Liu, Yao-Yuan; Harbison, SallyAnn
Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used. Copyright © 2017 Elsevier B.V. All rights reserved.
Genome-Wide Analyses of the NAC Transcription Factor Gene Family in Pepper (Capsicum annuum L.: Chromosome Location, Phylogeny, Structure, Expression Patterns, Cis-Elements in the Promoter, and Interaction Network
Full Text Available The NAM, ATAF1/2, and CUC2 (NAC transcription factors form a large plant-specific gene family, which is involved in the regulation of tissue development in response to biotic and abiotic stress. To date, there have been no comprehensive studies investigating chromosomal location, gene structure, gene phylogeny, conserved motifs, or gene expression of NAC in pepper (Capsicum annuum L.. The recent release of the complete genome sequence of pepper allowed us to perform a genome-wide investigation of Capsicum annuum L. NAC (CaNAC proteins. In the present study, a comprehensive analysis of the CaNAC gene family in pepper was performed, and a total of 104 CaNAC genes were identified. Genome mapping analysis revealed that CaNAC genes were enriched on four chromosomes (chromosomes 1, 2, 3, and 6. In addition, phylogenetic analysis of the NAC domains from pepper, potato, Arabidopsis, and rice showed that CaNAC genes could be clustered into three groups (I, II, and III. Group III, which contained 24 CaNAC genes, was exclusive to the Solanaceae plant family. Gene structure and protein motif analyses showed that these genes were relatively conserved within each subgroup. The number of introns in CaNAC genes varied from 0 to 8, with 83 (78.9% of CaNAC genes containing two or less introns. Promoter analysis confirmed that CaNAC genes are involved in pepper growth, development, and biotic or abiotic stress responses. Further, the expression of 22 selected CaNAC genes in response to seven different biotic and abiotic stresses [salt, heat shock, drought, Phytophthora capsici, abscisic acid, salicylic acid (SA, and methyl jasmonate (MeJA] was evaluated by quantitative RT-PCR to determine their stress-related expression patterns. Several putative stress-responsive CaNAC genes, including CaNAC72 and CaNAC27, which are orthologs of the known stress-responsive Arabidopsis gene ANAC055 and potato gene StNAC30, respectively, were highly regulated by treatment with
Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana
With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment. PMID:28609295
Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana
With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these "big data" analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber's goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment.
Full Text Available With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min clearly illustrate the importance of clubber in the everyday computational biology environment.
Baldi, Pierre; Brunak, Søren
, and medicine will be particularly affected by the new results and the increased understanding of life at the molecular level. Bioinformatics is the development and application of computer methods for analysis, interpretation, and prediction, as well as for the design of experiments. It has emerged...
Full Text Available Abstract Background The spatiotemporal regulation of gene expression largely depends on the presence and absence of cis-regulatory sites in the promoter. In the economically highly important grass family, our knowledge of transcription factor binding sites and transcriptional networks is still very limited. With the completion of the sorghum genome and the available rice genome sequence, comparative promoter analyses now allow genome-scale detection of conserved cis-elements. Results In this study, we identified thousands of phylogenetic footprints conserved between orthologous rice and sorghum upstream regions that are supported by co-expression information derived from three different rice expression data sets. In a complementary approach, cis-motifs were discovered by their highly conserved co-occurrence in syntenic promoter pairs. Sequence conservation and matches to known plant motifs support our findings. Expression similarities of gene pairs positively correlate with the number of motifs that are shared by gene pairs and corroborate the importance of similar promoter architectures for concerted regulation. This strongly suggests that these motifs function in the regulation of transcript levels in rice and, presumably also in sorghum. Conclusion Our work provides the first large-scale collection of cis-elements for rice and sorghum and can serve as a paradigm for cis-element analysis through comparative genomics in grasses in general.
Wang, Pengfei; Zhang, Bing; Duan, Guangcai; Wang, Yingfang; Hong, Lijuan; Wang, Linlin; Guo, Xiangjiao; Xi, Yuanlin; Yang, Haiyan
Clustered regularly interspaced short palindromic repeats (CRISPR) are inheritable genetic elements of a variety of archaea and bacteria and indicative of the bacterial ecological adaptation, conferring acquired immunity against invading foreign nucleic acids. Shigella is an important pathogen for anthroponosis. This study aimed to analyze the features of Shigella CRISPR structure and classify the spacers through bioinformatics approach. Among 107 Shigella, 434 CRISPR structure loci were identified with two to seven loci in different strains. CRISPR-Q1, CRISPR-Q4 and CRISPR-Q5 were widely distributed in Shigella strains. Comparison of the first and last repeats of CRISPR1, CRISPR2 and CRISPR3 revealed several base variants and different stem-loop structures. A total of 259 cas genes were found among these 107 Shigella strains. The cas gene deletions were discovered in 88 strains. However, there is one strain that does not contain cas gene. Intact clusters of cas genes were found in 19 strains. From comprehensive analysis of sequence signature and BLAST and CRISPRTarget score, the 708 spacers were classified into three subtypes: Type I, Type II and Type III. Of them, Type I spacer referred to those linked with one gene segment, Type II spacer linked with two or more different gene segments, and Type III spacer undefined. This study examined the diversity of CRISPR/cas system in Shigella strains, demonstrated the main features of CRISPR structure and spacer classification, which provided critical information for elucidation of the mechanisms of spacer formation and exploration of the role the spacers play in the function of the CRISPR/cas system.
Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T
Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.
Full Text Available Hair follicle cycling can be divided into the following three stages: anagen, catagen, and telogen. The molecular signals that orchestrate the follicular transition between phases are still unknown. To better understand the detailed protein networks controlling this process, proteomics and bioinformatics analyses were performed to construct comparative protein profiles of mouse skin at specific time points (0, 8, and 20 days. Ninety-five differentially expressed protein spots were identified by MALDI-TOF/TOF as 44 proteins, which were found to change during hair follicle cycle transition. Proteomics analysis revealed that these changes in protein expression are involved in Ca2+-regulated biological processes, migration, and regulation of signal transduction, among other processes. Subsequently, three proteins were selected to validate the reliability of expression patterns using western blotting. Cluster analysis revealed three expression patterns, and each pattern correlated with specific cell processes that occur during the hair cycle. Furthermore, bioinformatics analysis indicated that the differentially expressed proteins impacted multiple biological networks, after which detailed functional analyses were performed. Taken together, the above data may provide insight into the three stages of mouse hair follicle morphogenesis and provide a solid basis for potential therapeutic molecular targets for this hair disease.
Jonathan W Snow
Full Text Available In development, lineage-restricted transcription factors simultaneously promote differentiation while repressing alternative fates. Molecular dissection of this process has been challenging as transcription factor loci are regulated by many trans-acting factors functioning through dispersed cis elements. It is not understood whether these elements function collectively to confer transcriptional regulation, or individually to control specific aspects of activation or repression, such as initiation versus maintenance. Here, we have analyzed cis element regulation of the critical hematopoietic factor Gata2, which is expressed in early precursors and repressed as GATA-1 levels rise during terminal differentiation. We engineered mice lacking a single cis element -1.8 kb upstream of the Gata2 transcriptional start site. Although Gata2 is normally repressed in late-stage erythroblasts, the -1.8 kb mutation unexpectedly resulted in reactivated Gata2 transcription, blocked differentiation, and an aberrant lineage-specific gene expression pattern. Our findings demonstrate that the -1.8 kb site selectively maintains repression, confers a specific histone modification pattern and expels RNA Polymerase II from the locus. These studies reveal how an individual cis element establishes a normal developmental program via regulating specific steps in the mechanism by which a critical transcription factor is repressed.
Ben Ayed, Rayda; Ben Hassen, Hanen; Ennouri, Karim; Rebai, Ahmed
The genetic diversity of 22 olive tree cultivars (Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles (average 2.2 per allele). The dendrogram based on cultivar genotypes revealed three clusters consistent with the cultivars classification. Besides, the results obtained with the five SNPs were compared to those obtained with the SSR markers using bioinformatic analyses and by computing a cophenetic correlation coefficient, indicating the usefulness of the UPGMA method for clustering plant genotypes. Based on principal coordinate analysis using a similarity matrix, the first two coordinates, revealed 54.94 % of the total variance. This work provides a more comprehensive explanation of the diversity available in Tunisia olive cultivars, and an important contribution for olive breeding and olive oil authenticity.
