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs, explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE was used for analysis, which include 8,842 individuals (age, 52.2 ± 8.9 years; body mass index, 24.6 ± 3.2 kg/m2. A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < 5 × 10-6, and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < 1.38 × 10-7, Bonferroni-adjusted p < 0.05. Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF, the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.

A functional genomics approach using metabolomics and in silico pathway analysis

DEFF Research Database (Denmark)

Förster, Jochen; Gombert, Andreas Karoly; Nielsen, Jens

2002-01-01

analysis techniques and changes in the genotype will in many cases lead to different metabolite profiles. Here, a theoretical framework that may be applied to identify the function of orphan genes is presented. The approach is based on a combination of metabolome analysis combined with in silico pathway...

Integrating emotional and psychological support into the end-stage renal disease pathway: a protocol for mixed methods research to identify patients' lower-level support needs and how these can most effectively be addressed.

Science.gov (United States)

Taylor, Francesca; Taylor, Celia; Baharani, Jyoti; Nicholas, Johann; Combes, Gill

2016-08-02

As a result of difficulties related to their illness, diagnosis and treatment, patients with end-stage renal disease experience significant emotional and psychological problems, which untreated can have considerable negative impact on their health and wellbeing. Despite evidence that patients desire improved support, management of their psychosocial problems, particularly at the lower-level, remains sub-optimal. There is limited understanding of the specific support that patients need and want, from whom, and when, and also a lack of data on what helps and hinders renal staff in identifying and responding to their patients' support needs, and how barriers to doing so might be overcome. Through this research we therefore seek to determine what, when, and how, support for patients with lower-level emotional and psychological problems should be integrated into the end-stage renal disease pathway. The research will involve two linked, multicentre studies, designed to identify and consider the perspectives of patients at five different stages of the end-stage renal disease pathway (Study 1), and renal staff working with them (Study 2). A convergent, parallel mixed methods design will be employed for both studies, with quantitative and qualitative data collected separately. For each study, the data sets will be analysed separately and the results then compared or combined using interpretive analysis. A further stage of synthesis will employ data-driven thematic analysis to identify: triangulation and frequency of themes across pathway stages; patterns and plausible explanations of effects. There is an important need for this research given the high frequency of lower-level distress experienced by end-stage renal disease patients and lack of progress to date in integrating support for their lower-level psychosocial needs into the care pathway. Use of a mixed methods design across the two studies will generate a holistic patient and healthcare professional perspective that

Pathways to Medical Home Recognition: A Qualitative Comparative Analysis of the PCMH Transformation Process.

Science.gov (United States)

Mendel, Peter; Chen, Emily K; Green, Harold D; Armstrong, Courtney; Timbie, Justin W; Kress, Amii M; Friedberg, Mark W; Kahn, Katherine L

2017-12-15

To understand the process of practice transformation by identifying pathways for attaining patient-centered medical home (PCMH) recognition. The CMS Federally Qualified Health Center (FQHC) Advanced Primary Care Practice Demonstration was designed to help FQHCs achieve NCQA Level 3 PCMH recognition and improve patient outcomes. We used a stratified random sample of 20 (out of 503) participating sites for this analysis. We developed a conceptual model of structural, cultural, and implementation factors affecting PCMH transformation based on literature and initial qualitative interview themes. We then used conventional cross-case analysis, followed by qualitative comparative analysis (QCA), a cross-case method based on Boolean logic algorithms, to systematically identify pathways (i.e., combinations of factors) associated with attaining-or not attaining-Level 3 recognition. Site-level indicators were derived from semistructured interviews with site leaders at two points in time (mid- and late-implementation) and administrative data collected prior to and during the demonstration period. The QCA results identified five distinct pathways to attaining PCMH recognition and four distinct pathways to not attaining recognition by the end of the demonstration. Across these pathways, one condition (change leader capacity) was common to all pathways for attaining recognition, and another (previous improvement or recognition experience) was absent in all pathways for not attaining recognition. In general, sites could compensate for deficiencies in one factor with capacity in others, but they needed a threshold of strengths in cultural and implementation factors to attain PCMH recognition. Future efforts at primary care transformation should take into account multiple pathways sites may pursue. Sites should be assessed on key cultural and implementation factors, in addition to structural components, in order to differentiate interventions and technical assistance. © Health

Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

Directory of Open Access Journals (Sweden)

Zhike Zi

Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

Intragraft Molecular Pathways Associated with Tolerance Induction in Renal Transplantation.

Science.gov (United States)

Gallon, Lorenzo; Mathew, James M; Bontha, Sai Vineela; Dumur, Catherine I; Dalal, Pranav; Nadimpalli, Lakshmi; Maluf, Daniel G; Shetty, Aneesha A; Ildstad, Suzanne T; Leventhal, Joseph R; Mas, Valeria R

2018-02-01

The modern immunosuppression regimen has greatly improved short-term allograft outcomes but not long-term allograft survival. Complications associated with immunosuppression, specifically nephrotoxicity and infection risk, significantly affect graft and patient survival. Inducing and understanding pathways underlying clinical tolerance after transplantation are, therefore, necessary. We previously showed full donor chimerism and immunosuppression withdrawal in highly mismatched allograft recipients using a bioengineered stem cell product (FCRx). Here, we evaluated the gene expression and microRNA expression profiles in renal biopsy samples from tolerance-induced FCRx recipients, paired donor organs before implant, and subjects under standard immunosuppression (SIS) without rejection and with acute rejection. Unlike allograft samples showing acute rejection, samples from FCRx recipients did not show upregulation of T cell- and B cell-mediated rejection pathways. Gene expression pathways differed slightly between FCRx samples and the paired preimplantation donor organ samples, but most of the functional gene networks overlapped. Notably, compared with SIS samples, FCRx samples showed upregulation of genes involved in pathways, like B cell receptor signaling. Additionally, prediction analysis showed inhibition of proinflammatory regulators and activation of anti-inflammatory pathways in FCRx samples. Furthermore, integrative analyses (microRNA and gene expression profiling from the same biopsy sample) identified the induction of regulators with demonstrated roles in the downregulation of inflammatory pathways and maintenance of tissue homeostasis in tolerance-induced FCRx samples compared with SIS samples. This pilot study highlights the utility of molecular intragraft evaluation of pathways related to FCRx-induced tolerance and the use of integrative analyses for identifying upstream regulators of the affected downstream molecular pathways. Copyright © 2018 by the

Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways

Directory of Open Access Journals (Sweden)

Salcedo Mauricio

2007-09-01

Full Text Available Abstract Background Cervical carcinoma (CC is a leading cause of death among women worldwide. Human papilloma virus (HPV is a major etiological factor in CC and HPV 16 is the more frequent viral type present. Our aim was to characterize metabolic pathways altered in HPV 16 tumor samples by means of transcriptome wide analysis and bioinformatics tools for visualizing expression data in the context of KEGG biological pathways. Results We found 2,067 genes significantly up or down-modulated (at least 2-fold in tumor clinical samples compared to normal tissues, representing ~3.7% of analyzed genes. Cervical carcinoma was associated with an important up-regulation of Wnt signaling pathway, which was validated by in situ hybridization in clinical samples. Other up-regulated pathways were those of calcium signaling and MAPK signaling, as well as cell cycle-related genes. There was down-regulation of focal adhesion, TGF-β signaling, among other metabolic pathways. Conclusion This analysis of HPV 16 tumors transcriptome could be useful for the identification of genes and molecular pathways involved in the pathogenesis of cervical carcinoma. Understanding the possible role of these proteins in the pathogenesis of CC deserves further studies.

The use of social network analysis to examine the transmission of Salmonella spp. within a vertically integrated broiler enterprise.

Science.gov (United States)

Crabb, Helen Kathleen; Allen, Joanne Lee; Devlin, Joanne Maree; Firestone, Simon Matthew; Stevenson, Mark Anthony; Gilkerson, James Rudkin

2018-05-01

To better understand factors influencing infectious agent dispersal within a livestock population information is needed on the nature and frequency of contacts between farm enterprises. This study uses social network analysis to describe the contact network within a vertically integrated broiler poultry enterprise to identify the potential horizontal and vertical transmission pathways for Salmonella spp. Nodes (farms, sheds, production facilities) were identified and the daily movement of commodities (eggs, birds, feed, litter) and people between nodes were extracted from routinely kept farm records. Three time periods were examined in detail, 1- and 8- and 17-weeks of the production cycle and contact networks were described for all movements, and by commodity and production type. All nodes were linked by at least one movement during the study period but network density was low indicating that all potential pathways between nodes did not exist. Salmonella spp. transmission via vertical or horizontal pathways can only occur along directed pathways when those pathways are present. Only two locations (breeder or feed nodes) were identified where the transmission of a single Salmonella spp. clone could theoretically percolate through the network to the broiler or processing nodes. Only the feed transmission pathway directly connected all parts of the network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Proliferation Resistance: Acquisition/Diversion Pathway Analysis for the DUPIC Fuel Cycle

International Nuclear Information System (INIS)

Ko, Won Il; Chang, Hong Lae; Song, Dae Yong; Lee, Ho Hee; Kwon, Eun Ha; Jeong, Chang Joon; Kim, Ho Dong

2009-07-01

Within the International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO), a methodology for evaluating proliferation resistance (INPRO PR methodology) has been developed. However, it remains to develop the methodology to evaluate User Requirements (UR) 4 regarding multiplicity and robustness of barriers against proliferation - innovative nuclear energy systems should incorporate multiple proliferation resistance features and measures. Since this requires an acquisition/diversion pathway analysis, this report describes a systematic approach developed for the identification and analysis of pathways for the acquisition of weapons-usable nuclear material using the DUPIC fuel cycle system. At the first step, the objectives of the proliferation were identified, including the quality and quantity of the material, the time required to acquire the material for the proliferation, thr capability of the potential proliferant country, etc. At the second step, the possible strategies, which the potential proliferant country could adopt, were identified: undeclared removal of nuclear material from the fuel cycle facilities; and further treatment of the diverted nuclear materials needed to acquire weapons-usable materials. At the final step, a systematic approach to select the plausible pathways for the acquisition/diversion of nuclear material during the whole fuel cycle has been developed. The coarse material diversion pathways for the DUPIC fuel cycle and the approach developed was reviewed and discussed at the experts meeting at the IAEA for its appropriateness and comprehensiveness

An Automated Pipeline for Engineering Many-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization.

Science.gov (United States)

Halper, Sean M; Cetnar, Daniel P; Salis, Howard M

2018-01-01

Engineering many-enzyme metabolic pathways suffers from the design curse of dimensionality. There are an astronomical number of synonymous DNA sequence choices, though relatively few will express an evolutionary robust, maximally productive pathway without metabolic bottlenecks. To solve this challenge, we have developed an integrated, automated computational-experimental pipeline that identifies a pathway's optimal DNA sequence without high-throughput screening or many cycles of design-build-test. The first step applies our Operon Calculator algorithm to design a host-specific evolutionary robust bacterial operon sequence with maximally tunable enzyme expression levels. The second step applies our RBS Library Calculator algorithm to systematically vary enzyme expression levels with the smallest-sized library. After characterizing a small number of constructed pathway variants, measurements are supplied to our Pathway Map Calculator algorithm, which then parameterizes a kinetic metabolic model that ultimately predicts the pathway's optimal enzyme expression levels and DNA sequences. Altogether, our algorithms provide the ability to efficiently map the pathway's sequence-expression-activity space and predict DNA sequences with desired metabolic fluxes. Here, we provide a step-by-step guide to applying the Pathway Optimization Pipeline on a desired multi-enzyme pathway in a bacterial host.

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

Science.gov (United States)

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

Directory of Open Access Journals (Sweden)

Miranda van Uitert

Full Text Available Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite and protein-protein associations (STRING. This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome. The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300 and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Integrated Assessment of Shallow-Aquifer Vulnerability to Multiple Contaminants and Drinking-Water Exposure Pathways in Holliston, Massachusetts

Directory of Open Access Journals (Sweden)

Birgit Claus Henn

2017-12-01

Full Text Available Half of U.S. drinking water comes from aquifers, and very shallow ones (<20 feet to water table are especially vulnerable to anthropogenic contamination. We present the case of Holliston, a Boston, Massachusetts suburb that draws its drinking water from very shallow aquifers, and where metals and solvents have been reported in groundwater. Community concerns focus on water discolored by naturally occurring manganese (Mn, despite reports stating regulatory aesthetic compliance. Epidemiologic studies suggest Mn is a potentially toxic element (PTE for children exposed by the drinking-water pathway at levels near the regulatory aesthetic level. We designed an integrated, community-based project: five sites were profiled for contaminant releases; service areas for wells were modeled; and the capture zone for one vulnerable well was estimated. Manganese, mercury, and trichloroethylene are among 20 contaminants of interest. Findings show that past and/or current exposures to multiple contaminants in drinking water are plausible, satisfying the criteria for complete exposure pathways. This case questions the adequacy of aquifer protection and monitoring regulations, and highlights the need for integrated assessment of multiple contaminants, associated exposures and health risks. It posits that community-researcher partnerships are essential for understanding and solving complex problems.

Integral data analysis for resonance parameters determination

International Nuclear Information System (INIS)

Larson, N.M.; Leal, L.C.; Derrien, H.

1997-09-01

Neutron time-of-flight experiments have long been used to determine resonance parameters. Those resonance parameters have then been used in calculations of integral quantities such as Maxwellian averages or resonance integrals, and results of those calculations in turn have been used as a criterion for acceptability of the resonance analysis. However, the calculations were inadequate because covariances on the parameter values were not included in the calculations. In this report an effort to correct for that deficiency is documented: (1) the R-matrix analysis code SAMMY has been modified to include integral quantities of importance, (2) directly within the resonance parameter analysis, and (3) to determine the best fit to both differential (microscopic) and integral (macroscopic) data simultaneously. This modification was implemented because it is expected to have an impact on the intermediate-energy range that is important for criticality safety applications

Identification of the missing links in prokaryotic pentose oxidation pathways: evidence for enzyme recruitment.

Science.gov (United States)

Brouns, Stan J J; Walther, Jasper; Snijders, Ambrosius P L; van de Werken, Harmen J G; Willemen, Hanneke L D M; Worm, Petra; de Vos, Marjon G J; Andersson, Anders; Lundgren, Magnus; Mazon, Hortense F M; van den Heuvel, Robert H H; Nilsson, Peter; Salmon, Laurent; de Vos, Willem M; Wright, Phillip C; Bernander, Rolf; van der Oost, John

2006-09-15

The pentose metabolism of Archaea is largely unknown. Here, we have employed an integrated genomics approach including DNA microarray and proteomics analyses to elucidate the catabolic pathway for D-arabinose in Sulfolobus solfataricus. During growth on this sugar, a small set of genes appeared to be differentially expressed compared with growth on D-glucose. These genes were heterologously overexpressed in Escherichia coli, and the recombinant proteins were purified and biochemically studied. This showed that D-arabinose is oxidized to 2-oxoglutarate by the consecutive action of a number of previously uncharacterized enzymes, including a D-arabinose dehydrogenase, a D-arabinonate dehydratase, a novel 2-keto-3-deoxy-D-arabinonate dehydratase, and a 2,5-dioxopentanoate dehydrogenase. Promoter analysis of these genes revealed a palindromic sequence upstream of the TATA box, which is likely to be involved in their concerted transcriptional control. Integration of the obtained biochemical data with genomic context analysis strongly suggests the occurrence of pentose oxidation pathways in both Archaea and Bacteria, and predicts the involvement of additional enzyme components. Moreover, it revealed striking genetic similarities between the catabolic pathways for pentoses, hexaric acids, and hydroxyproline degradation, which support the theory of metabolic pathway genesis by enzyme recruitment.

Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

Science.gov (United States)

Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

2011-10-04

Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

Integrated analysis of microRNA and gene expression profiles reveals a functional regulatory module associated with liver fibrosis.

Science.gov (United States)

Chen, Wei; Zhao, Wenshan; Yang, Aiting; Xu, Anjian; Wang, Huan; Cong, Min; Liu, Tianhui; Wang, Ping; You, Hong

2017-12-15

Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear. The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells. We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM

Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts.

Science.gov (United States)

Liggi, Sonia; Drakakis, Georgios; Koutsoukas, Alexios; Cortes-Ciriano, Isidro; Martínez-Alonso, Patricia; Malliavin, Thérèse E; Velazquez-Campoy, Adrian; Brewerton, Suzanne C; Bodkin, Michael J; Evans, David A; Glen, Robert C; Carrodeguas, José Alberto; Bender, Andreas

2014-01-01

An in silico mechanism-of-action analysis protocol was developed, comprising molecule bioactivity profiling, annotation of predicted targets with pathways and calculation of enrichment factors to highlight targets and pathways more likely to be implicated in the studied phenotype. The method was applied to a cytotoxicity phenotypic endpoint, with enriched targets/pathways found to be statistically significant when compared with 100 random datasets. Application on a smaller apoptotic set (10 molecules) did not allowed to obtain statistically relevant results, suggesting that the protocol requires modification such as analysis of the most frequently predicted targets/annotated pathways. Pathway annotations improved the mechanism-of-action information gained by target prediction alone, allowing a better interpretation of the predictions and providing better mapping of targets onto pathways.

Analysis of Stomatal Patterning in Selected Mutants of MAPK Pathways

KAUST Repository

Felemban, Abrar

2016-05-01

Stomata are cellular valves in plants that play an essential role in the regulation of gas exchange and are distributed in the epidermis of aerial organs. In Arabidopsis thaliana, stomatal production and development are coordinated by the mitogen-activated protein kinase (MAPK) signalling pathway, which modulates a variety of other processes, including cell proliferation, regulation of cytokinesis, programed cell death, and response to abiotic and biotic stress. The environment also plays a role in stomatal development, by influencing the frequency at which stomata develop in leaves. This thesis presents an analysis of stomatal development in Arabidopsis mutants in two MAPK pathways: MEKK1-MKK1/MKK2-MPK4, and MAP3K17/18-MKK3. Obtained results demonstrate the effect of stress conditions on stomatal development and specify the involvement of analysed MAPK in stomatal patterning. First, both analysed pathways modulate stomatal patterning in Arabidopsis cotyledons. Second, plant growth-promoting bacteria tested enhance stomatal density and affect guard cell morphology. Third, the sucrose or mannitol treatment increases defects in stomatal patterning. Finally, salt stress or high temperature can suppress stomatal defects in mutants of the MEKK1-MKK1/MKK2-MPK4 pathway.

Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome.

Science.gov (United States)

Shen, Haoran; Liang, Zhou; Zheng, Saihua; Li, Xuelian

2017-11-01

The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS.

Real analysis measure theory, integration, and Hilbert spaces

CERN Document Server

Stein, Elias M

2005-01-01

Real Analysis is the third volume in the Princeton Lectures in Analysis, a series of four textbooks that aim to present, in an integrated manner, the core areas of analysis. Here the focus is on the development of measure and integration theory, differentiation and integration, Hilbert spaces, and Hausdorff measure and fractals. This book reflects the objective of the series as a whole: to make plain the organic unity that exists between the various parts of the subject, and to illustrate the wide applicability of ideas of analysis to other fields of mathematics and science. After

Integration of Signaling Pathways with the Epigenetic Machinery in the Maintenance of Stem Cells

Directory of Open Access Journals (Sweden)

Luca Fagnocchi

2016-01-01

Full Text Available Stem cells balance their self-renewal and differentiation potential by integrating environmental signals with the transcriptional regulatory network. The maintenance of cell identity and/or cell lineage commitment relies on the interplay of multiple factors including signaling pathways, transcription factors, and the epigenetic machinery. These regulatory modules are strongly interconnected and they influence the pattern of gene expression of stem cells, thus guiding their cellular fate. Embryonic stem cells (ESCs represent an invaluable tool to study this interplay, being able to indefinitely self-renew and to differentiate towards all three embryonic germ layers in response to developmental cues. In this review, we highlight those mechanisms of signaling to chromatin, which regulate chromatin modifying enzymes, histone modifications, and nucleosome occupancy. In addition, we report the molecular mechanisms through which signaling pathways affect both the epigenetic and the transcriptional state of ESCs, thereby influencing their cell identity. We propose that the dynamic nature of oscillating signaling and the different regulatory network topologies through which those signals are encoded determine specific gene expression programs, leading to the fluctuation of ESCs among multiple pluripotent states or to the establishment of the necessary conditions to exit pluripotency.

An integrative genomic and transcriptomic analysis reveals potential targets associated with cell proliferation in uterine leiomyomas.

Directory of Open Access Journals (Sweden)

Priscila Daniele Ramos Cirilo

Full Text Available Uterine Leiomyomas (ULs are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs. Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs.We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC and gene expression microarrays (SAM. The CONEXIC algorithm was applied to integrate the data.The integrated analysis identified the top 30 significant genes (P<0.01, which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively and IGFBP5 (P = 0.0002 and P = 0.006, respectively were up-regulated in the tumours when compared with the adjacent normal myometrium.The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs.

Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.

Directory of Open Access Journals (Sweden)

Katrina M Waters

Full Text Available To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

Energy Technology Data Exchange (ETDEWEB)

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

2012-03-29

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

Science.gov (United States)

Jiang, Zhenhong; He, Fei; Zhang, Ziding

2017-07-01

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study

Activation of the cell wall integrity pathway promotes escape from G2 in the fungus Ustilago maydis.

Directory of Open Access Journals (Sweden)

Natalia Carbó

2010-07-01

Full Text Available It is widely accepted that MAPK activation in budding and fission yeasts is often associated with negative effects on cell cycle progression, resulting in delay or arrest at a specific stage in the cell cycle, thereby enabling cells to adapt to changing environmental conditions. For instance, activation of the Cell Wall Integrity (CWI pathway in the budding yeast Saccharomyces cerevisiae signals an increase in CDK inhibitory phosphorylation, which leads cells to remain in the G2 phase. Here we characterized the CWI pathway of Ustilago maydis, a fungus evolutionarily distant from budding and fission yeasts, and show that activation of the CWI pathway forces cells to escape from G2 phase. In spite of these disparate cell cycle responses in S. cerevisiae and U. maydis, the CWI pathway in both organisms appears to respond to the same class cell wall stressors. To understand the basis of such a difference, we studied the mechanism behind the U. maydis response. We found that activation of CWI pathway in U. maydis results in a decrease in CDK inhibitory phosphorylation, which depends on the mitotic phosphatase Cdc25. Moreover, in response to activation of the CWI pathway, Cdc25 accumulates in the nucleus, providing a likely explanation for the increase in the unphosphorylated form of CDK. We also found that the extended N-terminal domain of Cdc25, which is dispensable under normal growth conditions, is required for this G2 escape as well as for resistance to cell wall stressors. We propose that the process of cell cycle adaptation to cell stress evolved differently in these two divergent organisms so that each can move towards a cell cycle phase most appropriate for responding to the environmental signals encountered.

LncSubpathway: a novel approach for identifying dysfunctional subpathways associated with risk lncRNAs by integrating lncRNA and mRNA expression profiles and pathway topologies.

Science.gov (United States)

Xu, Yanjun; Li, Feng; Wu, Tan; Xu, Yingqi; Yang, Haixiu; Dong, Qun; Zheng, Meiyu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Li, Xia

2017-02-28

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including the development of many diseases. Pathway analysis is a valuable aid for understanding the cellular functions of these transcripts. We have developed and characterized LncSubpathway, a novel method that integrates lncRNA and protein coding gene (PCG) expression with interactome data to identify disease risk subpathways that functionally associated with risk lncRNAs. LncSubpathway identifies the most relevance regions which are related with risk lncRNA set and implicated with study conditions through simultaneously considering the dysregulation extent of lncRNAs, PCGs and their correlations. Simulation studies demonstrated that the sensitivity and false positive rates of LncSubpathway were within acceptable ranges, and that LncSubpathway could accurately identify dysregulated regions that related with disease risk lncRNAs within pathways. When LncSubpathway was applied to colorectal carcinoma and breast cancer subtype datasets, it identified cancer type- and breast cancer subtype-related meaningful subpathways. Further, analysis of its robustness and reproducibility indicated that LncSubpathway was a reliable means of identifying subpathways that functionally associated with lncRNAs. LncSubpathway is freely available at http://www.bio-bigdata.com/lncSubpathway/.

Transcriptome Analysis of Manganese-deficient Chlamydomonas reinhardtii Provides Insight on the Chlorophyll Biosynthesis Pathway

Energy Technology Data Exchange (ETDEWEB)

Lockhart, Ainsley; Zvenigorodsky, Natasha; Pedraza, Mary Ann; Lindquist, Erika

2011-08-11

The biosynthesis of chlorophyll and other tetrapyrroles is a vital but poorly understood process. Recent genomic advances with the unicellular green algae Chlamydomonas reinhardtii have created opportunity to more closely examine the mechanisms of the chlorophyll biosynthesis pathway via transcriptome analysis. Manganese is a nutrient of interest for complex reactions because of its multiple stable oxidation states and role in molecular oxygen coordination. C. reinhardtii was cultured in Manganese-deplete Tris-acetate-phosphate (TAP) media for 24 hours and used to create cDNA libraries for sequencing using Illumina TruSeq technology. Transcriptome analysis provided intriguing insight on possible regulatory mechanisms in the pathway. Evidence supports similarities of GTR (Glutamyl-tRNA synthase) to its Chlorella vulgaris homolog in terms of Mn requirements. Data was also suggestive of Mn-related compensatory up-regulation for pathway proteins CHLH1 (Manganese Chelatase), GUN4 (Magnesium chelatase activating protein), and POR1 (Light-dependent protochlorophyllide reductase). Intriguingly, data suggests possible reciprocal expression of oxygen dependent CPX1 (coproporphyrinogen III oxidase) and oxygen independent CPX2. Further analysis using RT-PCR could provide compelling evidence for several novel regulatory mechanisms in the chlorophyll biosynthesis pathway.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints

Science.gov (United States)

Klamt, Steffen; Gerstl, Matthias P.; Jungreuthmayer, Christian; Mahadevan, Radhakrishnan; Müller, Stefan

2017-01-01

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks. PMID:28406903

Integrated data analysis reveals potential drivers and pathways disrupted by DNA methylation in papillary thyroid carcinomas

DEFF Research Database (Denmark)

Beltrami, Caroline Moraes; Dos Reis, Mariana Bisarro; Barros-Filho, Mateus Camargo

2017-01-01

and positive correlation, respectively. Genes showing negative correlation underlined FGF and retinoic acid signaling as critical canonical pathways disrupted by DNA methylation in PTC. BRAF mutation was detected in 68% (28 of 41) of the tumors, which presented a higher level of demethylation (95...

Operational integration in primary health care: patient encounters and workflows.

Science.gov (United States)

Sifaki-Pistolla, Dimitra; Chatzea, Vasiliki-Eirini; Markaki, Adelais; Kritikos, Kyriakos; Petelos, Elena; Lionis, Christos

2017-11-29

Despite several countrywide attempts to strengthen and standardise the primary healthcare (PHC) system, Greece is still lacking a sustainable, policy-based model of integrated services. The aim of our study was to identify operational integration levels through existing patient care pathways and to recommend an alternative PHC model for optimum integration. The study was part of a large state-funded project, which included 22 randomly selected PHC units located across two health regions of Greece. Dimensions of operational integration in PHC were selected based on the work of Kringos and colleagues. A five-point Likert-type scale, coupled with an algorithm, was used to capture and transform theoretical framework features into measurable attributes. PHC services were grouped under the main categories of chronic care, urgent/acute care, preventive care, and home care. A web-based platform was used to assess patient pathways, evaluate integration levels and propose improvement actions. Analysis relied on a comparison of actual pathways versus optimal, the latter ones having been identified through literature review. Overall integration varied among units. The majority (57%) of units corresponded to a basic level. Integration by type of PHC service ranged as follows: basic (86%) or poor (14%) for chronic care units, poor (78%) or basic (22%) for urgent/acute care units, basic (50%) for preventive care units, and partial or basic (50%) for home care units. The actual pathways across all four categories of PHC services differed from those captured in the optimum integration model. Certain similarities were observed in the operational flows between chronic care management and urgent/acute care management. Such similarities were present at the highest level of abstraction, but also in common steps along the operational flows. Existing patient care pathways were mapped and analysed, and recommendations for an optimum integration PHC model were made. The developed web

Semantic web for integrated network analysis in biomedicine.

Science.gov (United States)

Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

2009-03-01

The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

Atmospheric Pathway Screening Analysis for Saltstone Disposal Facility Vault 4

International Nuclear Information System (INIS)

COOK, JAMES

2004-01-01

A sequential screening process using a methodology developed by the National Council on Radiation Protection and Measurements, professional judgment and process knowledge has been used to produce a list of radionuclides requiring detailed analysis to derive disposal limits for the Saltstone Disposal Facility based on the atmospheric pathway

An integrated analysis of miRNA and gene copy numbers in xenografts of Ewing's sarcoma

Directory of Open Access Journals (Sweden)

Mosakhani Neda

2012-03-01

Full Text Available Abstract Background Xenografts have been shown to provide a suitable source of tumor tissue for molecular analysis in the absence of primary tumor material. We utilized ES xenograft series for integrated microarray analyses to identify novel biomarkers. Method Microarray technology (array comparative genomic hybridization (aCGH and micro RNA arrays was used to screen and identify copy number changes and differentially expressed miRNAs of 34 and 14 passages, respectively. Incubated cells used for xenografting (Passage 0 were considered to represent the primary tumor. Four important differentially expressed miRNAs (miR-31, miR-31*, miR-145, miR-106 were selected for further validation by real time polymerase chain reaction (RT-PCR. Integrated analysis of aCGH and miRNA data was performed on 14 xenograft passages by bioinformatic methods. Results The most frequent losses and gains of DNA copy number were detected at 9p21.3, 16q and at 8, 15, 17q21.32-qter, 1q21.1-qter, respectively. The presence of these alterations was consistent in all tumor passages. aCGH profiles of xenograft passages of each series resembled their corresponding primary tumors (passage 0. MiR-21, miR-31, miR-31*, miR-106b, miR-145, miR-150*, miR-371-5p, miR-557 and miR-598 showed recurrently altered expression. These miRNAS were predicted to regulate many ES-associated genes, such as genes of the IGF1 pathway, EWSR1, FLI1 and their fusion gene (EWS-FLI1. Twenty differentially expressed miRNAs were pinpointed in regions carrying altered copy numbers. Conclusion In the present study, ES xenografts were successfully applied for integrated microarray analyses. Our findings showed expression changes of miRNAs that were predicted to regulate many ES associated genes, such as IGF1 pathway genes, FLI1, EWSR1, and the EWS-FLI1 fusion genes.

Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA.

Science.gov (United States)

Yang, Xian; Han, Rui; Guo, Yike; Bradley, Jeremy; Cox, Benita; Dickinson, Robert; Kitney, Richard

2012-01-01

Hospitals nowadays have to serve numerous patients with limited medical staff and equipment while maintaining healthcare quality. Clinical pathway informatics is regarded as an efficient way to solve a series of hospital challenges. To date, conventional research lacks a mathematical model to describe clinical pathways. Existing vague descriptions cannot fully capture the complexities accurately in clinical pathways and hinders the effective management and further optimization of clinical pathways. Given this motivation, this paper presents a clinical pathway management platform, the Imperial Clinical Pathway Analyzer (ICPA). By extending the stochastic model performance evaluation process algebra (PEPA), ICPA introduces a clinical-pathway-specific model: clinical pathway PEPA (CPP). ICPA can simulate stochastic behaviours of a clinical pathway by extracting information from public clinical databases and other related documents using CPP. Thus, the performance of this clinical pathway, including its throughput, resource utilisation and passage time can be quantitatively analysed. A typical clinical pathway on stroke extracted from a UK hospital is used to illustrate the effectiveness of ICPA. Three application scenarios are tested using ICPA: 1) redundant resources are identified and removed, thus the number of patients being served is maintained with less cost; 2) the patient passage time is estimated, providing the likelihood that patients can leave hospital within a specific period; 3) the maximum number of input patients are found, helping hospitals to decide whether they can serve more patients with the existing resource allocation. ICPA is an effective platform for clinical pathway management: 1) ICPA can describe a variety of components (state, activity, resource and constraints) in a clinical pathway, thus facilitating the proper understanding of complexities involved in it; 2) ICPA supports the performance analysis of clinical pathway, thereby assisting

Advanced Concept Architecture Design and Integrated Analysis (ACADIA)

Science.gov (United States)

2017-11-03

1 Advanced Concept Architecture Design and Integrated Analysis (ACADIA) Submitted to the National Institute of Aerospace (NIA) on...Research Report 20161001 - 20161030 Advanced Concept Architecture Design and Integrated Analysis (ACADIA) W911NF-16-2-0229 8504Cedric Justin, Youngjun

Enhancement of Nucleoside Production in Hirsutella sinensis Based on Biosynthetic Pathway Analysis

Science.gov (United States)

Liu, Zhi-Qiang; Zhang, Bo; Lin, Shan; Baker, Peter James; Chen, Mao-Sheng; Xue, Ya-Ping; Wu, Hui; Xu, Feng; Yuan, Shui-Jin; Teng, Yi; Wu, Ling-Fang

2017-01-01

To enhance nucleoside production in Hirsutella sinensis, the biosynthetic pathways of purine and pyrimidine nucleosides were constructed and verified. The differential expression analysis showed that purine nucleoside phosphorylase, inosine monophosphate dehydrogenase, and guanosine monophosphate synthase genes involved in purine nucleotide biosynthesis were significantly upregulated 16.56-fold, 8-fold, and 5.43-fold, respectively. Moreover, dihydroorotate dehydrogenase, uridine nucleosidase, uridine/cytidine monophosphate kinase, and inosine triphosphate pyrophosphatase genes participating in pyrimidine nucleoside biosynthesis were upregulated 4.53-fold, 10.63-fold, 4.26-fold, and 5.98-fold, respectively. To enhance the nucleoside production, precursors for synthesis of nucleosides were added based on the analysis of biosynthetic pathways. Uridine and cytidine contents, respectively, reached 5.04 mg/g and 3.54 mg/g when adding 2 mg/mL of ribose, resulting in an increase of 28.6% and 296% compared with the control, respectively. Meanwhile, uridine and cytidine contents, respectively, reached 10.83 mg/g 2.12 mg/g when adding 0.3 mg/mL of uracil, leading to an increase of 176.3% and 137.1%, respectively. This report indicated that fermentation regulation was an effective way to enhance the nucleoside production in H. sinensis based on biosynthetic pathway analysis. PMID:29333435

Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia

International Nuclear Information System (INIS)

Raponi, Mitch; Belly, Robert T; Karp, Judith E; Lancet, Jeffrey E; Atkins, David; Wang, Yixin

2004-01-01

Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA™, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML). Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

Science.gov (United States)

Wilson, Paul; Larminie, Christopher; Smith, Rona

2016-01-01

To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

Science.gov (United States)

Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

2013-01-01

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

Interleukin-2 signaling pathway analysis by quantitative phosphoproteomics

DEFF Research Database (Denmark)

Osinalde, Nerea; Moss, Helle; Arrizabalaga, Onetsine

2011-01-01

among which 79 were found with increased abundance in the tyrosine-phosphorylated complexes, including several previously not reported IL-2 downstream effectors. Combinatorial site-specific phosphoproteomic analysis resulted in identification of 99 phosphorylated sites mapping to the identified proteins...... with increased abundance in the tyrosine-phosphorylated complexes, of which 34 were not previously described. In addition, chemical inhibition of the identified IL-2-mediated JAK, PI3K and MAPK signaling pathways, resulted in distinct alteration on the IL-2 dependent proliferation....

Developing an Integrated Treatment Pathway for a Post-Coronary Artery Bypass Grating (CABG) Geriatric Patient with Comorbid Hypertension and Type 1 Diabetes Mellitus for Treating Acute Hypoglycemia and Electrolyte Imbalance.

Science.gov (United States)

Naqvi, Atta Abbas; Shah, Amna; Ahmad, Rizwan; Ahmad, Niyaz

2017-01-01

The ailments afflicting the elderly population is a well-defined specialty of medicine. It calls for an immaculately designed health-care plan to treat diseases in geriatrics. For chronic illnesses such as diabetes mellitus (DM), coronary heart disease, and hypertension (HTN), they require proper management throughout the rest of patient's life. An integrated treatment pathway helps in treatment decision-making and improving standards of health care for the patient. This case describes an exclusive clinical pharmacist-driven designing of an integrated treatment pathway for a post-coronary artery bypass grafting (CABG) geriatric male patient with DM type I and HTN for the treatment of hypoglycemia and electrolyte imbalance. The treatment begins addressing the chief complaints which were vomiting and unconsciousness. Biochemical screening is essential to establish a diagnosis of electrolyte imbalance along with blood glucose level after which the integrated pathway defines the treatment course. This individualized treatment pathway provides an outline of the course of treatment of acute hypoglycemia, electrolyte imbalance as well as some unconfirmed diagnosis, namely, acute coronary syndrome and respiratory tract infection for a post-CABG geriatric patient with HTN and type 1 DM. The eligibility criterion for patients to be treated according to treatment pathway is to fall in the defined category.

A peer review process as part of the implementation of clinical pathways in radiation oncology: Does it improve compliance?

Science.gov (United States)

Gebhardt, Brian J; Heron, Dwight E; Beriwal, Sushil

Clinical pathways are patient management plans that standardize evidence-based practices to ensure high-quality and cost-effective medical care. Implementation of a pathway is a collaborative process in our network, requiring the active involvement of physicians. This approach promotes acceptance of pathway recommendations, although a peer review process is necessary to ensure compliance and to capture and approve off-pathway selections. We investigated the peer review process and factors associated with time to completion of peer review. Our cancer center implemented radiation oncology pathways for every disease site throughout a large, integrated network. Recommendations are written based upon national guidelines, published literature, and institutional experience with evidence evaluated hierarchically in order of efficacy, toxicity, and then cost. Physicians enter decisions into an online, menu-driven decision support tool that integrates with medical records. Data were collected from the support tool and included the rate of on- and off-pathway selections, peer review decisions performed by disease site directors, and time to complete peer review. A total of 6965 treatment decisions were entered in 2015, and 605 (8.7%) were made off-pathway and were subject to peer review. The median time to peer review decision was 2 days (interquartile range, 0.2-6.8). Factors associated with time to peer review decision >48 hours on univariate analysis include disease site (P peer review (P 48 hours. Clinical pathways are an integral tool for standardizing evidence-based care throughout our large, integrated network, with 91.3% of all treatment decisions being made as per pathway. The peer review process was feasible, with peer review of treatment decisions encourages compliance with clinical pathway recommendations. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Development of safety analysis technology for integral reactor

Energy Technology Data Exchange (ETDEWEB)

Sim, Suk K.; Song, J. H.; Chung, Y. J. and others

1999-03-01

Inherent safety features and safety system characteristics of the SMART integral reactor are investigated in this study. Performance and safety of the SMART conceptual design have been evaluated and confirmed through the performance and safety analyses using safety analysis system codes as well as a preliminary performance and safety analysis methodology. SMART design base events and their acceptance criteria are identified to develop a preliminary PIRT for the SMART integral reactor. Using the preliminary PIRT, a set of experimental program for the thermal hydraulic separate effect tests and the integral effect tests was developed for the thermal hydraulic model development and the system code validation. Safety characteristics as well as the safety issues of the integral reactor has been identified during the study, which will be used to resolve the safety issues and guide the regulatory criteria for the integral reactor. The results of the performance and safety analyses performed during the study were used to feedback for the SMART conceptual design. The performance and safety analysis code systems as well as the preliminary safety analysis methodology developed in this study will be validated as the SMART design evolves. The performance and safety analysis technology developed during the study will be utilized for the SMART basic design development. (author)

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

Science.gov (United States)

Cong, Wang; Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Liu, Wenjie; Wang, Ying; Cheng, Sipu; Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Saykin, Andrew J; Liang, Hong; Shen, Li

2017-05-30

The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ 1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ 1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta

Pathway analysis of systemic transcriptome responses to injected polystyrene particles in zebrafish larvae.

Science.gov (United States)

Veneman, Wouter J; Spaink, Herman P; Brun, Nadja R; Bosker, Thijs; Vijver, Martina G

2017-09-01

Microplastics are a contaminant of emergent concern in the environment, however, to date there is a limited understanding on their movement within organisms and the response of organisms. In the current study zebrafish embryos at different development stages were exposed to 700nm fluorescent polystyrene (PS) particles and the response pathway after exposure was investigated using imaging and transcriptomics. Our results show limited spreading of particles within the larvae after injection during the blastula stage. This is in contrast to injection of PS particles in the yolk of 2-day old embryos, which resulted in redistribution of the PS particles throughout the bloodstream, and accumulation in the heart region. Although injection was local, the transcriptome profiling showed strong responses of zebrafish embryos exposed to PS particle, indicating a systemic response. We found several biological pathways activated which are related to an immune response in the PS exposed zebrafish larvae. Most notably the complement system was enriched as indicated by upregulation of genes in the alternative complement pathway (e.g. cfhl3, cfhl4, cfb and c9). The fact that complement pathway is activated indicates that plastic microparticles are integrated in immunological recognition processes. This was supported by fluorescence microscopy results, in which we observed co-localisation of neutrophils and macrophages around the PS particles. Identifying these key events can be a first building block to the development of an adverse outcome pathway (AOP). These data subsequently can be used within ecological and human risk assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cloning and Expression Analysis of MEP Pathway Enzyme-encoding Genes in Osmanthus fragrans

Directory of Open Access Journals (Sweden)

Chen Xu

2016-09-01

Full Text Available The 2-C-methyl-d-erythritol 4-phosphate (MEP pathway is responsible for the biosynthesis of many crucial secondary metabolites, such as carotenoids, monoterpenes, plastoquinone, and tocopherols. In this study, we isolated and identified 10 MEP pathway genes in the important aromatic plant sweet osmanthus (Osmanthus fragrans. Multiple sequence alignments revealed that 10 MEP pathway genes shared high identities with other reported proteins. The genes showed distinctive expression profiles in various tissues, or at different flower stages and diel time points. The qRT-PCR results demonstrated that these genes were highly expressed in inflorescences, which suggested a tissue-specific transcript pattern. Our results also showed that OfDXS1, OfDXS2, and OfHDR1 had a clear diurnal oscillation pattern. The isolation and expression analysis provides a strong foundation for further research on the MEP pathway involved in gene function and molecular evolution, and improves our understanding of the molecular mechanism underlying this pathway in plants.

Metabolic pathway analysis and kinetic studies for production of nattokinase in Bacillus subtilis.

Science.gov (United States)

Unrean, Pornkamol; Nguyen, Nhung H A

2013-01-01

We have constructed a reaction network model of Bacillus subtilis. The model was analyzed using a pathway analysis tool called elementary mode analysis (EMA). The analysis tool was used to study the network capabilities and the possible effects of altered culturing conditions on the production of a fibrinolytic enzyme, nattokinase (NK) by B. subtilis. Based on all existing metabolic pathways, the maximum theoretical yield for NK synthesis in B. subtilis under different substrates and oxygen availability was predicted and the optimal culturing condition for NK production was identified. To confirm model predictions, experiments were conducted by testing these culture conditions for their influence on NK activity. The optimal culturing conditions were then applied to batch fermentation, resulting in high NK activity. The EMA approach was also applied for engineering B. subtilis metabolism towards the most efficient pathway for NK synthesis by identifying target genes for deletion and overexpression that enable the cell to produce NK at the maximum theoretical yield. The consistency between experiments and model predictions proves the feasibility of EMA being used to rationally design culture conditions and genetic manipulations for the efficient production of desired products.

Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

Science.gov (United States)

Xie, Jianbo; Tian, Jiaxing; Du, Qingzhang; Chen, Jinhui; Li, Ying; Yang, Xiaohui; Li, Bailian; Zhang, Deqiang

2016-05-01

Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study

Energy Technology Data Exchange (ETDEWEB)

Cochran, Jaquelin M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Palchak, Joseph D [National Renewable Energy Lab. (NREL), Golden, CO (United States); McBennett, Brendan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Milligan, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Ehlen, Ali [National Renewable Energy Lab. (NREL), Golden, CO (United States); Deshmukh, Ranjit [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Abhyankar, Nikit [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Soonee, Sushil Kumar [Power System Operation Corporation Limited (POSOCO), New Delhi (India); Narasimhan, S. R. [Power System Operation Corporation Limited (POSOCO), New Delhi (India); Joshi, Mohit [Power System Operation Corporation Limited (POSOCO), New Delhi (India); Sreedharan, Priya [U.S. Agency for International Development (USAID), Washington, DC (United States)

2017-10-27

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinated operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission

Tolerant industrial yeast Saccharomyces cerevisiae posses a more robust cell wall integrity signaling pathway against 2-furaldehyde and 5-(hydroxymethyl)-2-furaldehyde

Science.gov (United States)

Cell wall integrity signaling pathway in Saccharomyces cerevisiae is a conserved function for detecting and responding to cell stress conditions but less understood for industrial yeast. We dissected gene expression dynamics for a tolerant industrial yeast strain NRRL Y-50049 in response to challeng...

Cost benefit analysis of power plant database integration

International Nuclear Information System (INIS)

Wilber, B.E.; Cimento, A.; Stuart, R.