Full Text Available Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of ten classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning.
Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics) and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning. PMID:22919594
Deka, Ranjit K.; Brautigam, Chad A.; Goldberg, Martin; Schuck, Peter; Tomchick, Diana R.; Norgard, Michael V. (NIH); (UTSMC)
Treponema pallidum, the bacterial agent of syphilis, is predicted to encode one tripartite ATP-independent periplasmic transporter (TRAP-T). TRAP-Ts typically employ a periplasmic substrate-binding protein (SBP) to deliver the cognate ligand to the transmembrane symporter. Herein, we demonstrate that the genes encoding the putative TRAP-T components from T. pallidum, tp0957 (the SBP), and tp0958 (the symporter), are in an operon with an uncharacterized third gene, tp0956. We determined the crystal structure of recombinant Tp0956; the protein is trimeric and perforated by a pore. Part of Tp0956 forms an assembly similar to those of 'tetratricopeptide repeat' (TPR) motifs. The crystal structure of recombinant Tp0957 was also determined; like the SBPs of other TRAP-Ts, there are two lobes separated by a cleft. In these other SBPs, the cleft binds a negatively charged ligand. However, the cleft of Tp0957 has a strikingly hydrophobic chemical composition, indicating that its ligand may be substantially different and likely hydrophobic. Analytical ultracentrifugation of the recombinant versions of Tp0956 and Tp0957 established that these proteins associate avidly. This unprecedented interaction was confirmed for the native molecules using in vivo cross-linking experiments. Finally, bioinformatic analyses suggested that this transporter exemplifies a new subfamily of TPATs (TPR-protein-associated TRAP-Ts) that require the action of a TPR-containing accessory protein for the periplasmic transport of a potentially hydrophobic ligand(s).
VanDrisse, Chelsey M.; Hentchel, Kristy L.
ABSTRACT Acetylation of small molecules is widespread in nature, and in some cases, cells use this process to detoxify harmful chemicals. Streptomyces species utilize a Gcn5 N-acetyltransferase (GNAT), known as Bar, to acetylate and detoxify a self-produced toxin, phosphinothricin (PPT), a glutamate analogue. Bar homologues, such as MddA from Salmonella enterica, acetylate methionine analogues such as methionine sulfoximine (MSX) and methionine sulfone (MSO), but not PPT, even though Bar homologues are annotated as PPT acetyltransferases. S. enterica was used as a heterologous host to determine whether or not putative PPT acetyltransferases from various sources could acetylate PPT, MSX, and MSO. In vitro and in vivo analyses identified substrates acetylated by putative PPT acetyltransferases from Deinococcus radiodurans (DR_1057 and DR_1182) and Geobacillus kaustophilus (GK0593 and GK2920). In vivo, synthesis of DR_1182, GK0593, and GK2920 blocked the inhibitory effects of PPT, MSX, and MSO. In contrast, DR_1057 did not detoxify any of the above substrates. Results of in vitro studies were consistent with the in vivo results. In addition, phylogenetic analyses were used to predict the functionality of annotated PPT acetyltransferases in Burkholderia xenovorans, Bacillus subtilis, Staphylococcus aureus, Acinetobacter baylyi, and Escherichia coli. IMPORTANCE The work reported here provides an example of the use of a heterologous system for the identification of enzyme function. Many members of this superfamily of proteins do not have a known function, or it has been annotated solely on the basis of sequence homology to previously characterized enzymes. The critical role of Gcn5 N-acetyltransferases (GNATs) in the modulation of central metabolic processes, and in controlling metabolic stress, necessitates approaches that can reveal their physiological role. The combination of in vivo, in vitro, and bioinformatics approaches reported here identified GNATs that can
Menegidio, Fabiano B; Jabes, Daniela L; Costa de Oliveira, Regina; Nunes, Luiz R
This manuscript introduces and describes Dugong, a Docker image based on Ubuntu 16.04, which automates installation of more than 3500 bioinformatics tools (along with their respective libraries and dependencies), in alternative computational environments. The software operates through a user-friendly XFCE4 graphic interface that allows software management and installation by users not fully familiarized with the Linux command line and provides the Jupyter Notebook to assist in the delivery and exchange of consistent and reproducible protocols and results across laboratories, assisting in the development of open science projects. Source code and instructions for local installation are available at https://github.com/DugongBioinformatics, under the MIT open source license. Luiz.firstname.lastname@example.org. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com
Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omi...
Soh, Hyuncheol; Choi, Yongsang; Lee, Taek-Kyun; Yeo, Up-Dong; Han, Kyeongsik; Auh, Chungkyun; Lee, Sukchan
Arabidopsis gene expression microarray (44 K) was used to detect genes highly induced under simulated microgravity stress (SMS). Ten SMS-inducible genes were selected from the microarray data and these 10 genes were found to be abundantly expressed in 3-week-old plants. Nine out of the 10 SMS-inducible genes were also expressed in response to the three abiotic stresses of drought, touch, and wounding in 3-week-old Arabidopsis plants respectively. However, WRKY46 was elevated only in response to SMS. Six other WRKY genes did not respond to SMS. To clarify the characteristics of the genes expressed at high levels in response to SMS, 20 cis-elements in the promoters of the 40 selected genes including the 10 SMS-inducible genes, the 6 WRKY genes, and abiotic stress-inducible genes were analyzed and their spatial positions on each promoter were determined. Four cis-elements (M/T-G-T-P from MYB1AT or TATABOX5, GT1CONSENSUS, TATABOX5, and POLASIG1) showed a unique spatial arrangement in most SMS-inducible genes including WRKY46. Therefore the M/T-G-T-P cis-element patterns identified in the promoter of WRKY46 may play important roles in regulating gene expression in response to SMS. The presences of the cis-element patterns suggest that the order or spatial positioning of certain groups of cis-elements is more important than the existence or numbers of specific cis-elements. Taken together, our data indicate that WRKY46 is a novel SMS inducible transcription factor and the unique spatial arrangement of cis-elements shown in WRKY46 promoter may play an important role for its response to SMS.
Hérisson, Joan; Ferey, Nicolas; Gros, Pierre-Emmanuel; Gherbi, Rachid
Most of biologists work on textual DNA sequences that are limited to the linear representation of DNA. In this paper, we address the potential offered by Virtual Reality for 3D modeling and immersive visualization of large genomic sequences. The representation of the 3D structure of naked DNA allows biologists to observe and analyze genomes in an interactive way at different levels. We developed a powerful software platform that provides a new point of view for sequences analysis: ADNViewer. Nevertheless, a classical eukaryotic chromosome of 40 million base pairs requires about 6 Gbytes of 3D data. In order to manage these huge amounts of data in real-time, we designed various scene management algorithms and immersive human-computer interaction for user-friendly data exploration. In addition, one bioinformatics study scenario is proposed.
C. Appia-ayme; R. Quatrini; Y. Denis; F. Denizot; S. Silver; F. Roberto; F. Veloso; J. Valdes; J. P. Cardenas; M. Esparza; O. Orellana; E. Jedlicki; V. Bonnefoy; D. Holmes
Acidithiobacillus ferrooxidans is a chemolithoautotrophic bacterium that uses iron or sulfur as an energy and electron source. Bioinformatic analysis was used to identify putative genes and potential metabolic pathways involved in CO2 fixation, 2P-glycolate detoxification, carboxysome formation and glycogen utilization in At. ferrooxidans. Microarray transcript profiling was carried out to compare the relative expression of the predicted genes of these pathways when the microorganism was grown in the presence of iron versus sulfur. Several gene expression patterns were confirmed by real-time PCR. Genes for each of the above predicted pathways were found to be organized into discrete clusters. Clusters exhibited differential gene expression depending on the presence of iron or sulfur in the medium. Concordance of gene expression within each cluster, suggested that they are operons Most notably, clusters of genes predicted to be involved in CO2 fixation, carboxysome formation, 2P-glycolate detoxification and glycogen biosynthesis were up-regulated in sulfur medium, whereas genes involved in glycogen utilization were preferentially expressed in iron medium. These results can be explained in terms of models of gene regulation that suggest how A. ferrooxidans can adjust its central carbon management to respond to changing environmental conditions.