1988-01-01

A cost benefit analysis of plant wide data integration allows utility management to evaluate integration and automation benefits from an economic perspective. With this evaluation, the utility can determine both the quantitative and qualitative savings that can be expected from data integration. The cost benefit analysis is then a planning tool which helps the utility to develop a focused long term implementation strategy that will yield significant near term benefits. This paper presents a flexible cost benefit analysis methodology which is both simple to use and yields accurate, verifiable results. Included in this paper is a list of parameters to consider, a procedure for performing the cost savings analysis, and samples of this procedure when applied to a utility. A case study is presented involving a specific utility where this procedure was applied. Their uses of the cost-benefit analysis are also described

Representative Agricultural Pathways and Scenarios for Regional Integrated Assessment of Climate Change Impacts, Vulnerability, and Adaptation. 5; Chapter

Science.gov (United States)

Valdivia, Roberto O.; Antle, John M.; Rosenzweig, Cynthia; Ruane, Alexander C.; Vervoort, Joost; Ashfaq, Muhammad; Hathie, Ibrahima; Tui, Sabine Homann-Kee; Mulwa, Richard; Nhemachena, Charles;

Integration of Design and Control through Model Analysis

DEFF Research Database (Denmark)

Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

2002-01-01

A systematic computer aided analysis of the process model is proposed as a pre-solution step for integration of design and control problems. The process model equations are classified in terms of balance equations, constitutive equations and conditional equations. Analysis of the phenomena models...... (structure selection) issues for the integrated problems are considered. (C) 2002 Elsevier Science Ltd. All rights reserved....... representing the constitutive equations identify the relationships between the important process and design variables, which help to understand, define and address some of the issues related to integration of design and control. Furthermore, the analysis is able to identify a set of process (control) variables...

Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways.

Science.gov (United States)

Lee, Yun; Lafontaine Rivera, Jimmy G; Liao, James C

2014-09-01

Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Direct integration multiple collision integral transport analysis method for high energy fusion neutronics

International Nuclear Information System (INIS)

Koch, K.R.

1985-01-01

A new analysis method specially suited for the inherent difficulties of fusion neutronics was developed to provide detailed studies of the fusion neutron transport physics. These studies should provide a better understanding of the limitations and accuracies of typical fusion neutronics calculations. The new analysis method is based on the direct integration of the integral form of the neutron transport equation and employs a continuous energy formulation with the exact treatment of the energy angle kinematics of the scattering process. In addition, the overall solution is analyzed in terms of uncollided, once-collided, and multi-collided solution components based on a multiple collision treatment. Furthermore, the numerical evaluations of integrals use quadrature schemes that are based on the actual dependencies exhibited in the integrands. The new DITRAN computer code was developed on the Cyber 205 vector supercomputer to implement this direct integration multiple-collision fusion neutronics analysis. Three representative fusion reactor models were devised and the solutions to these problems were studied to provide suitable choices for the numerical quadrature orders as well as the discretized solution grid and to understand the limitations of the new analysis method. As further verification and as a first step in assessing the accuracy of existing fusion-neutronics calculations, solutions obtained using the new analysis method were compared to typical multigroup discrete ordinates calculations

Compromised Integrity of Central Visual Pathways in Patients With Macular Degeneration.

Science.gov (United States)

Malania, Maka; Konrad, Julia; Jägle, Herbert; Werner, John S; Greenlee, Mark W

2017-06-01

Macular degeneration (MD) affects the central retina and leads to gradual loss of foveal vision. Although, photoreceptors are primarily affected in MD, the retinal nerve fiber layer (RNFL) and central visual pathways may also be altered subsequent to photoreceptor degeneration. Here we investigate whether retinal damage caused by MD alters microstructural properties of visual pathways using diffusion-weighted magnetic resonance imaging. Six MD patients and six healthy control subjects participated in the study. Retinal images were obtained by spectral-domain optical coherence tomography (SD-OCT). Diffusion tensor images (DTI) and high-resolution T1-weighted structural images were collected for each subject. We used diffusion-based tensor modeling and probabilistic fiber tractography to identify the optic tract (OT) and optic radiations (OR), as well as nonvisual pathways (corticospinal tract and anterior fibers of corpus callosum). Fractional anisotropy (FA) and axial and radial diffusivity values (AD, RD) were calculated along the nonvisual and visual pathways. Measurement of RNFL thickness reveals that the temporal circumpapillary retinal nerve fiber layer was significantly thinner in eyes with macular degeneration than normal. While we did not find significant differences in diffusion properties in nonvisual pathways, patients showed significant changes in diffusion scalars (FA, RD, and AD) both in OT and OR. The results indicate that the RNFL and the white matter of the visual pathways are significantly altered in MD patients. Damage to the photoreceptors in MD leads to atrophy of the ganglion cell axons and to corresponding changes in microstructural properties of central visual pathways.

International Space Station Configuration Analysis and Integration

Science.gov (United States)

Anchondo, Rebekah

2016-01-01

Ambitious engineering projects, such as NASA's International Space Station (ISS), require dependable modeling, analysis, visualization, and robotics to ensure that complex mission strategies are carried out cost effectively, sustainably, and safely. Learn how Booz Allen Hamilton's Modeling, Analysis, Visualization, and Robotics Integration Center (MAVRIC) team performs engineering analysis of the ISS Configuration based primarily on the use of 3D CAD models. To support mission planning and execution, the team tracks the configuration of ISS and maintains configuration requirements to ensure operational goals are met. The MAVRIC team performs multi-disciplinary integration and trade studies to ensure future configurations meet stakeholder needs.

Overcoming barriers to integrating economic analysis into risk assessment.

Science.gov (United States)

Hoffmann, Sandra

2011-09-01

Regulatory risk analysis is designed to provide decisionmakers with a clearer understanding of how policies are likely to affect risk. The systems that produce risk are biological, physical, and social and economic. As a result, risk analysis is an inherently interdisciplinary task. Yet in practice, risk analysis has been interdisciplinary in only limited ways. Risk analysis could provide more accurate assessments of risk if there were better integration of economics and other social sciences into risk assessment itself. This essay examines how discussions about risk analysis policy have influenced the roles of various disciplines in risk analysis. It explores ways in which integrated bio/physical-economic modeling could contribute to more accurate assessments of risk. It reviews examples of the kind of integrated economics-bio/physical modeling that could be used to enhance risk assessment. The essay ends with a discussion of institutional barriers to greater integration of economic modeling into risk assessment and provides suggestions on how these might be overcome. © 2011 Society for Risk Analysis.

Integrating fire management analysis into land management planning

Science.gov (United States)

Thomas J. Mills

1983-01-01

The analysis of alternative fire management programs should be integrated into the land and resource management planning process, but a single fire management analysis model cannot meet all planning needs. Therefore, a set of simulation models that are analytically separate from integrated land management planning models are required. The design of four levels of fire...

Arachidonic Acid Metabolism Pathway Is Not Only Dominant in Metabolic Modulation but Associated With Phenotypic Variation After Acute Hypoxia Exposure

Directory of Open Access Journals (Sweden)

Chang Liu

2018-03-01

Full Text Available Background: The modulation of arachidonic acid (AA metabolism pathway is identified in metabolic alterations after hypoxia exposure, but its biological function is controversial. We aimed at integrating plasma metabolomic and transcriptomic approaches to systematically explore the roles of the AA metabolism pathway in response to acute hypoxia using an acute mountain sickness (AMS model.Methods: Blood samples were obtained from 53 enrolled subjects before and after exposure to high altitude. Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry and RNA sequencing were separately performed for metabolomic and transcriptomic profiling, respectively. Influential modules comprising essential metabolites and genes were identified by weighted gene co-expression network analysis (WGCNA after integrating metabolic information with phenotypic and transcriptomic datasets, respectively.Results: Enrolled subjects exhibited diverse response manners to hypoxia. Combined with obviously altered heart rate, oxygen saturation, hemoglobin, and Lake Louise Score (LLS, metabolomic profiling detected that 36 metabolites were highly related to clinical features in hypoxia responses, out of which 27 were upregulated and nine were downregulated, and could be mapped to AA metabolism pathway significantly. Integrated analysis of metabolomic and transcriptomic data revealed that these dominant molecules showed remarkable association with genes in gas transport incapacitation and disorders of hemoglobin metabolism pathways, such as ALAS2, HEMGN. After detailed description of AA metabolism pathway, we found that the molecules of 15-d-PGJ2, PGA2, PGE2, 12-O-3-OH-LTB4, LTD4, LTE4 were significantly up-regulated after hypoxia stimuli, and increased in those with poor response manner to hypoxia particularly. Further analysis in another cohort showed that genes in AA metabolism pathway such as PTGES, PTGS1, GGT1, TBAS1 et al. were excessively

Integrating neural network technology and noise analysis

International Nuclear Information System (INIS)

Uhrig, R.E.; Oak Ridge National Lab., TN

1995-01-01

The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check values and bearings illustrate the usefulness of the methodology developed. (Author)

Phytohormone signaling pathway analysis method for comparing hormone responses in plant-pest interactions

Directory of Open Access Journals (Sweden)

Studham Matthew E

2012-07-01

Full Text Available Abstract Background Phytohormones mediate plant defense responses to pests and pathogens. In particular, the hormones jasmonic acid, ethylene, salicylic acid, and abscisic acid have been shown to dictate and fine-tune defense responses, and identification of the phytohormone components of a particular defense response is commonly used to characterize it. Identification of phytohormone regulation is particularly important in transcriptome analyses. Currently there is no computational tool to determine the relative activity of these hormones that can be applied to transcriptome analyses in soybean. Findings We developed a pathway analysis method that provides a broad measure of the activation or suppression of individual phytohormone pathways based on changes in transcript expression of pathway-related genes. The magnitude and significance of these changes are used to determine a pathway score for a phytohormone for a given comparison in a microarray experiment. Scores for individual hormones can then be compared to determine the dominant phytohormone in a given defense response. To validate this method, it was applied to publicly available data from previous microarray experiments that studied the response of soybean plants to Asian soybean rust and soybean cyst nematode. The results of the analyses for these experiments agreed with our current understanding of the role of phytohormones in these defense responses. Conclusions This method is useful in providing a broad measure of the relative induction and suppression of soybean phytohormones during a defense response. This method could be used as part of microarray studies that include individual transcript analysis, gene set analysis, and other methods for a comprehensive defense response characterization.

Comparative expression pathway analysis of human and canine mammary tumors

Directory of Open Access Journals (Sweden)

Marconato Laura

2009-03-01

Full Text Available Abstract Background Spontaneous tumors in dog have been demonstrated to share many features with their human counterparts, including relevant molecular targets, histological appearance, genetics, biological behavior and response to conventional treatments. Mammary tumors in dog therefore provide an attractive alternative to more classical mouse models, such as transgenics or xenografts, where the tumour is artificially induced. To assess the extent to which dog tumors represent clinically significant human phenotypes, we performed the first genome-wide comparative analysis of transcriptional changes occurring in mammary tumors of the two species, with particular focus on the molecular pathways involved. Results We analyzed human and dog gene expression data derived from both tumor and normal mammary samples. By analyzing the expression levels of about ten thousand dog/human orthologous genes we observed a significant overlap of genes deregulated in the mammary tumor samples, as compared to their normal counterparts. Pathway analysis of gene expression data revealed a great degree of similarity in the perturbation of many cancer-related pathways, including the 'PI3K/AKT', 'KRAS', 'PTEN', 'WNT-beta catenin' and 'MAPK cascade'. Moreover, we show that the transcriptional relationships between different gene signatures observed in human breast cancer are largely maintained in the canine model, suggesting a close interspecies similarity in the network of cancer signalling circuitries. Conclusion Our data confirm and further strengthen the value of the canine mammary cancer model and open up new perspectives for the evaluation of novel cancer therapeutics and the development of prognostic and diagnostic biomarkers to be used in clinical studies.

Integrative analysis of copy number alteration and gene expression profiling in ovarian clear cell adenocarcinoma.

Science.gov (United States)

Sung, Chang Ohk; Choi, Chel Hun; Ko, Young-Hyeh; Ju, Hyunjeong; Choi, Yoon-La; Kim, Nyunsu; Kang, So Young; Ha, Sang Yun; Choi, Kyusam; Bae, Duk-Soo; Lee, Jeong-Won; Kim, Tae-Joong; Song, Sang Yong; Kim, Byoung-Gie

2013-05-01

Ovarian clear cell adenocarcinoma (Ov-CCA) is a distinctive subtype of ovarian epithelial carcinoma. In this study, we performed array comparative genomic hybridization (aCGH) and paired gene expression microarray of 19 fresh-frozen samples and conducted integrative analysis. For the copy number alterations, significantly amplified regions (false discovery rate [FDR] q genes demonstrating frequent copy number alterations (>25% of samples) that correlated with gene expression (FDR genes were mainly located on 8p11.21, 8p21.2-p21.3, 8q22.1, 8q24.3, 17q23.2-q23.3, 19p13.3, and 19p13.11. Among the regions, 8q24.3 was found to contain the most genes (30 of 94 genes) including PTK2. The 8q24.3 region was indicated as the most significant region, as supported by copy number, GISTIC, and integrative analysis. Pathway analysis using differentially expressed genes on 8q24.3 revealed several major nodes, including PTK2. In conclusion, we identified a set of 94 candidate genes with frequent copy number alterations that correlated with gene expression. Specific chromosomal alterations, such as the 8q24.3 gain containing PTK2, could be a therapeutic target in a subset of Ov-CCAs. Copyright © 2013. Published by Elsevier Inc.

Prioritizing Acquisition Pathways in the State Level Concept

Energy Technology Data Exchange (ETDEWEB)

Murphy, Chantell L. [Los Alamos National Laboratory; Budlong-Sylvester, Kory [Los Alamos National Laboratory; Pilat, Joseph F. [Los Alamos National Laboratory

2012-06-27

The International Atomic Energy Agency's (IAEA) Department of Safeguards has launched a project to further develop the State-level concept for the planning, implementation, and evaluation of safeguards activities. In order to further evolve the safeguards system an emphasis is placed on integrating inspection-related activities and the State evaluation process to draw safeguards conclusions in the most efficient way. The credible implementation of acquisition pathway analysis is central to the success of the IAEA's State-level concept. NNSA's Office of Nuclear Safeguards and Security (NA-241) The Next Generation Safeguards Initiative (NGSI) is sponsoring Los Alamos National Laboratory (LANL) to produce a study that will examine the use of acquisition pathway analysis in: (1) Developing a State-specific, State-level approach (SLA) and Annual Implementation Plan (AIP); (2) Maximizing the utility of the physical model; and (3) Supporting resource allocation decisions through a pathway prioritization. To deal with the challenge of developing an effective and efficient SLA, this study looks at: (1) Prioritizing proliferation pathways based on an assessment of a State's capabilities and assumed proliferation strategies; and (2) Relevant State behavior (e.g., transparency, cooperation, etc.) while avoiding subjective judgments about States themselves. The study makes use of case studies and concrete examples in order to illustrate how new concepts and approaches will be implemented, and how they may differ from more traditional safeguards approaches.

Development of data analysis tool for combat system integration

Directory of Open Access Journals (Sweden)

Seung-Chun Shin

2013-03-01

Full Text Available System integration is an important element for the construction of naval combat ships. In particular, because impeccable combat system integration together with the sensors and weapons can ensure the combat capability and survivability of the ship, the integrated performance of the combat system should be verified and validated whether or not it fulfills the requirements of the end user. In order to conduct systematic verification and validation, a data analysis tool is requisite. This paper suggests the Data Extraction, Recording and Analysis Tool (DERAT for the data analysis of the integrated performance of the combat system, including the functional definition, architecture and effectiveness of the DERAT by presenting the test results.

Using Formal Concept Analysis to Create Pathways through Museum Collections

DEFF Research Database (Denmark)

Wray, Tim; Eklund, Peter

2014-01-01

This paper presents A Place for Art - an iPad app that allows users to explore an art collection via semantically linked pathways that are generated using Formal Concept Analysis. The app embraces the information seeking approach of exploration and is based on the idea that showing context...... and relationships among objects in a museum collection augments an interpretive experience. The fundamental interaction metaphor inherent in A Place for Art relies on Formal Concept Analysis so the interface has embedded within it the semantic clustering features of machine learning in artificial intelligence....

Thermodynamics of metabolic pathways for penicillin production: Analysis of thermodynamic feasibility and free energy changes during fed-batch cultivation

DEFF Research Database (Denmark)

Pissarra, P.D.; Nielsen, Jens Bredal

1997-01-01

This paper describes the thermodynamic analysis of pathways related to penicillin production in Penicillium chrysogenum. First a thermodynamic feasibility analysis is performed of the L-lysine pathway of which one of the precursors for penicillin biosynthesis (alpha-aminoadipic acid......) is an intermediate. It is found that the L-lysine pathway in P. chrysogenum is thermodynamically feasible and that the calculated standard Gibbs free energy values of the two enzymes controlling the pathway flux indicate that they operate far from equilibrium. It is therefore proposed that the regulation of alpha......-aminoadipate reductase by lysine is important to maintain a high concentration of alpha-aminoadipate in order to direct the carbon flux to penicillin production. Secondly the changes in Gibbs free energy in the penicillin biosynthetic pathway during fed-batch cultivation were studied. The analysis showed that all...

Integrative and comparative genomics analysis of early hepatocellular carcinoma differentiated from liver regeneration in young and old

Directory of Open Access Journals (Sweden)

Ozand Pinar T

2010-06-01

Full Text Available Abstract Background Hepatocellular carcinoma (HCC is the third-leading cause of cancer-related deaths worldwide. It is often diagnosed at an advanced stage, and hence typically has a poor prognosis. To identify distinct molecular mechanisms for early HCC we developed a rat model of liver regeneration post-hepatectomy, as well as liver cells undergoing malignant transformation and compared them to normal liver using a microarray approach. Subsequently, we performed cross-species comparative analysis coupled with copy number alterations (CNA of independent early human HCC microarray studies to facilitate the identification of critical regulatory modules conserved across species. Results We identified 35 signature genes conserved across species, and shared among different types of early human HCCs. Over 70% of signature genes were cancer-related, and more than 50% of the conserved genes were mapped to human genomic CNA regions. Functional annotation revealed genes already implicated in HCC, as well as novel genes which were not previously reported in liver tumors. A subset of differentially expressed genes was validated using quantitative RT-PCR. Concordance was also confirmed for a significant number of genes and pathways in five independent validation microarray datasets. Our results indicated alterations in a number of cancer related pathways, including p53, p38 MAPK, ERK/MAPK, PI3K/AKT, and TGF-β signaling pathways, and potential critical regulatory role of MYC, ERBB2, HNF4A, and SMAD3 for early HCC transformation. Conclusions The integrative analysis of transcriptional deregulation, genomic CNA and comparative cross species analysis brings new insights into the molecular profile of early hepatoma formation. This approach may lead to robust biomarkers for the detection of early human HCC.

Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis

Directory of Open Access Journals (Sweden)

Xiaowen Tan

2017-01-01

Full Text Available Background. Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. Methods. Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO, including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs were analyzed. Results. 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. Conclusion. The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.

Integrative pathway dissection of molecular mechanisms of moxLDL-induced vascular smooth muscle phenotype transformation

Directory of Open Access Journals (Sweden)

Karagiannis George S

2013-01-01

Full Text Available Abstract Background Atherosclerosis (AT is a chronic inflammatory disease characterized by the accumulation of inflammatory cells, lipoproteins and fibrous tissue in the walls of arteries. AT is the primary cause of heart attacks and stroke and is the leading cause of death in Western countries. To date, the pathogenesis of AT is not well-defined. Studies have shown that the dedifferentiation of contractile and quiescent vascular smooth muscle cells (SMC to the proliferative, migratory and synthetic phenotype in the intima is pivotal for the onset and progression of AT. To further delineate the mechanisms underlying the pathogenesis of AT, we analyzed the early molecular pathways and networks involved in the SMC phenotype transformation. Methods Quiescent human coronary artery SMCs were treated with minimally-oxidized LDL (moxLDL, for 3 hours and 21 hours, respectively. Transcriptomic data was generated for both time-points using microarrays and was subjected to pathway analysis using Gene Set Enrichment Analysis, GeneMANIA and Ingenuity software tools. Gene expression heat maps and pathways enriched in differentially expressed genes were compared to identify functional biological themes to elucidate early and late molecular mechanisms of moxLDL-induced SMC dedifferentiation. Results Differentially expressed genes were found to be enriched in cholesterol biosynthesis, inflammatory cytokines, chemokines, growth factors, cell cycle control and myogenic contraction themes. These pathways are consistent with inflammatory responses, cell proliferation, migration and ECM production, which are characteristic of SMC dedifferentiation. Furthermore, up-regulation of cholesterol synthesis and dysregulation of cholesterol metabolism was observed in moxLDL-induced SMC. These observations are consistent with the accumulation of cholesterol and oxidized cholesterol esters, which induce proinflammatory reactions during atherogenesis. Our data implicate for the

Analysis Method for Integrating Components of Product

Energy Technology Data Exchange (ETDEWEB)

Choi, Jun Ho [Inzest Co. Ltd, Seoul (Korea, Republic of); Lee, Kun Sang [Kookmin Univ., Seoul (Korea, Republic of)

2017-04-15

This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.

Analysis Method for Integrating Components of Product

International Nuclear Information System (INIS)

Choi, Jun Ho; Lee, Kun Sang

2017-01-01

This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.

Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

Science.gov (United States)

Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M

2012-11-15

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

MetaPathways v2.5: quantitative functional, taxonomic and usability improvements.

Science.gov (United States)

Konwar, Kishori M; Hanson, Niels W; Bhatia, Maya P; Kim, Dongjae; Wu, Shang-Ju; Hahn, Aria S; Morgan-Lang, Connor; Cheung, Hiu Kan; Hallam, Steven J

2015-10-15

Next-generation sequencing is producing vast amounts of sequence information from natural and engineered ecosystems. Although this data deluge has an enormous potential to transform our lives, knowledge creation and translation need software applications that scale with increasing data processing and analysis requirements. Here, we present improvements to MetaPathways, an annotation and analysis pipeline for environmental sequence information that expedites this transformation. We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure. Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications. Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database. MetaPathways v2.5 is available on GitHub: http://github.com/hallamlab/metapathways2. shallam@mail.ubc.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Life cycle analysis of transportation fuel pathways

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-02-24

The purpose of this work is to improve the understanding of the concept of life cycle analysis (LCA) of transportation fuels and some of its pertinent issues among non-technical people, senior managers, and policy makers. This work should provide some guidance to nations considering LCA-based policies and to people who are affected by existing policies or those being developed. While the concept of employing LCA to evaluate fuel options is simple and straightforward, the act of putting the concept into practice is complex and fraught with issues. Policy makers need to understand the limitations inherent in carrying out LCA work for transportation fuel systems. For many systems, even those that have been employed for a 100 years, there is a lack of sound data on the performance of those systems. Comparisons between systems should ideally be made using the same tool, so that differences caused by system boundaries, allocation processes, and temporal issues can be minimized (although probably not eliminated). Comparing the results for fuel pathway 1 from tool A to those of fuel system 2 from tool B introduces significant uncertainty into the results. There is also the question of the scale of system changes. LCA will give more reliable estimates when it is used to examine small changes in transportation fuel pathways than when used to estimate large scale changes that replace current pathways with completely new pathways. Some LCA tools have been developed recently primarily for regulatory purposes. These tools may deviate from ISO principles in order to facilitate simplicity and ease of use. In a regulatory environment, simplicity and ease of use are worthy objectives and in most cases there is nothing inherently wrong with this approach, particularly for assessing relative performance. However, the results of these tools should not be confused with, or compared to, the results that are obtained from a more complex and rigorous ISO compliant LCA. It should be

The Notch ligand Delta-like 1 integrates inputs from TGFbeta/Activin and Wnt pathways

Energy Technology Data Exchange (ETDEWEB)

Bordonaro, Michael, E-mail: mbordonaro@tcmedc.org; Tewari, Shruti, E-mail: stewari@tcmedc.org; Atamna, Wafa, E-mail: watamna@tcmedc.org; Lazarova, Darina L., E-mail: dlazarova@tcmedc.org

2011-06-10

Unlike the well-characterized nuclear function of the Notch intracellular domain, it has been difficult to identify a nuclear role for the ligands of Notch. Here we provide evidence for the nuclear function of the Notch ligand Delta-like 1 in colon cancer (CC) cells exposed to butyrate. We demonstrate that the intracellular domain of Delta-like 1 (Dll1icd) augments the activity of Wnt signaling-dependent reporters and that of the promoter of the connective tissue growth factor (CTGF) gene. Data suggest that Dll1icd upregulates CTGF promoter activity through both direct and indirect mechanisms. The direct mechanism is supported by co-immunoprecipitation of endogenous Smad2/3 proteins and Dll1 and by chromatin immunoprecipitation analyses that revealed the occupancy of Dll1icd on CTGF promoter sequences containing a Smad binding element. The indirect upregulation of CTGF expression by Dll1 is likely due to the ability of Dll1icd to increase Wnt signaling, a pathway that targets CTGF. CTGF expression is induced in butyrate-treated CC cells and results from clonal growth assays support a role for CTGF in the cell growth-suppressive role of butyrate. In conclusion, integration of the Notch, Wnt, and TGFbeta/Activin signaling pathways is in part mediated by the interactions of Dll1 with Smad2/3 and Tcf4.

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

Science.gov (United States)

He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

2017-01-01

The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

Directory of Open Access Journals (Sweden)

Tilton Susan C

2012-11-01

Full Text Available Abstract Background MicroRNAs (miRNAs are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

Science.gov (United States)

2012-01-01

Background MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis

Techno-economic analysis of biofuel production considering logistic configurations.

Science.gov (United States)

Li, Qi; Hu, Guiping

2016-04-01

In the study, a techno-economic analysis method considering logistic configurations is proposed. The economic feasibility of a low temperature biomass gasification pathway and an integrated pathway with fast pyrolysis and bio-oil gasification are evaluated and compared with the proposed method in Iowa. The results show that both pathways are profitable, biomass gasification pathway could achieve an Internal Rate of Return (IRR) of 10.00% by building a single biorefinery and integrated bio-oil gasification pathway could achieve an IRR of 3.32% by applying decentralized supply chain structure. A Monte-Carlo simulation considering interactions among parameters is also proposed and conducted, which indicates that both pathways are at high risk currently. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assembly of inflammation-related genes for pathway-focused genetic analysis.

Directory of Open Access Journals (Sweden)

Matthew J Loza

2007-10-01

Full Text Available Recent identifications of associations between novel variants in inflammation-related genes and several common diseases emphasize the need for systematic evaluations of these genes in disease susceptibility. Considering that many genes are involved in the complex inflammation responses and many genetic variants in these genes have the potential to alter the functions and expression of these genes, we assembled a list of key inflammation-related genes to facilitate the identification of genetic associations of diseases with an inflammation-related etiology. We first reviewed various phases of inflammation responses, including the development of immune cells, sensing of danger, influx of cells to sites of insult, activation and functional responses of immune and non-immune cells, and resolution of the immune response. Assisted by the Ingenuity Pathway Analysis, we then identified 17 functional sub-pathways that are involved in one or multiple phases. This organization would greatly increase the chance of detecting gene-gene interactions by hierarchical clustering of genes with their functional closeness in a pathway. Finally, as an example application, we have developed tagging single nucleotide polymorphism (tSNP arrays for populations of European and African descent to capture all the common variants of these key inflammation-related genes. Assays of these tSNPs have been designed and assembled into two Affymetrix ParAllele customized chips, one each for European (12,011 SNPs and African (21,542 SNPs populations. These tSNPs have greater coverage for these inflammation-related genes compared to the existing genome-wide arrays, particularly in the African population. These tSNP arrays can facilitate systematic evaluation of inflammation pathways in disease susceptibility. For additional applications, other genotyping platforms could also be employed. For existing genome-wide association data, this list of key inflammation-related genes and

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

Science.gov (United States)

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes.

Science.gov (United States)

Li, Qike; Schissler, A Grant; Gardeux, Vincent; Achour, Ikbel; Kenost, Colleen; Berghout, Joanne; Li, Haiquan; Zhang, Hao Helen; Lussier, Yves A

2017-05-24

Transcriptome analytic tools are commonly used across patient cohorts to develop drugs and predict clinical outcomes. However, as precision medicine pursues more accurate and individualized treatment decisions, these methods are not designed to address single-patient transcriptome analyses. We previously developed and validated the N-of-1-pathways framework using two methods, Wilcoxon and Mahalanobis Distance (MD), for personal transcriptome analysis derived from a pair of samples of a single patient. Although, both methods uncover concordantly dysregulated pathways, they are not designed to detect dysregulated pathways with up- and down-regulated genes (bidirectional dysregulation) that are ubiquitous in biological systems. We developed N-of-1-pathways MixEnrich, a mixture model followed by a gene set enrichment test, to uncover bidirectional and concordantly dysregulated pathways one patient at a time. We assess its accuracy in a comprehensive simulation study and in a RNA-Seq data analysis of head and neck squamous cell carcinomas (HNSCCs). In presence of bidirectionally dysregulated genes in the pathway or in presence of high background noise, MixEnrich substantially outperforms previous single-subject transcriptome analysis methods, both in the simulation study and the HNSCCs data analysis (ROC Curves; higher true positive rates; lower false positive rates). Bidirectional and concordant dysregulated pathways uncovered by MixEnrich in each patient largely overlapped with the quasi-gold standard compared to other single-subject and cohort-based transcriptome analyses. The greater performance of MixEnrich presents an advantage over previous methods to meet the promise of providing accurate personal transcriptome analysis to support precision medicine at point of care.

Comprehensive analysis of schizophrenia-associated loci highlights ion channel pathways and biologically plausible candidate causal genes

DEFF Research Database (Denmark)

Pers, Tune H; Timshel, Pascal; Ripke, Stephan

2016-01-01

Over 100 associated genetic loci have been robustly associated with schizophrenia. Gene prioritization and pathway analysis have focused on a priori hypotheses and thus may have been unduly influenced by prior assumptions and missed important causal genes and pathways. Using a data-driven approac...

CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures.

Science.gov (United States)

Chovancova, Eva; Pavelka, Antonin; Benes, Petr; Strnad, Ondrej; Brezovsky, Jan; Kozlikova, Barbora; Gora, Artur; Sustr, Vilem; Klvana, Martin; Medek, Petr; Biedermannova, Lada; Sochor, Jiri; Damborsky, Jiri

2012-01-01

Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures.