Prats, A C; Roy, C; Wang, P A; Erard, M; Housset, V; Gabus, C; Paoletti, C; Darlix, J L
The genetic material of all retroviruses examined so far consists of two identical RNA molecules joined at their 5' ends by the dimer linkage structure (DLS). Since the precise location of the DLS as well as the mechanism and role(s) of RNA dimerization remain unclear, we analyzed the dimerization process of Moloney murine leukemia virus (MoMuLV) genomic RNA. For this purpose we derived an in vitro model for RNA dimerization. By using this model, murine leukemia virus RNA was shown to form dimeric molecules. Deletion mutagenesis in the 620-nucleotide leader of MoMuLV RNA showed that the dimer promoting sequences are located within the encapsidation element Psi between positions 215 and 420. Furthermore, hybridization assays in which DNA oligomers were used to probe monomer and dimer forms of MoMuLV RNA indicated that the DLS probably maps between positions 280 and 330 from the RNA 5' end. Also, retroviral nucleocapsid protein was shown to catalyze dimerization of MoMuLV RNA and to be tightly bound to genomic dimer RNA in virions. These results suggest that MoMuLV RNA dimerization and encapsidation are probably controlled by the same cis element, Psi, and trans-acting factor, nucleocapsid protein, and thus might be linked during virion formation.
Busk, Peter Kamp; Hallin, Peter Fischer; Salomon, Jesper
-regulatory elements. We have developed a method for identifying short, conserved motifs in biological sequences such as proteins, DNA and RNA5. This method was used for analysis of approximately 2000 Arabidopsis thaliana promoters that have been shown by DNA array analysis to be induced by abscisic acid6....... These promoters were compared to 28000 promoters that are not induced by abscisic acid. The analysis identified previously described ABA-inducible promoter elements such as ABRE, CE3 and CRT1 but also new cis-elements were found. Furthermore, the list of DNA elements could be used to predict ABA...
Leyfer, Dmitriy; Weng, Zhiping
A holistic approach to the study of cellular processes is identifying both gene-expression changes and regulatory elements promoting such changes. Cellular regulatory processes can be viewed as transcriptional modules (TMs), groups of coexpressed genes regulated by groups of transcription factors (TFs). We set out to devise a method that would identify TMs while avoiding arbitrary thresholds on TM sizes and number. Assuming that gene expression is determined by TFs that bind to the gene's promoter, clustering of genes based on TF binding sites (cis-elements) should create gene groups similar to those obtained by gene expression clustering. Intersections between the expression and cis-element-based gene clusters reveal TMs. Statistical significance assigned to each TM allows identification of regulatory units of any size. Our method correctly identifies the number and sizes of TMs on simulated datasets. We demonstrate that yeast experimental TMs are biologically relevant by comparing them with MIPS and GO categories. Our modules are in statistically significant agreement with TMs from other research groups. This work suggests that there is no preferential division of biological processes into regulatory units; each degree of partitioning exhibits a slice of biological network revealing hierarchical modular organization of transcriptional regulation.
Full Text Available The link between polyadenylation (pA and various biological, behavioral, and pathological events of eukaryotes underlines the need to develop in vivo polyadenylation assay methods for characterization of the cis-acting elements, trans-acting factors and environmental stimuli that affect polyadenylation efficiency and/or relative usage of two alternative polyadenylation (APA sites. The current protein-based CAT or luciferase reporter systems can measure the polyadenylation efficiency of a single pA site or candidate cis element but not the choice of two APA sites. To address this issue, we developed a set of four new bicistronic reporter vectors that harbor either two luciferase or fluorescence protein open reading frames connected with one Internal Ribosome Entry Site (IRES. Transfection of single or dual insertion constructs of these vectors into mammalian cells demonstrated that they could be utilized not only to quantify the strength of a single candidate pA site or cis element, but also to accurately measure the relative usage of two APA sites at both the mRNA (qRT-PCR and protein levels. This represents the first reporter system that can study polyadenylation efficiency of a single pA site or element and regulation of two APA sites at both the mRNA and protein levels.
Papantonis, Argyris; Sourmeli, Sissy; Lecanidou, Rena
From the different cis-elements clustered on silkmoth chorion gene promoters, C/EBP binding sites predominate. Their sequence composition and dispersal vary amongst promoters of diverse developmental specificity. Occupancy of these sites by BmC/EBP was examined through Southwestern and ChIP assays modified to suit ovarian follicular cells. For the genes studied, binding of BmC/EBP coincided with the respective stages of transcriptional activation. However, the factor was reloaded on promoter sequences long after individual gene repression. Furthermore, suppression of BmC/EBP transcription in developing follicles resulted in de-regulation of chorion gene expression. A biphasic function of BmC/EBP, according to which it may act as both an activator and a repressor during silkmoth choriogenesis, is considered under the light of the presented data.
Full Text Available Phalaenopsis bellina is a scented orchid emitting large amount of monoterpenes. GERANYL DIPHOSPHATE SYNTHASE (PbGDPS is the key enzyme for monoterpene biosynthesis, and shows concomitant expression with the emission of monoterpenes during flower development in P. bellina. Here, we identified a dual repeat cis-element in the GDPS promoter that is critical for monoterpene biosynthesis in Phalaenopsis orchids. A strong correlation between the dual repeat and the monoterpene production was revealed by examination of the GDPS promoter fragments over 12 Phalaenopsis species. Serial-deletion of the 2-kb GDPS promoter fragments demonstrated that the integrity of the dual repeat was crucial for its promoter activities. By screening the Arabidopsis transcription factors (TFs cDNA library using yeast one-hybrid assay, AtbZIP18, a member of group I of bZIP TFs, was identified to be able to bind the dual repeat. We then identified PbbZIP4 in the transcriptome of P. bellina, showing 83% identity in the DNA binding region with that of AtbZIP18, and the expression level of PbbZIP4 was higher in the scented orchids. In addition, PbbZIP4 transactivated the GDPS promoter fragment containing the dual repeat in dual luciferase assay. Furthermore, transient ectopic expression of PbbZIP4 induced a 10-fold production of monoterpenoids in the scentless orchid. In conclusion, these results indicate that the dual repeat is a real TF-bound cis-element significant for GDPS gene expression, and thus subsequent monoterpene biosynthesis in the scented Phalaenopsis orchids.
Muhle, Rebecca A; Adjalley, Sophie; Falkard, Brie; Nkrumah, Louis J; Muhle, Michael E; Fidock, David A
Questions surround the mechanism of mutually exclusive expression by which Plasmodium falciparum mediates activation and silencing of var genes. These encode PfEMP1 proteins, which function as cytoadherent and immunomodulatory molecules at the surface of parasitised erythrocytes. Current evidence suggests that promoter silencing by var introns might play a key role in var gene regulation. To evaluate the impact of cis-acting regulatory regions on var silencing, we generated P. falciparum lines in which luciferase was placed under the control of an UpsA var promoter. By utilising the Bxb1 integrase system, these reporter cassettes were targeted to a genomic region that was not in apposition to var subtelomeric domains. This eliminated possible effects from surrounding telomeric elements and removed the variability inherent in episomal systems. Studies with highly synchronised parasites revealed that the UpsA element possessed minimal activity in comparison with a heterologous (hrp3) promoter. This may result from the integrated UpsA promoter being largely silenced by the neighbouring cg6 promoter. Our analyses also revealed that the DownsA 3' untranslated region further decreased the luciferase activity from both cassettes, whereas the var A intron repressed the UpsA promoter specifically. By applying multivariate analysis over the entire cell cycle, we confirmed the significance of these cis-elements and found the parasite stage to be the major factor regulating UpsA-promoter activity. Additionally, we observed that the UpsA promoter was capable of nucleating reversible silencing that spread to a downstream promoter. We believe these studies are the first to analyse promoter activity of Group A var genes, which have been implicated in severe malaria, and support the model that var introns can further suppress var expression. These data also suggest an important suppressive role for the DownsA terminator. Our findings imply the existence of multiple levels of var
Pittayakhajonwut, Daraporn; Angeletti, Peter C.
Human papillomaviruses (HPVs) are maintained latently in dividing epithelial cells as nuclear plasmids. Two virally encoded proteins, E1, a helicase, and E2, a transcription factor, are important players in replication and stable plasmid maintenance in host cells. Recent experiments in yeast have demonstrated that viral genomes retain replication and maintenance function independently of E1 and E2 [Angeletti, P.C., Kim, K., Fernandes, F.J., and Lambert, P.F. (2002). Stable replication of papillomavirus genomes in Saccharomyces cerevisiae. J. Virol. 76(7), 3350-8; Kim, K., Angeletti, P.C., Hassebroek, E.C., and Lambert, P.F. (2005). Identification of cis-acting elements that mediate the replication and maintenance of human papillomavirus type 16 genomes in Saccharomyces cerevisiae. J. Virol. 79(10), 5933-42]. Flow cytometry studies of EGFP-reporter vectors containing subgenomic HPV fragments with or without a human ARS (hARS), revealed that six fragments located in E6-E7, E1-E2, L1, and L2 regions showed a capacity for plasmid stabilization in the absence of E1 and E2 proteins. Interestingly, four fragments within E7, the 3' end of L2, and the 5' end of L1 exhibited stability in plasmids that lacked an hARS, indicating that they possess both replication and maintenance functions. Two fragments lying in E1-E2 and the 3' region of L1 were stable only in the presence of hARS, that they contained only maintenance function. Mutational analyses of HPV16-GFP reporter constructs provided evidence that genomes lacking E1 and E2 could replicate to an extent similar to wild type HPV16. Together these results support the concept that cellular factors influence HPV replication and maintenance, independently, and perhaps in conjunction with E1 and E2, suggesting a role in the persistent phase of the viral lifecycle
Sunny Li-Yun Chang
Full Text Available Proper development of vertebrate embryos depends not only on the crucial funtions of key evolutionarily conserved transcriptional regulators, but also on the precisely spatiotemporal expression of these transcriptional regulators. The mouse Nolz-1/Znf503/Zfp503 gene is a mammalian member of the conserved zinc-finger containing NET family. The expression pattern of Nolz-1 in mouse embryos is highly correlated with that of its homologues in different species. To study the spatiotemporal regulation of Nolz-1, we first identified two evolutionarily conserved cis-elements, UREA and UREB, in 5' upstream regions of mouse Nolz-1 locus. We then generated UREA-LacZ and UREB-LacZ transgenic reporter mice to characterize the putative enhancer activity of UREA and UREB. The results indicated that both UREA and UREB contained tissue-specific enhancer activity for directing LacZ expression in selective tissue organs during mouse embryogensis. UREA directed LacZ expression preferentially in selective regions of developing central nervous system, including the forebrain, hindbrain and spinal cord, whereas UREB directed LacZ expression mainly in other developing tissue organs such as the Nolz-1 expressing branchial arches and its derivatives, the apical ectodermal ridge of limb buds and the urogenital tissues. Both UREA and UREB directed strong LacZ expression in the lateral plate mesoderm where endogenous Nolz-1 was also expressed. Despite that the LacZ expression pattern did not full recapitulated the endogenous Nolz-1 expression and some mismatched expression patterns were observed, co-expression of LacZ and Nolz-1 did occur in many cells of selective tissue organs, such as in the ventrolateral cortex and ventral spinal cord of UREA-LacZ embryos, and the urogenital tubes of UREB-LacZ embryos. Taken together, our study suggests that UREA and UREB may function as evolutionarily conserved cis-regulatory elements that coordinate with other cis-elements to regulate
Full Text Available The MPT transports Pi to synthesize ATP. PsMPT, a chilling-induced gene, was previously reported to promote energy metabolism during bud dormancy release in tree peony. In this study, the regulatory elements of PsMPT promoter involved in chilling response were further analyzed. The PsMPT transcript was detected in different tree peony tissues and was highly expressed in the flower organs, including petal, stigma and stamen. An 1174 bp of the PsMPT promoter was isolated by TAIL-PCR, and the PsMPT promoter::GUS transgenic Arabidopsis was generated and analyzed. GUS staining and qPCR showed that the promoter was active in mainly the flower stigma and stamen. Moreover, it was found that the promoter activity was enhanced by chilling, NaCl, GA, ACC and NAA, but inhibited by ABA, mannitol and PEG. In transgenic plants harboring 421 bp of the PsMPT promoter, the GUS gene expression and the activity were significantly increased by chilling treatment. When the fragment from -421 to -408 containing a MYC cis-element was deleted, the chilling response could not be observed. Further mutation analysis confirmed that the MYC element was one of the key motifs responding to chilling in the PsMPT promoter. The present study provides useful information for further investigation of the regulatory mechanism of PsMPT during the endo-dormancy release.
Ian B Robertson
Full Text Available Proteins from the LTBP/fibrillin family perform key structural and functional roles in connective tissues. LTBP1 forms the large latent complex with TGFβ and its propeptide LAP, and sequesters the latent growth factor to the extracellular matrix. Bioinformatics studies suggest the main structural features of the LTBP1 C-terminus are conserved through evolution. NMR studies were carried out on three overlapping C-terminal fragments of LTBP1, comprising four domains with characterised homologues, cbEGF14, TB3, EGF3 and cbEGF15, and three regions with no homology to known structures. The NMR data reveal that the four domains adopt canonical folds, but largely lack the interdomain interactions observed with homologous fibrillin domains; the exception is the EGF3-cbEGF15 domain pair which has a well-defined interdomain interface. (15N relaxation studies further demonstrate that the three interdomain regions act as flexible linkers, allowing a wide range of motion between the well-structured domains. This work is consistent with the LTBP1 C-terminus adopting a flexible "knotted rope" structure, which may facilitate cell matrix interactions, and the accessibility to proteases or other factors that could contribute to TGFβ activation.
Darlix, J L; Gabus, C; Nugeyre, M T; Clavel, F; Barré-Sinoussi, F
The retroviral genome consists of two identical RNA molecules joined at their 5' ends by the Dimer Linkage Structure (DLS). To study the mechanism of dimerization and the DLS of HIV-1 RNA, large amounts of bona fide HIV-1 RNA and of mutants have been synthesized in vitro. We report that HIV-1 RNA forms dimeric molecules and that viral nucleocapsid (NC) protein NCp15 greatly activates dimerization. Deletion mutagenesis in the RNA 5' 1333 nucleotides indicated that a small domain of 100 nucleotides, located between positions 311 to 415 from the 5' end, is necessary and sufficient to promote HIV-1 RNA dimerization. This dimerization domain encompasses an encapsidation element located between the 5' splice donor site and initiator AUG of gag and shows little sequence variations in different strains of HIV-1. Furthermore, cross-linking analysis of the interactions between NC and HIV-1 RNA (311 to 415) locates a major contact site in the encapsidation element of HIV-1 RNA. The genomic RNA dimer is tightly associated with nucleocapsid protein molecules in avian and murine retroviruses, and this ribonucleoprotein structure is believed to be the template for reverse transcription. Genomic RNA-protein interactions have been analyzed in human immunodeficiency virus (HIV) virions and results showed that NC protein molecules are tightly bound to the genomic RNA dimer. Since retroviral RNA dimerization and packaging appear to be under the control of the same cis element, the encapsidation sequences, and trans-acting factor, the NC protein, they are probably related events in the course of virion assembly.