Directory of Open Access Journals (Sweden)

Eva Chovancova

Full Text Available Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic Protein Structures

Science.gov (United States)

Strnad, Ondrej; Brezovsky, Jan; Kozlikova, Barbora; Gora, Artur; Sustr, Vilem; Klvana, Martin; Medek, Petr; Biedermannova, Lada; Sochor, Jiri; Damborsky, Jiri

2012-01-01

Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz. PMID:23093919

Well-to-wheels analysis of fast pyrolysis pathways with the GREET model.

Energy Technology Data Exchange (ETDEWEB)

Han, J.; Elgowainy, A.; Palou-Rivera, I.; Dunn, J.B.; Wang, M.Q. (Energy Systems)

2011-12-01

The pyrolysis of biomass can help produce liquid transportation fuels with properties similar to those of petroleum gasoline and diesel fuel. Argonne National Laboratory conducted a life-cycle (i.e., well-to-wheels [WTW]) analysis of various pyrolysis pathways by expanding and employing the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The WTW energy use and greenhouse gas (GHG) emissions from the pyrolysis pathways were compared with those from the baseline petroleum gasoline and diesel pathways. Various pyrolysis pathway scenarios with a wide variety of possible hydrogen sources, liquid fuel yields, and co-product application and treatment methods were considered. At one extreme, when hydrogen is produced from natural gas and when bio-char is used for process energy needs, the pyrolysis-based liquid fuel yield is high (32% of the dry mass of biomass input). The reductions in WTW fossil energy use and GHG emissions relative to those that occur when baseline petroleum fuels are used, however, is modest, at 50% and 51%, respectively, on a per unit of fuel energy basis. At the other extreme, when hydrogen is produced internally via reforming of pyrolysis oil and when bio-char is sequestered in soil applications, the pyrolysis-based liquid fuel yield is low (15% of the dry mass of biomass input), but the reductions in WTW fossil energy use and GHG emissions are large, at 79% and 96%, respectively, relative to those that occur when baseline petroleum fuels are used. The petroleum energy use in all scenarios was restricted to biomass collection and transportation activities, which resulted in a reduction in WTW petroleum energy use of 92-95% relative to that found when baseline petroleum fuels are used. Internal hydrogen production (i.e., via reforming of pyrolysis oil) significantly reduces fossil fuel use and GHG emissions because the hydrogen from fuel gas or pyrolysis oil (renewable sources) displaces that from fossil fuel

An integrated acquisition, display, and analysis system

International Nuclear Information System (INIS)

Ahmad, T.; Huckins, R.J.

1987-01-01

The design goal of the ND9900/Genuie was to integrate a high performance data acquisition and display subsystem with a state-of-the-art 32-bit supermicrocomputer. This was achieved by integrating a Digital Equipment Corporation MicroVAX II CPU board with acquisition and display controllers via the Q-bus. The result is a tightly coupled processing and analysis system for Pulse Height Analysis and other applications. The system architecture supports distributed processing, so that acquisition and display functions are semi-autonomous, making the VAX concurrently available for applications programs

NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs.

Directory of Open Access Journals (Sweden)

Elize A Shirdel

2011-02-01

Full Text Available MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP.mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05, suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001, to be more studied (p<0.0002, and to have higher degree in the KEGG cancer pathway (p<0.0001, compared to intra-pathway microRNAs.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

Updates to the Corn Ethanol Pathway and Development of an Integrated Corn and Corn Stover Ethanol Pathway in the GREET™ Model

Energy Technology Data Exchange (ETDEWEB)

Wang, Zhichao [Argonne National Lab. (ANL), Argonne, IL (United States). Energy Systems Division; Dunn, Jennifer B. [Argonne National Lab. (ANL), Argonne, IL (United States). Energy Systems Division; Wang, Michael Q. [Argonne National Lab. (ANL), Argonne, IL (United States). Energy Systems Division

2014-09-01

Corn ethanol, a first-generation biofuel, is the predominant biofuel in the United States. In 2013, the total U.S. ethanol fuel production was 13.3 billion gallons, over 95% of which was produced from corn (RFA, 2014). The 2013 total renewable fuel mandate was 16.6 billion gallons according to the Energy Independence and Security Act (EISA) (U.S. Congress, 2007). Furthermore, until 2020, corn ethanol will make up a large portion of the renewable fuel volume mandated by Renewable Fuels Standard (RFS2). For the GREET1_2014 release, the corn ethanol pathway was subject to updates reflecting changes in corn agriculture and at corn ethanol plants. In the latter case, we especially focused on the incorporation of corn oil as a corn ethanol plant co-product. Section 2 covers these updates. In addition, GREET now includes options to integrate corn grain and corn stover ethanol production on the field and at the biorefinery. These changes are the focus of Section 3.

Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA).

Science.gov (United States)

Tollefsen, Knut Erik; Scholz, Stefan; Cronin, Mark T; Edwards, Stephen W; de Knecht, Joop; Crofton, Kevin; Garcia-Reyero, Natalia; Hartung, Thomas; Worth, Andrew; Patlewicz, Grace

2014-12-01

Chemical regulation is challenged by the large number of chemicals requiring assessment for potential human health and environmental impacts. Current approaches are too resource intensive in terms of time, money and animal use to evaluate all chemicals under development or already on the market. The need for timely and robust decision making demands that regulatory toxicity testing becomes more cost-effective and efficient. One way to realize this goal is by being more strategic in directing testing resources; focusing on chemicals of highest concern, limiting testing to the most probable hazards, or targeting the most vulnerable species. Hypothesis driven Integrated Approaches to Testing and Assessment (IATA) have been proposed as practical solutions to such strategic testing. In parallel, the development of the Adverse Outcome Pathway (AOP) framework, which provides information on the causal links between a molecular initiating event (MIE), intermediate key events (KEs) and an adverse outcome (AO) of regulatory concern, offers the biological context to facilitate development of IATA for regulatory decision making. This manuscript summarizes discussions at the Workshop entitled "Advancing AOPs for Integrated Toxicology and Regulatory Applications" with particular focus on the role AOPs play in informing the development of IATA for different regulatory purposes. Copyright © 2014 Elsevier Inc. All rights reserved.

Intrauterine Growth Restriction Programs the Hypothalamus of Adult Male Rats: Integrated Analysis of Proteomic and Metabolomic Data.

Science.gov (United States)

Pedroso, Amanda P; Souza, Adriana P; Dornellas, Ana P S; Oyama, Lila M; Nascimento, Cláudia M O; Santos, Gianni M S; Rosa, José C; Bertolla, Ricardo P; Klawitter, Jelena; Christians, Uwe; Tashima, Alexandre K; Ribeiro, Eliane B

2017-04-07

Programming of hypothalamic functions regulating energy homeostasis may play a role in intrauterine growth restriction (IUGR)-induced adulthood obesity. The present study investigated the effects of IUGR on the hypothalamus proteome and metabolome of adult rats submitted to 50% protein-energy restriction throughout pregnancy. Proteomic and metabolomic analyzes were performed by data independent acquisition mass spectrometry and multiple reaction monitoring, respectively. At age 4 months, the restricted rats showed elevated adiposity, increased leptin and signs of insulin resistance. 1356 proteins were identified and 348 quantified while 127 metabolites were quantified. The restricted hypothalamus showed down-regulation of 36 proteins and 5 metabolites and up-regulation of 21 proteins and 9 metabolites. Integrated pathway analysis of the proteomics and metabolomics data indicated impairment of hypothalamic glucose metabolism, increased flux through the hexosamine pathway, deregulation of TCA cycle and the respiratory chain, and alterations in glutathione metabolism. The data suggest IUGR modulation of energy metabolism and redox homeostasis in the hypothalamus of male adult rats. The present results indicated deleterious consequences of IUGR on hypothalamic pathways involved in pivotal physiological functions. These results provide guidance for future mechanistic studies assessing the role of intrauterine malnutrition in the development of metabolic diseases later in life.

ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

Science.gov (United States)

Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing

2011-07-01

Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

PHIDIAS- Pathogen Host Interaction Data Integration and Analysis

Indian Academy of Sciences (India)

PHIDIAS- Pathogen Host Interaction Data Integration and Analysis- allows searching of integrated genome sequences, conserved domains and gene expressions data related to pathogen host interactions in high priority agents for public health and security ...

Potential barriers and facilitators for implementation of an integrated care pathway for hearing-impaired persons: an exploratory survey among patients and professionals

Directory of Open Access Journals (Sweden)

Verschuure Hans

2007-04-01

Full Text Available Abstract Background Because of the increasing costs and anticipated shortage of Ear Nose and Throat (ENT specialists in the care for hearing-impaired persons, an integrated care pathway that includes direct hearing aid provision was developed. While this direct pathway is still under investigation, in a survey we examined expectations and potential barriers and facilitators towards this direct pathway, of patients and professionals involved in the pathway. Methods Two study populations were assessed: members of the health professions involved in the care pathway for hearing-impaired persons (general practitioners (GPs, hearing aid dispensers, ENT-specialists and clinical audiologists and persons with hearing complaints. We developed a comprehensive semi-structured questionnaire for the professionals, regarding expectations, barriers, facilitators and conditions for implementation. We developed two questionnaires for persons with hearing complaints, both regarding evaluations and preferences, and administered them after they had experienced two key elements of the direct pathway: the triage and the hearing aid fitting. Results On average GPs and hearing aid dispensers had positive expectations towards the direct pathway, while ENT-specialists and clinical audiologists had negative expectations. Professionals stated both barriers and facilitators towards the direct pathway. Most professionals either supported implementation of the direct pathway, provided that a number of conditions were satisfied, or did not support implementation, unless roughly the same conditions were satisfied. Professionals generally agreed on which conditions need to be satisfied. Persons with hearing complaints evaluated the present referral pathway and the new direct pathway equally. Many, especially older, participants stated however that they would still visit the GP and ENT-specialist, even when this would not be necessary for reimbursement of the hearing aid, and

A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways

Science.gov (United States)

Yang, Yunlai; Arouri, Khaled

2016-03-01

A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways.

Science.gov (United States)

Yang, Yunlai; Arouri, Khaled

2016-03-11

A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

Understanding alternative fluxes/effluxes through comparative metabolic pathway analysis of phylum actinobacteria using a simplified approach.

Science.gov (United States)

Verma, Mansi; Lal, Devi; Saxena, Anjali; Anand, Shailly; Kaur, Jasvinder; Kaur, Jaspreet; Lal, Rup

2013-12-01

Actinobacteria are known for their diverse metabolism and physiology. Some are dreadful human pathogens whereas some constitute the natural flora for human gut. Therefore, the understanding of metabolic pathways is a key feature for targeting the pathogenic bacteria without disturbing the symbiotic ones. A big challenge faced today is multiple drug resistance by Mycobacterium and other pathogens that utilize alternative fluxes/effluxes. With the availability of genome sequence, it is now feasible to conduct the comparative in silico analysis. Here we present a simplified approach to compare metabolic pathways so that the species specific enzyme may be traced and engineered for future therapeutics. The analyses of four key carbohydrate metabolic pathways, i.e., glycolysis, pyruvate metabolism, tri carboxylic acid cycle and pentose phosphate pathway suggest the presence of alternative fluxes. It was found that the upper pathway of glycolysis was highly variable in the actinobacterial genomes whereas lower glycolytic pathway was highly conserved. Likewise, pentose phosphate pathway was well conserved in contradiction to TCA cycle, which was found to be incomplete in majority of actinobacteria. The clustering based on presence and absence of genes of these metabolic pathways clearly revealed that members of different genera shared identical pathways and, therefore, provided an easy method to identify the metabolic similarities/differences between pathogenic and symbiotic organisms. The analyses could identify isoenzymes and some key enzymes that were found to be missing in some pathogenic actinobacteria. The present work defines a simple approach to explore the effluxes in four metabolic pathways within the phylum actinobacteria. The analysis clearly reflects that actinobacteria exhibit diverse routes for metabolizing substrates. The pathway comparison can help in finding the enzymes that can be used as drug targets for pathogens without effecting symbiotic organisms

IIS--Integrated Interactome System: a web-based platform for the annotation, analysis and visualization of protein-metabolite-gene-drug interactions by integrating a variety of data sources and tools.

Science.gov (United States)

Carazzolle, Marcelo Falsarella; de Carvalho, Lucas Miguel; Slepicka, Hugo Henrique; Vidal, Ramon Oliveira; Pereira, Gonçalo Amarante Guimarães; Kobarg, Jörg; Meirelles, Gabriela Vaz

2014-01-01

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two

Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles.

Directory of Open Access Journals (Sweden)

Arsen Arakelyan

Full Text Available Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms.Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies.The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune

Computational Chemical Synthesis Analysis and Pathway Design

Directory of Open Access Journals (Sweden)

Fan Feng

2018-06-01

Full Text Available With the idea of retrosynthetic analysis, which was raised in the 1960s, chemical synthesis analysis and pathway design have been transformed from a complex problem to a regular process of structural simplification. This review aims to summarize the developments of computer-assisted synthetic analysis and design in recent years, and how machine-learning algorithms contributed to them. LHASA system started the pioneering work of designing semi-empirical reaction modes in computers, with its following rule-based and network-searching work not only expanding the databases, but also building new approaches to indicating reaction rules. Programs like ARChem Route Designer replaced hand-coded reaction modes with automatically-extracted rules, and programs like Chematica changed traditional designing into network searching. Afterward, with the help of machine learning, two-step models which combine reaction rules and statistical methods became the main stream. Recently, fully data-driven learning methods using deep neural networks which even do not require any prior knowledge, were applied into this field. Up to now, however, these methods still cannot replace experienced human organic chemists due to their relatively low accuracies. Future new algorithms with the aid of powerful computational hardware will make this topic promising and with good prospects.

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

Science.gov (United States)

Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

Abel integral equations analysis and applications

CERN Document Server

Gorenflo, Rudolf

1991-01-01

In many fields of application of mathematics, progress is crucially dependent on the good flow of information between (i) theoretical mathematicians looking for applications, (ii) mathematicians working in applications in need of theory, and (iii) scientists and engineers applying mathematical models and methods. The intention of this book is to stimulate this flow of information. In the first three chapters (accessible to third year students of mathematics and physics and to mathematically interested engineers) applications of Abel integral equations are surveyed broadly including determination of potentials, stereology, seismic travel times, spectroscopy, optical fibres. In subsequent chapters (requiring some background in functional analysis) mapping properties of Abel integral operators and their relation to other integral transforms in various function spaces are investi- gated, questions of existence and uniqueness of solutions of linear and nonlinear Abel integral equations are treated, and for equatio...

Integrated analysis of genetic data with R

Directory of Open Access Journals (Sweden)

Zhao Jing

2006-01-01

Full Text Available Abstract Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially when genetic data are analysed in conjunction with a large number of covariates. Here, R http://www.r-project.org, a free, flexible and platform-independent environment for statistical modelling and graphics is explored as an integrated system for genetic data analysis. An overview of some packages currently available for analysis of genetic data is given. This is followed by examples of package development and practical applications. With clear advantages in data management, graphics, statistical analysis, programming, internet capability and use of available codes, it is a feasible, although challenging, task to develop it into an integrated platform for genetic analysis; this will require the joint efforts of many researchers.