Rawat, Reetika; Xu, Zeng-Fu; Yao, Kwok-Ming; Chye, Mee-Len
We have previously shown that the expression of SmCP which encodes Solanum melongena cysteine proteinase is ethylene-inducible and is under circadian control. To understand the regulation of SmCP, a 1.34-kb SmCP 5'-flanking region and its deletion derivatives were analyzed for cis-elements using GUS and luc fusions and by in vitro binding assays. Analysis of transgenic tobacco transformed with SmCP promoter-GUS constructs confirmed that the promoter region -415/+54 containing Ethylene Responsive Element ERE(-355/-348) conferred threefold ethylene-induction of GUS expression, while -827/+54 which also contains ERE(-683/-676), produced fivefold induction. Using gel mobility shift assays, we demonstrated that each ERE binds nuclear proteins from both ethephon-treated and untreated 5-week-old seedlings, suggesting that different transcriptions factors bind each ERE under varying physiological conditions. Binding was also observed in extracts from senescent, but not young, fruits. The variation in binding at the EREs in fruits and seedlings imply that organ-specific factors may participate in binding. Analysis of transgenic tobacco expressing various SmCP promoter-luc constructs containing wild-type or mutant Evening Elements (EEs) confirmed that both conserved EEs at -795/-787 and -785/-777 are important in circadian control. We confirmed the binding of total nuclear proteins to EEs in gel mobility shift assays and in DNase I footprinting. Our results suggest that multiple proteins bind the EEs which are conserved in plants other than Arabidopsis and that functional EEs and EREs are present in the 5'-flanking region of a gene encoding cysteine proteinase.
Chen Jiegen; Li Xi; Huang Haiyan; Liu Honglei; Liu Deguo; Song Tanjing; Ma Chungu; Ma Duan; Song Houyan; Tang Qiqun
PAI-1 is expressed and secreted by adipose tissue which may mediate the pathogenesis of obesity-associated cardiovascular complications. Evidence is presented in this report that PAI-1 is not expressed by preadipocyte, but significantly induced during 3T3-L1 adipocyte differentiation and the PAI-1 expression correlates with the induction of peroxisome proliferator-activated receptor γ (PPARγ). A peroxisome proliferator responsive element (PPRE)-like cis-element (-206TCCCCCATGCCCT-194) is identified in the mouse PAI-1 gene promoter by electrophoretic mobility shift assay (EMSA) combined with transient transfection experiments; the PPRE-like cis-element forms a specific DNA-protein complex only with adipocyte nuclear extracts, not with preadipocyte nuclear extracts; the DNA-protein complex can be totally competed away by non-labeled consensus PPRE, and can be supershifted with PPARγ antibody. Mutation of this PPRE-like cis-element can abolish the transactivation of mouse PAI-1 promoter mediated by PPARγ. Specific PPARγ ligand Pioglitazone can significantly induce the PAI-1 expression, and stimulate the secretion of PAI-1 into medium
Full Text Available Abstract Background The process of HIV-1 genomic RNA (gRNA encapsidation is governed by a number of viral encoded components, most notably the Gag protein and gRNA cis elements in the canonical packaging signal (ψ. Also implicated in encapsidation are cis determinants in the R, U5, and PBS (primer binding site from the 5' untranslated region (UTR. Although conventionally associated with nuclear export of HIV-1 RNA, there is a burgeoning role for the Rev/RRE in the encapsidation process. Pleiotropic effects exhibited by these cis and trans viral components may confound the ability to examine their independent, and combined, impact on encapsidation of RNA into HIV-1 viral particles in their innate viral context. We systematically reconstructed the HIV-1 packaging system in the context of a heterologous murine leukemia virus (MLV vector RNA to elucidate a mechanism in which the Rev/RRE system is central to achieving efficient and specific encapsidation into HIV-1 viral particles. Results We show for the first time that the Rev/RRE system can augment RNA encapsidation independent of all cis elements from the 5' UTR (R, U5, PBS, and ψ. Incorporation of all the 5' UTR cis elements did not enhance RNA encapsidation in the absence of the Rev/RRE system. In fact, we demonstrate that the Rev/RRE system is required for specific and efficient encapsidation commonly associated with the canonical packaging signal. The mechanism of Rev/RRE-mediated encapsidation is not a general phenomenon, since the combination of the Rev/RRE system and 5' UTR cis elements did not enhance encapsidation into MLV-derived viral particles. Lastly, we show that heterologous MLV RNAs conform to transduction properties commonly associated with HIV-1 viral particles, including in vivo transduction of non-dividing cells (i.e. mouse neurons; however, the cDNA forms are episomes predominantly in the 1-LTR circle form. Conclusions Premised on encapsidation of a heterologous RNA into
Muhle, Rebecca A.; Adjalley, Sophie; Falkard, Brie; Nkrumah, Louis J.; Muhle, Michael E.; Fidock, David A.
Questions surround the mechanism of mutually exclusive expression by which Plasmodium falciparum mediates activation and silencing of var genes. These encode PfEMP1 proteins, which function as cytoadherent and immunomodulatory molecules at the surface of parasitized erythrocytes. Current evidence suggests that promoter silencing by var introns might play a key role in var gene regulation. To evaluate the impact of cis-acting regulatory regions on var silencing, we generated P. falciparum lines in which luciferase was placed under the control of an UpsA var promoter. By utilizing the Bxb1 integrase system, these reporter cassettes were targeted to a genomic region that was not in apposition to var sub-telomeric domains. This eliminated possible effects from surrounding telomeric elements and removed the variability inherent in episomal systems. Studies with highly synchronized parasites revealed that the UpsA element possessed minimal activity in comparison with a heterologous (hrp3) promoter. This may well result from the integrated UpsA promoter being largely silenced by the neighboring cg6 promoter. Our analyses also revealed that the DownsA 3’ untranslated region further decreased the luciferase activity from both cassettes, whereas the var A intron repressed the UpsA promoter specifically. By applying multivariate analysis over the entire cell cycle, we confirmed the significance of these cis-elements and found the parasite stage to be the major factor regulating UpsA promoter activity. Additionally, we observed that the UpsA promoter was capable of nucleating reversible silencing that spread to a downstream promoter. We believe these studies are the first to analyze promoter activity of Group A var genes which have been implicated in severe malaria, and support the model that var introns can further suppress var expression. These data also suggest an important suppressive role for the DownsA terminator. Our findings imply the existence of multiple levels of
Full Text Available BACKGROUND: SCP/TAPS proteins of parasitic helminths have been proposed to play key roles in fundamental biological processes linked to the invasion of and establishment in their mammalian host animals, such as the transition from free-living to parasitic stages and the modulation of host immune responses. Despite the evidence that SCP/TAPS proteins of parasitic nematodes are involved in host-parasite interactions, there is a paucity of information on this protein family for parasitic trematodes of socio-economic importance. METHODOLOGY/PRINCIPAL FINDINGS: We conducted the first large-scale study of SCP/TAPS proteins of a range of parasitic trematodes of both human and veterinary importance (including the liver flukes Clonorchis sinensis, Opisthorchis viverrini, Fasciola hepatica and F. gigantica as well as the blood flukes Schistosoma mansoni, S. japonicum and S. haematobium. We mined all current transcriptomic and/or genomic sequence datasets from public databases, predicted secondary structures of full-length protein sequences, undertook systematic phylogenetic analyses and investigated the differential transcription of SCP/TAPS genes in O. viverrini and F. hepatica, with an emphasis on those that are up-regulated in the developmental stages infecting the mammalian host. CONCLUSIONS: This work, which sheds new light on SCP/TAPS proteins, guides future structural and functional explorations of key SCP/TAPS molecules associated with diseases caused by flatworms. Future fundamental investigations of these molecules in parasites and the integration of structural and functional data could lead to new approaches for the control of parasitic diseases.
Alexandre G. de Brevern
de Brevern, Alexandre G.; Meyniel, Jean-Philippe; Fairhead, Cécile; Neuvéglise, Cécile; Malpertuy, Alain
de Brevern, Alexandre G; Meyniel, Jean-Philippe; Fairhead, Cécile; Neuvéglise, Cécile; Malpertuy, Alain
Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.
Brazas, Michelle D.; Ouellette, B. F. Francis
With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable...
Lawlor, Brendan; Walsh, Paul
There is a lack of software engineering skills in bioinformatic contexts. We discuss the consequences of this lack, examine existing explanations and remedies to the problem, point out their shortcomings, and propose alternatives. Previous analyses of the problem have tended to treat the use of software in scientific contexts as categorically different from the general application of software engineering in commercial settings. In contrast, we describe bioinformatic software engineering as a specialization of general software engineering, and examine how it should be practiced. Specifically, we highlight the difference between programming and software engineering, list elements of the latter and present the results of a survey of bioinformatic practitioners which quantifies the extent to which those elements are employed in bioinformatics. We propose that the ideal way to bring engineering values into research projects is to bring engineers themselves. We identify the role of Bioinformatic Engineer and describe how such a role would work within bioinformatic research teams. We conclude by recommending an educational emphasis on cross-training software engineers into life sciences, and propose research on Domain Specific Languages to facilitate collaboration between engineers and bioinformaticians.
Lawlor, Brendan; Walsh, Paul
There is a lack of software engineering skills in bioinformatic contexts. We discuss the consequences of this lack, examine existing explanations and remedies to the problem, point out their shortcomings, and propose alternatives. Previous analyses of the problem have tended to treat the use of software in scientific contexts as categorically different from the general application of software engineering in commercial settings. In contrast, we describe bioinformatic software engineering as a specialization of general software engineering, and examine how it should be practiced. Specifically, we highlight the difference between programming and software engineering, list elements of the latter and present the results of a survey of bioinformatic practitioners which quantifies the extent to which those elements are employed in bioinformatics. We propose that the ideal way to bring engineering values into research projects is to bring engineers themselves. We identify the role of Bioinformatic Engineer and describe how such a role would work within bioinformatic research teams. We conclude by recommending an educational emphasis on cross-training software engineers into life sciences, and propose research on Domain Specific Languages to facilitate collaboration between engineers and bioinformaticians. PMID:25996054
Wooller, Sarah K; Benstead-Hume, Graeme; Chen, Xiangrong; Ali, Yusuf; Pearl, Frances M G
Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications. © 2017 The Author(s).
Ma, Zhaoxue; Hu, Xupeng; Cai, Wenjuan; Huang, Weihua; Zhou, Xin; Luo, Qian; Yang, Hongquan; Wang, Jiawei; Huang, Jirong
An extraordinarily precise regulation of chlorophyll biosynthesis is essential for plant growth and development. However, our knowledge on the complex regulatory mechanisms of chlorophyll biosynthesis is very limited. Previous studies have demonstrated that miR171-targeted scarecrow-like proteins (SCL6/22/27) negatively regulate chlorophyll biosynthesis via an unknown mechanism. Here we showed that SCLs inhibit the expression of the key gene encoding protochlorophyllide oxidoreductase (POR) in light-grown plants, but have no significant effect on protochlorophyllide biosynthesis in etiolated seedlings. Histochemical analysis of β-glucuronidase (GUS) activity in transgenic plants expressing pSCL27::rSCL27-GUS revealed that SCL27-GUS accumulates at high levels and suppresses chlorophyll biosynthesis at the leaf basal proliferation region during leaf development. Transient gene expression assays showed that the promoter activity of PORC is indeed regulated by SCL27. Consistently, chromatin immunoprecipitation and quantitative PCR assays showed that SCL27 binds to the promoter region of PORC in vivo. An electrophoretic mobility shift assay revealed that SCL27 is directly interacted with G(A/G)(A/T)AA(A/T)GT cis-elements of the PORC promoter. Furthermore, genetic analysis showed that gibberellin (GA)-regulated chlorophyll biosynthesis is mediated, at least in part, by SCLs. We demonstrated that SCL27 interacts with DELLA proteins in vitro and in vivo by yeast-two-hybrid and coimmunoprecipitation analysis and found that their interaction reduces the binding activity of SCL27 to the PORC promoter. Additionally, we showed that SCL27 activates MIR171 gene expression, forming a feedback regulatory loop. Taken together, our data suggest that the miR171-SCL module is critical for mediating GA-DELLA signaling in the coordinate regulation of chlorophyll biosynthesis and leaf growth in light. PMID:25101599
Full Text Available Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyse and describe several approaches that use sequences, structures, interactomics and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are: a remote homology searches using Psi-Blast, b detection of functional motifs and domains, c analysis of data from protein-protein interaction databases (PPIs, d match the query protein sequence to 3D databases (i.e., algorithms as PISITE, e mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs have the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations –it requires the existence of multialigned family protein sequences - but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (http://wallace.uab.es/multitask/, previously published by our group, has been used as a benchmark for the all of the analyses.
Brazas, Michelle D; Ouellette, B F Francis
With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable in the learning continuum. Bioinformatics.ca, which hosts the Canadian Bioinformatics Workshops, has blended more traditional learning styles with current online and social learning styles. Here we share our growing experiences over the past 12 years and look toward what the future holds for bioinformatics training programs.
Gonzales, Melissa; Bowden, G Tim
The ultraviolet B (UVB) portion (280-320 nm) of the ultraviolet spectrum has been shown to contribute to the development of non-melanoma skin cancer in humans. Research in the human keratinocyte cell line, HaCaT, revealed that UVB irradiation caused the upregulation of the transcription factor activator protein-1 (AP-1). The AP-1 complex formed in UVB-irradiated HaCaT cells is specifically composed of c-fos and Jun D. c-Fos expression was induced in a manner that correlated with the UVB-induced activation of AP-1. To investigate how c-fos expression is regulated by UVB irradiation, the role of each of four cis elements within the c-fos promoter was evaluated. Clustered point mutations at the sis inducible element (SIE), serum response element (SRE), c-fos AP-1 site (FAP1), or cyclic AMP response elements (CRE) significantly inhibited UVB induction of the c-fos promoter. This indicated that all four cis elements are required for maximum promoter activity. The CRE and FAP1 elements were the two most active cis elements that mediate the UVB transactivation of c-fos. Homodimers of phosphorylated cAMP response element binding protein (CREB) were induced by UVB irradiation to bind to each of these elements. Therefore, CREB may function as an important regulatory protein in the UVB-induced expression of c-fos.
Genomic and bioinformatics analyses of HAdV-4vac and HAdV-7vac, two human adenovirus (HAdV) strains that constituted original prophylaxis against HAdV-related acute respiratory disease, a reemerging epidemic disease.
Purkayastha, Anjan; Su, Jing; McGraw, John; Ditty, Susan E; Hadfield, Ted L; Seto, Jason; Russell, Kevin L; Tibbetts, Clark; Seto, Donald
Vaccine strains of human adenovirus serotypes 4 and 7 (HAdV-4vac and HAdV-7vac) have been used successfully to prevent adenovirus-related acute respiratory disease outbreaks. The genomes of these two vaccine strains have been sequenced, annotated, and compared with their prototype equivalents with the goals of understanding their genomes for molecular diagnostics applications, vaccine redevelopment, and HAdV pathoepidemiology. These reference genomes are archived in GenBank as HAdV-4vac (35,994 bp; AY594254) and HAdV-7vac (35,240 bp; AY594256). Bioinformatics and comparative whole-genome analyses with their recently reported and archived prototype genomes reveal six mismatches and four insertions-deletions (indels) between the HAdV-4 prototype and vaccine strains, in contrast to the 611 mismatches and 130 indels between the HAdV-7 prototype and vaccine strains. Annotation reveals that the HAdV-4vac and HAdV-7vac genomes contain 51 and 50 coding units, respectively. Neither vaccine strain appears to be attenuated for virulence based on bioinformatics analyses. There is evidence of genome recombination, as the inverted terminal repeat of HAdV-4vac is initially identical to that of species C whereas the prototype is identical to species B1. These vaccine reference sequences yield unique genome signatures for molecular diagnostics. As a molecular forensics application, these references identify the circulating and problematic 1950s era field strains as the original HAdV-4 prototype and the Greider prototype, from which the vaccines are derived. Thus, they are useful for genomic comparisons to current epidemic and reemerging field strains, as well as leading to an understanding of pathoepidemiology among the human adenoviruses.
Fuller, Jonathan C; Khoueiry, Pierre; Dinkel, Holger; Forslund, Kristoffer; Stamatakis, Alexandros; Barry, Joseph; Budd, Aidan; Soldatos, Theodoros G; Linssen, Katja; Rajput, Abdul Mateen
The third Heidelberg Unseminars in Bioinformatics (HUB) was held on 18th October 2012, at Heidelberg University, Germany. HUB brought together around 40 bioinformaticians from academia and industry to discuss the 'Biggest Challenges in Bioinformatics' in a 'World Café' style event.