Integrated care: a comprehensive bibliometric analysis and literature review

Directory of Open Access Journals (Sweden)

Xiaowei Sun

2014-06-01

Full Text Available Introduction: Integrated care could not only fix up fragmented health care but also improve the continuity of care and the quality of life. Despite the volume and variety of publications, little is known about how ‘integrated care’ has developed. There is a need for a systematic bibliometric analysis on studying the important features of the integrated care literature.Aim: To investigate the growth pattern, core journals and jurisdictions and identify the key research domains of integrated care.Methods: We searched Medline/PubMed using the search strategy ‘(delivery of health care, integrated [MeSH Terms] OR integrated care [Title/Abstract]’ without time and language limits. Second, we extracted the publishing year, journals, jurisdictions and keywords of the retrieved articles. Finally, descriptive statistical analysis by the Bibliographic Item Co-occurrence Matrix Builder and hierarchical clustering by SPSS were used.Results: As many as 9090 articles were retrieved. Results included: (1 the cumulative numbers of the publications on integrated care rose perpendicularly after 1993; (2 all documents were recorded by 1646 kinds of journals. There were 28 core journals; (3 the USA is the predominant publishing country; and (4 there are six key domains including: the definition/models of integrated care, interdisciplinary patient care team, disease management for chronically ill patients, types of health care organizations and policy, information system integration and legislation/jurisprudence.Discussion and conclusion: Integrated care literature has been most evident in developed countries. International Journal of Integrated Care is highly recommended in this research area. The bibliometric analysis and identification of publication hotspots provides researchers and practitioners with core target journals, as well as an overview of the field for further research in integrated care.

Hanford Site Composite Analysis Technical Approach Description: Groundwater Pathway Dose Calculation.

Energy Technology Data Exchange (ETDEWEB)

Morgans, D. L. [CH2M Hill Plateau Remediation Company, Richland, WA (United States); Lindberg, S. L. [Intera Inc., Austin, TX (United States)

2017-09-20

The purpose of this technical approach document (TAD) is to document the assumptions, equations, and methods used to perform the groundwater pathway radiological dose calculations for the revised Hanford Site Composite Analysis (CA). DOE M 435.1-1, states, “The composite analysis results shall be used for planning, radiation protection activities, and future use commitments to minimize the likelihood that current low-level waste disposal activities will result in the need for future corrective or remedial actions to adequately protect the public and the environment.”

Bioinformatic Integration of Molecular Networks and Major Pathways Involved in Mice Cochlear and Vestibular Supporting Cells.

Science.gov (United States)

Requena, Teresa; Gallego-Martinez, Alvaro; Lopez-Escamez, Jose A

2018-01-01

Background : Cochlear and vestibular epithelial non-hair cells (ENHCs) are the supporting elements of the cellular architecture in the organ of Corti and the vestibular neuroepithelium in the inner ear. Intercellular and cell-extracellular matrix interactions are essential to prevent an abnormal ion redistribution leading to hearing and vestibular loss. The aim of this study is to define the main pathways and molecular networks in the mouse ENHCs. Methods : We retrieved microarray and RNA-seq datasets from mouse epithelial sensory and non-sensory cells from gEAR portal (http://umgear.org/index.html) and obtained gene expression fold-change between ENHCs and non-epithelial cells (NECs) against HCs for each gene. Differentially expressed genes (DEG) with a log2 fold change between 1 and -1 were discarded. The remaining genes were selected to search for interactions using Ingenuity Pathway Analysis and STRING platform. Specific molecular networks for ENHCs in the cochlea and the vestibular organs were generated and significant pathways were identified. Results : Between 1723 and 1559 DEG were found in the mouse cochlear and vestibular tissues, respectively. Six main pathways showed enrichment in the supporting cells in both tissues: (1) "Inhibition of Matrix Metalloproteases"; (2) "Calcium Transport I"; (3) "Calcium Signaling"; (4) "Leukocyte Extravasation Signaling"; (5) "Signaling by Rho Family GTPases"; and (6) "Axonal Guidance Si". In the mouse cochlea, ENHCs showed a significant enrichment in 18 pathways highlighting "axonal guidance signaling (AGS)" ( p = 4.37 × 10 -8 ) and "RhoGDI Signaling" ( p = 3.31 × 10 -8 ). In the vestibular dataset, there were 20 enriched pathways in ENHCs, the most significant being "Leukocyte Extravasation Signaling" ( p = 8.71 × 10 -6 ), "Signaling by Rho Family GTPases" ( p = 1.20 × 10 -5 ) and "Calcium Signaling" ( p = 1.20 × 10 -5 ). Among the top ranked networks, the most biologically significant network contained the

Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

Science.gov (United States)

Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

2009-02-01

Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

Multi-variant pathway association analysis reveals the importance of genetic determinants of estrogen metabolism in breast and endometrial cancer susceptibility.

Directory of Open Access Journals (Sweden)

Yen Ling Low

2010-07-01

Full Text Available Despite the central role of estrogen exposure in breast and endometrial cancer development and numerous studies of genes in the estrogen metabolic pathway, polymorphisms within the pathway have not been consistently associated with these cancers. We posit that this is due to the complexity of multiple weak genetic effects within the metabolic pathway that can only be effectively detected through multi-variant analysis. We conducted a comprehensive association analysis of the estrogen metabolic pathway by interrogating 239 tagSNPs within 35 genes of the pathway in three tumor samples. The discovery sample consisted of 1,596 breast cancer cases, 719 endometrial cancer cases, and 1,730 controls from Sweden; and the validation sample included 2,245 breast cancer cases and 1,287 controls from Finland. We performed admixture maximum likelihood (AML-based global tests to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three sub-pathways for androgen synthesis, androgen-to-estrogen conversion, and estrogen removal. In the discovery sample, although no single polymorphism was significant after correction for multiple testing, the pathway-based AML global test suggested association with both breast (p(global = 0.034 and endometrial (p(global = 0.052 cancers. Further testing revealed the association to be focused on polymorphisms within the androgen-to-estrogen conversion sub-pathway, for both breast (p(global = 0.008 and endometrial cancer (p(global = 0.014. The sub-pathway association was validated in the Finnish sample of breast cancer (p(global = 0.015. Further tumor subtype analysis demonstrated that the association of the androgen-to-estrogen conversion sub-pathway was confined to postmenopausal women with sporadic estrogen receptor positive tumors (p(global = 0.0003. Gene-based AML analysis suggested CYP19A1 and UGT2B4 to be the major players within the sub-pathway. Our study indicates that the composite

Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer.

Directory of Open Access Journals (Sweden)

Paolo Cossu-Rocca

Full Text Available Triple Negative Breast Cancer (TNBC accounts for 12-24% of all breast carcinomas, and shows worse prognosis compared to other breast cancer subtypes. Molecular studies demonstrated that TNBCs are a heterogeneous group of tumors with different clinical and pathologic features, prognosis, genetic-molecular alterations and treatment responsivity. The PI3K/AKT is a major pathway involved in the regulation of cell survival and proliferation, and is the most frequently altered pathway in breast cancer, apparently with different biologic impact on specific cancer subtypes. The most common genetic abnormality is represented by PIK3CA gene activating mutations, with an overall frequency of 20-40%. The aims of our study were to investigate PIK3CA gene mutations on a large series of TNBC, to perform a wider analysis on genetic alterations involving PI3K/AKT and BRAF/RAS/MAPK pathways and to correlate the results with clinical-pathologic data.PIK3CA mutation analysis was performed by using cobas® PIK3CA Mutation Test. EGFR, AKT1, BRAF, and KRAS genes were analyzed by sequencing. Immunohistochemistry was carried out to identify PTEN loss and to investigate for PI3K/AKT pathways components.PIK3CA mutations were detected in 23.7% of TNBC, whereas no mutations were identified in EGFR, AKT1, BRAF, and KRAS genes. Moreover, we observed PTEN loss in 11.3% of tumors. Deregulation of PI3K/AKT pathways was revealed by consistent activation of pAKT and p-p44/42 MAPK in all PIK3CA mutated TNBC.Our data shows that PIK3CA mutations and PI3K/AKT pathway activation are common events in TNBC. A deeper investigation on specific TNBC genomic abnormalities might be helpful in order to select patients who would benefit from current targeted therapy strategies.

Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer.

Science.gov (United States)

Cossu-Rocca, Paolo; Orrù, Sandra; Muroni, Maria Rosaria; Sanges, Francesca; Sotgiu, Giovanni; Ena, Sara; Pira, Giovanna; Murgia, Luciano; Manca, Alessandra; Uras, Maria Gabriela; Sarobba, Maria Giuseppina; Urru, Silvana; De Miglio, Maria Rosaria

2015-01-01

Triple Negative Breast Cancer (TNBC) accounts for 12-24% of all breast carcinomas, and shows worse prognosis compared to other breast cancer subtypes. Molecular studies demonstrated that TNBCs are a heterogeneous group of tumors with different clinical and pathologic features, prognosis, genetic-molecular alterations and treatment responsivity. The PI3K/AKT is a major pathway involved in the regulation of cell survival and proliferation, and is the most frequently altered pathway in breast cancer, apparently with different biologic impact on specific cancer subtypes. The most common genetic abnormality is represented by PIK3CA gene activating mutations, with an overall frequency of 20-40%. The aims of our study were to investigate PIK3CA gene mutations on a large series of TNBC, to perform a wider analysis on genetic alterations involving PI3K/AKT and BRAF/RAS/MAPK pathways and to correlate the results with clinical-pathologic data. PIK3CA mutation analysis was performed by using cobas® PIK3CA Mutation Test. EGFR, AKT1, BRAF, and KRAS genes were analyzed by sequencing. Immunohistochemistry was carried out to identify PTEN loss and to investigate for PI3K/AKT pathways components. PIK3CA mutations were detected in 23.7% of TNBC, whereas no mutations were identified in EGFR, AKT1, BRAF, and KRAS genes. Moreover, we observed PTEN loss in 11.3% of tumors. Deregulation of PI3K/AKT pathways was revealed by consistent activation of pAKT and p-p44/42 MAPK in all PIK3CA mutated TNBC. Our data shows that PIK3CA mutations and PI3K/AKT pathway activation are common events in TNBC. A deeper investigation on specific TNBC genomic abnormalities might be helpful in order to select patients who would benefit from current targeted therapy strategies.

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes, and Cytokine Signaling Genes in Crohn's Disease

Science.gov (United States)

Carbonetto, Peter; Stephens, Matthew

2013-01-01

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn's disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14

Triple phase boundary specific pathway analysis for quantitative characterization of solid oxide cell electrode microstructure

DEFF Research Database (Denmark)

Jørgensen, Peter Stanley; Ebbehøj, Søren Lyng; Hauch, Anne

2015-01-01

of the pathways through which they can be reached. New methods for performing TPB specific pathway analysis on 3D image data are introduced, analyzing the pathway properties of each TPB site in the electrode structure. The methods seek to provide additional information beyond whether the TPB sites are percolating......The density and percolation of Triple phase boundary sites are important quantities in analyzing microstructures of solid oxide fuel cell electrodes from tomography data. However, these measures do not provide descriptions of the quality of the TPB sites in terms of the length and radius...... or not by also analyzing the pathway length to the TPB sites and the bottleneck radius of the pathway. We show how these methods can be utilized in quantifying and relating the TPB specific results to cell test data of an electrode reduction protocol study for Ni/Scandia-and-Yttria-doped-Zirconia (Ni...

Parallel imaging of Drosophila embryos for quantitative analysis of genetic perturbations of the Ras pathway

Directory of Open Access Journals (Sweden)

Yogesh Goyal

2017-07-01

Full Text Available The Ras pathway patterns the poles of the Drosophila embryo by downregulating the levels and activity of a DNA-binding transcriptional repressor Capicua (Cic. We demonstrate that the spatiotemporal pattern of Cic during this signaling event can be harnessed for functional studies of mutations in the Ras pathway in human diseases. Our approach relies on a new microfluidic device that enables parallel imaging of Cic dynamics in dozens of live embryos. We found that although the pattern of Cic in early embryos is complex, it can be accurately approximated by a product of one spatial profile and one time-dependent amplitude. Analysis of these functions of space and time alone reveals the differential effects of mutations within the Ras pathway. Given the highly conserved nature of Ras-dependent control of Cic, our approach provides new opportunities for functional analysis of multiple sequence variants from developmental abnormalities and cancers.

A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility

DEFF Research Database (Denmark)

Damotte, V; Guillot-Noel, L; Patsopoulos, N A

2014-01-01

adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes...... in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell...... belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted...

Preliminary Integrated Safety Analysis Status Report

International Nuclear Information System (INIS)

Gwyn, D.

2001-01-01

This report provides the status of the potential Monitored Geologic Repository (MGR) Integrated Safety Analysis (EA) by identifying the initial work scope scheduled for completion during the ISA development period, the schedules associated with the tasks identified, safety analysis issues encountered, and a summary of accomplishments during the reporting period. This status covers the period from October 1, 2000 through March 30, 2001

Automated tool for virtual screening and pharmacology-based pathway prediction and analysis

Directory of Open Access Journals (Sweden)

Sugandh Kumar

2017-10-01

Full Text Available The virtual screening is an effective tool for the lead identification in drug discovery. However, there are limited numbers of crystal structures available as compared to the number of biological sequences which makes (Structure Based Drug Discovery SBDD a difficult choice. The current tool is an attempt to automate the protein structure modelling and automatic virtual screening followed by pharmacology-based prediction and analysis. Starting from sequence(s, this tool automates protein structure modelling, binding site identification, automated docking, ligand preparation, post docking analysis and identification of hits in the biological pathways that can be modulated by a group of ligands. This automation helps in the characterization of ligands selectivity and action of ligands on a complex biological molecular network as well as on individual receptor. The judicial combination of the ligands binding different receptors can be used to inhibit selective biological pathways in a disease. This tool also allows the user to systemically investigate network-dependent effects of a drug or drug candidate.

An integrated system for genetic analysis

Directory of Open Access Journals (Sweden)

Duan Xiao

2006-04-01

Full Text Available Abstract Background Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet are easy to use. Description We have developed an Integrated Genotyping System (IGS to meet this need. IGS securely stores, edits and analyses genotype and phenotype data. It stores information about DNA samples, plates, primers, markers and genotypes generated by a genotyping laboratory. Data are structured so that statistical genetic analysis of both case-control and pedigree data is straightforward. Conclusion IGS can model complex phenotypes and contain genotypes from whole genome association studies. The database makes it possible to integrate genetic analysis with data curation. The IGS web site http://bioinformatics.well.ox.ac.uk/project-igs.shtml contains further information.

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways

Directory of Open Access Journals (Sweden)

Q. Wang

Full Text Available Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC based on the functional dependency among pathways. Protein-protein interaction (PPI information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN, where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

Building integrated pathways to independence for diverse biomedical researchers: Project Pathways, the BUILD program at Xavier University of Louisiana.

Science.gov (United States)

Foroozesh, Maryam; Giguette, Marguerite; Morgan, Kathleen; Johanson, Kelly; D'Amour, Gene; Coston, Tiera; Wilkins-Green, Clair

2017-01-01

Xavier University of Louisiana is a historically Black and Catholic university that is nationally recognized for its science, technology, engineering and mathematics (STEM) curricula. Approximately 73% of Xavier's students are African American, and about 77% major in the biomedical sciences. Xavier is a national leader in the number of STEM majors who go on to receive M.D. degrees and Ph.D. degrees in science and engineering. Despite Xavier's advances in this area, African Americans still earn about 7.5% of the Bachelor's degrees, less than 8% of the Master's degrees, and less than 5% of the doctoral degrees conferred in STEM disciplines in the United States. Additionally, although many well-prepared, highly-motivated students are attracted by Xavier's reputation in the sciences, many of these students, though bright and capable, come from underperforming public school systems and receive substandard preparation in STEM disciplines. The purpose of this article is to describe how Xavier works to overcome unequal education backgrounds and socioeconomic challenges to develop student talent through expanding biomedical training opportunities and build on an established reputation in science education. The National Institutes of Health (NIH)/National Institute of General Medical Sciences (NIGMS)-funded BUILD (Building Infrastructure Leading to Diversity) Program at Xavier University of Louisiana, Project Pathways , is a highly-innovative program designed to broaden the career interests of students early on, and to engage them in activities that entice them to continue their education towards biomedical research careers. Project strategies involve a transformation of Xavier's academic and non-academic programs through the redesign, supplementation and integration of academic advising, tutoring, career services, personal counseling, undergraduate research training, faculty research mentoring, and development of new biomedical and research skills courses. The Program also

Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case

International Nuclear Information System (INIS)

Dundulis, Gintautas; Žutautaitė, Inga; Janulionis, Remigijus; Ušpuras, Eugenijus; Rimkevičius, Sigitas; Eid, Mohamed

2016-01-01

In this paper, the authors present an approach as an overall framework for the estimation of the failure probability of pipelines based on: the results of the deterministic-probabilistic structural integrity analysis (taking into account loads, material properties, geometry, boundary conditions, crack size, and defected zone thickness), the corrosion rate, the number of defects and failure data (involved into the model via application of Bayesian method). The proposed approach is applied to estimate the failure probability of a selected part of the Lithuanian natural gas transmission network. The presented approach for the estimation of integrated failure probability is a combination of several different analyses allowing us to obtain: the critical crack's length and depth, the failure probability of the defected zone thickness, dependency of the failure probability on the age of the natural gas transmission pipeline. A model's uncertainty analysis and uncertainty propagation analysis are performed, as well. - Highlights: • Degradation mechanisms of natural gas transmission pipelines. • Fracture mechanic analysis of the pipe with crack. • Stress evaluation of the pipe with critical crack. • Deterministic-probabilistic structural integrity analysis of gas pipeline. • Integrated estimation of pipeline failure probability by Bayesian method.

General Approach to Identifying Potential Targets for Cancer Imaging by Integrated Bioinformatics Analysis of Publicly Available Genomic Profiles

Directory of Open Access Journals (Sweden)

Yongliang Yang

2011-03-01

Full Text Available Molecular imaging has moved to the forefront of drug development and biomedical research. The identification of appropriate imaging targets has become the touchstone for the accurate diagnosis and prognosis of human cancer. Particularly, cell surface- or membrane-bound proteins are attractive imaging targets for their aberrant expression, easily accessible location, and unique biochemical functions in tumor cells. Previously, we published a literature mining of potential targets for our in-house enzyme-mediated cancer imaging and therapy technology. Here we present a simple and integrated bioinformatics analysis approach that assembles a public cancer microarray database with a pathway knowledge base for ascertaining and prioritizing upregulated genes encoding cell surface- or membrane-bound proteins, which could serve imaging targets. As examples, we obtained lists of potential hits for six common and lethal human tumors in the prostate, breast, lung, colon, ovary, and pancreas. As control tests, a number of well-known cancer imaging targets were detected and confirmed by our study. Further, by consulting gene-disease and protein-disease databases, we suggest a number of significantly upregulated genes as promising imaging targets, including cell surface-associated mucin-1, prostate-specific membrane antigen, hepsin, urokinase plasminogen activator receptor, and folate receptors. By integrating pathway analysis, we are able to organize and map “focused” interaction networks derived from significantly dysregulated entity pairs to reflect important cellular functions in disease processes. We provide herein an example of identifying a tumor cell growth and proliferation subnetwork for prostate cancer. This systematic mining approach can be broadly applied to identify imaging or therapeutic targets for other human diseases.

An analysis of 3D particle path integration algorithms

International Nuclear Information System (INIS)

Darmofal, D.L.; Haimes, R.

1996-01-01

Several techniques for the numerical integration of particle paths in steady and unsteady vector (velocity) fields are analyzed. Most of the analysis applies to unsteady vector fields, however, some results apply to steady vector field integration. Multistep, multistage, and some hybrid schemes are considered. It is shown that due to initialization errors, many unsteady particle path integration schemes are limited to third-order accuracy in time. Multistage schemes require at least three times more internal data storage than multistep schemes of equal order. However, for timesteps within the stability bounds, multistage schemes are generally more accurate. A linearized analysis shows that the stability of these integration algorithms are determined by the eigenvalues of the local velocity tensor. Thus, the accuracy and stability of the methods are interpreted with concepts typically used in critical point theory. This paper shows how integration schemes can lead to erroneous classification of critical points when the timestep is finite and fixed. For steady velocity fields, we demonstrate that timesteps outside of the relative stability region can lead to similar integration errors. From this analysis, guidelines for accurate timestep sizing are suggested for both steady and unsteady flows. In particular, using simulation data for the unsteady flow around a tapered cylinder, we show that accurate particle path integration requires timesteps which are at most on the order of the physical timescale of the flow

[The Alliance Programme: an integrated care pathway for patients with schizophrenia].

Science.gov (United States)

Nielsen, Bent; Sigsgaard, Anne; Gregersen, Jane; Meilvang, Bente; Halldorsson, Lene Leth; Christensen, Anders; Kirk, Else; Hansen, Vagn

2008-11-10

Experiences and results of implementation of an integrated care pathway (ICP) for patients with schizophrenia are described. The participants of the ICP were the hospital psychiatry unit, the community mental health team and the social psychiatry unit. The article reviews the collaboration in connection with patient hospitalization and discharge. The study includes 224 patients, who fulfill the ICD 10 criteria for schizophrenia or schizo-affective disorder. The patients were interviewed at admission to and discharge from the Psychiatric Department. During hospitalization, the staff filled in a check list establishing whether the established procedures were complied with in each individual case. The Outpatient Section filled in a similar check list. In addition, information from the local registry concerning the hospitalization pattern during the first 12 months after discharge was obtained. As a result of the ICP, collaboration was stimulated. During the first year disagreement between sectors with regard to the degree of compliance with the introduced procedures during hospitalization was observed (p > 0.05). Disagreement concerning the degree of compliance with procedures at admission was observed throughout the observation period (p > 0.05). Neither frequency of re-hospitalization nor inpatient bed costs were significantly reduced. ICP required considerable resource allocation, and the results of the effort were minimal. The ineffective initiatives were subsequently phased out.

The Cardiopulmonary Effects of Ambient Air Pollution and Mechanistic Pathways: A Comparative Hierarchical Pathway Analysis

Science.gov (United States)

Thomas, Duncan C.; Zhang, Junfeng; Kipen, Howard M.; Rich, David Q.; Zhu, Tong; Huang, Wei; Hu, Min; Wang, Guangfa; Wang, Yuedan; Zhu, Ping; Lu, Shou-En; Ohman-Strickland, Pamela; Diehl, Scott R.; Eckel, Sandrah P.

2014-01-01

Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2–3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system. PMID:25502951

The cardiopulmonary effects of ambient air pollution and mechanistic pathways: a comparative hierarchical pathway analysis.

Directory of Open Access Journals (Sweden)

Ananya Roy

Full Text Available Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001 and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005. These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours and the hemostasis pathway responds gradually over a 2-3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system.

A pathway-based network analysis of hypertension-related genes

Science.gov (United States)

Wang, Huan; Hu, Jing-Bo; Xu, Chuan-Yun; Zhang, De-Hai; Yan, Qian; Xu, Ming; Cao, Ke-Fei; Zhang, Xu-Sheng

2016-02-01

Complex network approach has become an effective way to describe interrelationships among large amounts of biological data, which is especially useful in finding core functions and global behavior of biological systems. Hypertension is a complex disease caused by many reasons including genetic, physiological, psychological and even social factors. In this paper, based on the information of biological pathways, we construct a network model of hypertension-related genes of the salt-sensitive rat to explore the interrelationship between genes. Statistical and topological characteristics show that the network has the small-world but not scale-free property, and exhibits a modular structure, revealing compact and complex connections among these genes. By the threshold of integrated centrality larger than 0.71, seven key hub genes are found: Jun, Rps6kb1, Cycs, Creb312, Cdk4, Actg1 and RT1-Da. These genes should play an important role in hypertension, suggesting that the treatment of hypertension should focus on the combination of drugs on multiple genes.

Integrity Analysis of Damaged Steam Generator Tubes

International Nuclear Information System (INIS)

Stanic, D.

1998-01-01

Variety of degradation mechanisms affecting steam generator tubes makes steam generators as one of the critical components in the nuclear power plants. Depending of their nature, degradation mechanisms cause different types of damages. It requires performance of extensive integrity analysis in order to access various conditions of crack behavior under operating and accidental conditions. Development and application of advanced eddy current techniques for steam generator examination provide good characterization of found damages. Damage characteristics (shape, orientation and dimensions) may be defined and used for further evaluation of damage influence on tube integrity. In comparison with experimental and analytical methods, numerical methods are also efficient tools for integrity assessment. Application of finite element methods provides relatively simple modeling of different type of damages and simulation of various operating conditions. The stress and strain analysis may be performed for elastic and elasto-plastic state with good ability for visual presentation of results. Furthermore, the fracture mechanics parameters may be calculated. Results obtained by numerical analysis supplemented with experimental results are the base for definition of alternative plugging criteria which may significantly reduce the number of plugged tubes. (author)

Boundary conditions for pathways, safety analysis and basic criteria for low-level radiation waste site selection

International Nuclear Information System (INIS)

Saverot, P.

1994-01-01

There are three successive periods in the life of a disposal facility: the operating period, the institutional control period and the unrestricted site access period. The purpose of safety analysis of the disposal facility is to ensure that the radiological impacts for each period in the life of the facility are acceptable under all circumstances. Founded on a deterministic approach, this analysis leads to a determination of the maximum quantity of each radionuclide present in the facility at the beginning of the institutional control period in order for the impacts to be considered acceptable. Safety analysis involves the calculation of the radiological impacts of a given radiological inventory under a selected scenario, from all plausible scenarios of radionuclide migration to the environment in both normal and accident conditions, and taking into account other specified variables. The calculation itself involves an assessment of the quantities of radionuclides that could be released to the environment under the specific scenario selected and following identified pathways, and a determination of the resultant exposure, both internal and external, to the public. An iterative approach is used in the performance of pathways analyses. If the pathways analyses result in unacceptable radiological impacts, either the radiological inventory of the site is reduced or barrier characteristics not previously factored into the analysis are taken into account. New pathways analyses are then performed until the results are within the acceptable range. Once accepted by the safety authorities, the radiological inventory becomes the radiological capacity, which is the approved quantities of specific radionuclides that may be disposed of at the site. The following elaborates on the boundary conditions used in safety analyses and describes the types of pathways analyses performed for a LLW disposal facility

Integrated framework for dynamic safety analysis

International Nuclear Information System (INIS)

Kim, Tae Wan; Karanki, Durga R.

2012-01-01

In the conventional PSA (Probabilistic Safety Assessment), detailed plant simulations by independent thermal hydraulic (TH) codes are used in the development of accident sequence models. Typical accidents in a NPP involve complex interactions among process, safety systems, and operator actions. As independent TH codes do not have the models of operator actions and full safety systems, they cannot literally simulate the integrated and dynamic interactions of process, safety systems, and operator responses. Offline simulation with pre decided states and time delays may not model the accident sequences properly. Moreover, when stochastic variability in responses of accident models is considered, defining all the combinations for simulations will be cumbersome task. To overcome some of these limitations of conventional safety analysis approach, TH models are coupled with the stochastic models in the dynamic event tree (DET) framework, which provides flexibility to model the integrated response due to better communication as all the accident elements are in the same model. The advantages of this framework also include: Realistic modeling in dynamic scenarios, comprehensive results, integrated approach (both deterministic and probabilistic models), and support for HRA (Human Reliability Analysis)

In Silico Analysis of Putrefaction Pathways in Bacteria and Its Implication in Colorectal Cancer

Directory of Open Access Journals (Sweden)

Harrisham Kaur

2017-11-01

Full Text Available Fermentation of undigested proteins in human gastrointestinal tract (gut by the resident microbiota, a process called bacterial putrefaction, can sometimes disrupt the gut homeostasis. In this process, essential amino acids (e.g., histidine, tryptophan, etc. that are required by the host may be utilized by the gut microbes. In addition, some of the products of putrefaction, like ammonia, putrescine, cresol, indole, phenol, etc., have been implicated in the disease pathogenesis of colorectal cancer (CRC. We have investigated bacterial putrefaction pathways that are known to be associated with such metabolites. Results of the comprehensive in silico analysis of the selected putrefaction pathways across bacterial genomes revealed presence of these pathways in limited bacterial groups. Majority of these bacteria are commonly found in human gut. These include Bacillus, Clostridium, Enterobacter, Escherichia, Fusobacterium, Salmonella, etc. Interestingly, while pathogens utilize almost all the analyzed pathways, commensals prefer putrescine and H2S production pathways for metabolizing the undigested proteins. Further, comparison of the putrefaction pathways in the gut microbiomes of healthy, carcinoma and adenoma datasets indicate higher abundances of putrefying bacteria in the carcinoma stage of CRC. The insights obtained from the present study indicate utilization of possible microbiome-based therapies to minimize the adverse effects of gut microbiome in enteric diseases.

Integrative sparse principal component analysis of gene expression data.

Science.gov (United States)

Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

2017-12-01

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

Pathway-based analysis of a melanoma genome-wide association study: analysis of genes related to tumour-immunosuppression.

Directory of Open Access Journals (Sweden)

Nils Schoof

Full Text Available Systemic immunosuppression is a risk factor for melanoma, and sunburn-induced immunosuppression is thought to be causal. Genes in immunosuppression pathways are therefore candidate melanoma-susceptibility genes. If variants within these genes individually have a small effect on disease risk, the association may be undetected in genome-wide association (GWA studies due to low power to reach a high significance level. Pathway-based approaches have been suggested as a method of incorporating a priori knowledge into the analysis of GWA studies. In this study, the association of 1113 single nucleotide polymorphisms (SNPs in 43 genes (39 genomic regions related to immunosuppression have been analysed using a gene-set approach in 1539 melanoma cases and 3917 controls from the GenoMEL consortium GWA study. The association between melanoma susceptibility and the whole set of tumour-immunosuppression genes, and also predefined functional subgroups of genes, was considered. The analysis was based on a measure formed by summing the evidence from the most significant SNP in each gene, and significance was evaluated empirically by case-control label permutation. An association was found between melanoma and the complete set of genes (p(emp=0.002, as well as the subgroups related to the generation of tolerogenic dendritic cells (p(emp=0.006 and secretion of suppressive factors (p(emp=0.0004, thus providing preliminary evidence of involvement of tumour-immunosuppression gene polymorphisms in melanoma susceptibility. The analysis was repeated on a second phase of the GenoMEL study, which showed no evidence of an association. As one of the first attempts to replicate a pathway-level association, our results suggest that low power and heterogeneity may present challenges.