Fuller, Jonathan C; Khoueiry, Pierre; Dinkel, Holger; Forslund, Kristoffer; Stamatakis, Alexandros; Barry, Joseph; Budd, Aidan; Soldatos, Theodoros G; Linssen, Katja; Rajput, Abdul Mateen
The third Heidelberg Unseminars in Bioinformatics (HUB) was held in October at Heidelberg University in Germany. HUB brought together around 40 bioinformaticians from academia and industry to discuss the ‘Biggest Challenges in Bioinformatics' in a ‘World Café' style event.
Pallen, Mark J
Microbial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever-growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale-up to the million-microbial-genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user-friendly outputs. The "internet of things" will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd-sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand-held sequencers will be analysed on mobile devices. Open-source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty-first century, microbial sequence space will remain the final frontier! © 2016 The Author. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.
Schönbach, Christian; Li, Jinyan; Ma, Lan; Horton, Paul; Sjaugi, Muhammad Farhan; Ranganathan, Shoba
The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018.
Gorodkin, Jan; Hofacker, Ivo L.; Ruzzo, Walter L.
RNA bioinformatics and computational RNA biology have emerged from implementing methods for predicting the secondary structure of single sequences. The field has evolved to exploit multiple sequences to take evolutionary information into account, such as compensating (and structure preserving) base...... for interactions between RNA and proteins.Here, we introduce the basic concepts of predicting RNA secondary structure relevant to the further analyses of RNA sequences. We also provide pointers to methods addressing various aspects of RNA bioinformatics and computational RNA biology....
Researchers take on challenges and opportunities to mine "Big Data" for answers to complex biological questions. Learn how bioinformatics uses advanced computing, mathematics, and technological platforms to store, manage, analyze, and understand data.
Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: firstname.lastname@example.org.
Chen, Xiaoling; Chang, Jeffrey T.
Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: email@example.com PMID:28052928
Full Text Available Extensive studies in Arabidopsis and rice have demonstrated that Subgroup-A members of the bZIP transcription factor family play important roles in plant responses to multiple abiotic stresses. Although common wheat (Triticum aestivum is one of the most widely cultivated and consumed food crops in the world, there are limited investigations into Subgroup A of the bZIP family in wheat. In this study, we performed bioinformatic analyses of the 41 Subgroup-A members of the wheat bZIP family. Phylogenetic and conserved motif analyses showed that most of the Subgroup-A bZIP proteins involved in abiotic stress responses of wheat, Arabidopsis and rice clustered in Clade A1 of the phylogenetic tree, and shared a majority of conserved motifs, suggesting the potential importance of Clade-A1 members in abiotic stress responses. Gene structure analysis showed that TabZIP genes with close phylogenetic relationships tended to possess similar exon-intron compositions, and the positions of introns in the hinge regions of the bZIP domains were highly conserved, whereas introns in the leucine zipper regions were at variable positions. Additionally, eleven groups of homologs and two groups of tandem paralogs were also identified in Subgroup A of the wheat bZIP family. Expression profiling analysis indicated that most Subgroup-A TabZIP genes were responsive to abscisic acid and various abiotic stress treatments. TabZIP27, TabZIP74, TabZIP138 and TabZIP174 proteins were localized in the nucleus of wheat protoplasts, whereas TabZIP9-GFP fusion protein was simultaneously present in the nucleus, cytoplasm and cell membrane. Transgenic Arabidopsis overexpressing TabZIP174 displayed increased seed germination rates and primary root lengths under drought treatments. Overexpression of TabZIP174 in transgenic Arabidopsis conferred enhanced drought tolerance, and transgenic plants exhibited lower water loss rates, higher survival rates, higher proline, soluble sugar and leaf
Li, Xueyin; Feng, Biane; Zhang, Fengjie; Tang, Yimiao; Zhang, Liping; Ma, Lingjian; Zhao, Changping; Gao, Shiqing
Extensive studies in Arabidopsis and rice have demonstrated that Subgroup-A members of the bZIP transcription factor family play important roles in plant responses to multiple abiotic stresses. Although common wheat (Triticum aestivum) is one of the most widely cultivated and consumed food crops in the world, there are limited investigations into Subgroup A of the bZIP family in wheat. In this study, we performed bioinformatic analyses of the 41 Subgroup-A members of the wheat bZIP family. Phylogenetic and conserved motif analyses showed that most of the Subgroup-A bZIP proteins involved in abiotic stress responses of wheat, Arabidopsis, and rice clustered in Clade A1 of the phylogenetic tree, and shared a majority of conserved motifs, suggesting the potential importance of Clade-A1 members in abiotic stress responses. Gene structure analysis showed that TabZIP genes with close phylogenetic relationships tended to possess similar exon–intron compositions, and the positions of introns in the hinge regions of the bZIP domains were highly conserved, whereas introns in the leucine zipper regions were at variable positions. Additionally, eleven groups of homologs and two groups of tandem paralogs were also identified in Subgroup A of the wheat bZIP family. Expression profiling analysis indicated that most Subgroup-A TabZIP genes were responsive to abscisic acid and various abiotic stress treatments. TabZIP27, TabZIP74, TabZIP138, and TabZIP174 proteins were localized in the nucleus of wheat protoplasts, whereas TabZIP9-GFP fusion protein was simultaneously present in the nucleus, cytoplasm, and cell membrane. Transgenic Arabidopsis overexpressing TabZIP174 displayed increased seed germination rates and primary root lengths under drought treatments. Overexpression of TabZIP174 in transgenic Arabidopsis conferred enhanced drought tolerance, and transgenic plants exhibited lower water loss rates, higher survival rates, higher proline, soluble sugar, and leaf chlorophyll
Johnson, Kathy A.
For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.
Wei, Dongqing; Zhao, Tangzhen; Dai, Hao
This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As such, it emphasizes programming and problem-solving skills. It provides information on structure bioinformatics at various levels, with individual chapters covering introductory to advanced aspects, from fundamental methods and guidelines on acquiring and analyzing genomics and proteomics sequences, the structures of protein, DNA and RNA, to the basics of physical simulations and methods for conform
Hiraoka, Satoshi; Yang, Ching-Chia; Iwasaki, Wataru
Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.
Good, Benjamin M; Su, Andrew I
Bioinformatics is faced with a variety of problems that require human involvement. Tasks like genome annotation, image analysis, knowledge-base population and protein structure determination all benefit from human input. In some cases, people are needed in vast quantities, whereas in others, we need just a few with rare abilities. Crowdsourcing encompasses an emerging collection of approaches for harnessing such distributed human intelligence. Recently, the bioinformatics community has begun to apply crowdsourcing in a variety of contexts, yet few resources are available that describe how these human-powered systems work and how to use them effectively in scientific domains. Here, we provide a framework for understanding and applying several different types of crowdsourcing. The framework considers two broad classes: systems for solving large-volume 'microtasks' and systems for solving high-difficulty 'megatasks'. Within these classes, we discuss system types, including volunteer labor, games with a purpose, microtask markets and open innovation contests. We illustrate each system type with successful examples in bioinformatics and conclude with a guide for matching problems to crowdsourcing solutions that highlights the positives and negatives of different approaches.
Burr, Tom L [Los Alamos National Laboratory
Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.
Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research.
Metz, B A; Welters, P; Hoffmann, H J
The primary structure of a leghemoglobin (lb) gene from the stem-nodulated, tropical legume Sesbania rostrata and two lb gene promoter regions was analysed. The S. rostrata lb gene structure and Lb amino acid composition were found to be highly conserved with previously described lb genes and Lb ...
Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; Fernandes, Pedro L; van Gelder, Celia; Jacob, Joachim; Jimenez, Rafael C; Loveland, Jane; Moran, Federico; Mulder, Nicola; Nyrö nen, Tommi; Rother, Kristian; Schneider, Maria Victoria; Attwood, Teresa K
concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource
Abdulganiyu Abdu Yusuf; Zahraddeen Sufyanu; Kabir Yusuf Mamman; Abubakar Umar Suleiman
Bioinformatics is the application of computational tools to capture and interpret biological data. It has wide applications in drug development, crop improvement, agricultural biotechnology and forensic DNA analysis. There are various databases available to researchers in bioinformatics. These databases are customized for a specific need and are ranged in size, scope, and purpose. The main drawbacks of bioinformatics databases include redundant information, constant change, data spread over m...
Full Text Available Venomics is a modern approach that combines transcriptomics and proteomics to explore the toxin content of venoms. This review will give an overview of computational approaches that have been created to classify and consolidate venomics data, as well as algorithms that have helped discovery and analysis of toxin nucleic acid and protein sequences, toxin three-dimensional structures and toxin functions. Bioinformatics is used to tackle specific challenges associated with the identification and annotations of toxins. Recognizing toxin transcript sequences among second generation sequencing data cannot rely only on basic sequence similarity because toxins are highly divergent. Mass spectrometry sequencing of mature toxins is challenging because toxins can display a large number of post-translational modifications. Identifying the mature toxin region in toxin precursor sequences requires the prediction of the cleavage sites of proprotein convertases, most of which are unknown or not well characterized. Tracing the evolutionary relationships between toxins should consider specific mechanisms of rapid evolution as well as interactions between predatory animals and prey. Rapidly determining the activity of toxins is the main bottleneck in venomics discovery, but some recent bioinformatics and molecular modeling approaches give hope that accurate predictions of toxin specificity could be made in the near future.
Emergent Computation is concerned with recent applications of Mathematical Linguistics or Automata Theory. This subject has a primary focus upon "Bioinformatics" (the Genome and arising interest in the Proteome), but the closing chapter also examines applications in Biology, Medicine, Anthropology, etc. The book is composed of an organized examination of DNA, RNA, and the assembly of amino acids into proteins. Rather than examine these areas from a purely mathematical viewpoint (that excludes much of the biochemical reality), the author uses scientific papers written mostly by biochemists based upon their laboratory observations. Thus while DNA may exist in its double stranded form, triple stranded forms are not excluded. Similarly, while bases exist in Watson-Crick complements, mismatched bases and abasic pairs are not excluded, nor are Hoogsteen bonds. Just as there are four bases naturally found in DNA, the existence of additional bases is not ignored, nor amino acids in addition to the usual complement of...
Kortsarts, Yana; Morris, Robert W.; Utell, Janine M.
Bioinformatics is a relatively new interdisciplinary field that integrates computer science, mathematics, biology, and information technology to manage, analyze, and understand biological, biochemical and biophysical information. We present our experience in teaching an interdisciplinary course, Introduction to Bioinformatics, which was developed…
Tolvanen, Martti; Vihinen, Mauno
Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…
Light and abiotic stresses regulate the expression of GDP-L-galactose phosphorylase and levels of ascorbic acid in two kiwifruit genotypes via light-responsive and stress-inducible cis-elements in their promoters.
Li, Juan; Liang, Dong; Li, Mingjun; Ma, Fengwang
Ascorbic acid (AsA) plays an essential role in plants by protecting cells against oxidative damage. GDP-L-galactose phosphorylase (GGP) is the first committed gene for AsA synthesis. Our research examined AsA levels, regulation of GGP gene expression, and how these are related to abiotic stresses in two species of Actinidia (kiwifruit). When leaves were subjected to continuous darkness or light, ABA or MeJA, heat, or a hypoxic environment, we found some correlation between the relative levels of GGP mRNA and AsA concentrations. In transformed tobacco plants, activity of the GGP promoter was induced by all of these treatments. However, the degree of inducibility in the two kiwifruit species differed among the GGP promoter deletions. We deduced that the G-box motif, a light-responsive element, may have an important function in regulating GGP transcripts under various light conditions in both A. deliciosa and A. eriantha. Other elements such as ABRE, the CGTCA motif, and HSE might also control the promoter activities of GGP in kiwifruit. Altogether, these data suggest that GGP expression in the two kiwifruit species is regulated by light or abiotic stress via the relative cis-elements in their promoters. Furthermore, GGP has a critical role in modulating AsA concentrations in kiwifruit species under abiotic stresses.
Shanahan, Hugh P.; Owen, Anne M.; Harrison, Andrew P.
We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development. PMID:25050811
Bruhn, Russel Elton; Burton, Philip John
Data interchange bioinformatics databases will, in the future, most likely take place using extensible markup language (XML). The document structure will be described by an XML Schema rather than a document type definition (DTD). To ensure flexibility, the XML Schema must incorporate aspects of Object-Oriented Modeling. This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists. Thus, there is a need for the general bioinformatics community to be aware of the design issues relating to XML Schema. This paper, which is aimed at a general bioinformatics audience, uses examples to describe the differences between a DTD and an XML Schema and indicates how Unified Modeling Language diagrams may be used to incorporate Object-Oriented Modeling in the design of schema.
Jagadeesh Chandra Bose, R.P.; Aalst, van der W.M.P.; Nurcan, S.
Process mining techniques can be used to extract non-trivial process related knowledge and thus generate interesting insights from event logs. Similarly, bioinformatics aims at increasing the understanding of biological processes through the analysis of information associated with biological
Chen, Hsing-Yu; Hsieh, En-Jung; Cheng, Mei-Chun; Chen, Chien-Yu; Hwang, Shih-Ying; Lin, Tsan-Piao
ORA47 (octadecanoid-responsive AP2/ERF-domain transcription factor 47) of Arabidopsis thaliana is an AP2/ERF domain transcription factor that regulates jasmonate (JA) biosynthesis and is induced by methyl JA treatment. The regulatory mechanism of ORA47 remains unclear. ORA47 is shown to bind to the cis-element (NC/GT)CGNCCA, which is referred to as the O-box, in the promoter of ABI2. We proposed that ORA47 acts as a connection between ABA INSENSITIVE1 (ABI1) and ABI2 and mediates an ABI1-ORA47-ABI2 positive feedback loop. PORA47:ORA47-GFP transgenic plants were used in a chromatin immunoprecipitation (ChIP) assay to show that ORA47 participates in the biosynthesis and/or signaling pathways of nine phytohormones. Specifically, many abscisic acid (ABA) and JA biosynthesis and signaling genes were direct targets of ORA47 under stress conditions. The JA content of the P35S:ORA47-GR lines was highly induced under wounding and moderately induced under water stress relative to that of the wild-type plants. The wounding treatment moderately increased ABA accumulation in the transgenic lines, whereas the water stress treatment repressed the ABA content. ORA47 is proposed to play a role in the biosynthesis of JA and ABA and in regulating the biosynthesis and/or signaling of a suite of phytohormone genes when plants are subjected to wounding and water stress. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
van Kampen, Antoine H C; Moerland, Perry D
Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically contributes to systems medicine. First, we explain the role of bioinformatics in the management and analysis of data. In particular we show the importance of publicly available biological and clinical repositories to support systems medicine studies. Second, we discuss how the integration and analysis of multiple types of omics data through integrative bioinformatics may facilitate the determination of more predictive and robust disease signatures, lead to a better understanding of (patho)physiological molecular mechanisms, and facilitate personalized medicine. Third, we focus on network analysis and discuss how gene networks can be constructed from omics data and how these networks can be decomposed into smaller modules. We discuss how the resulting modules can be used to generate experimentally testable hypotheses, provide insight into disease mechanisms, and lead to predictive models. Throughout, we provide several examples demonstrating how bioinformatics contributes to systems medicine and discuss future challenges in bioinformatics that need to be addressed to enable the advancement of systems medicine.
Hamada, Michiaki; Kiryu, Hisanori; Iwasaki, Wataru; Asai, Kiyoshi
In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which represent many fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics. PMID:21365017
Schneider, Maria V.; Walter, Peter; Blatter, Marie-Claude
and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review...
Greene, Casey S; Tan, Jie; Ung, Matthew; Moore, Jason H; Cheng, Chao
Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. © 2014 Wiley Periodicals, Inc.
A handout used in a HUB (Heidelberg Unseminars in Bioinformatics) meeting focused on career development for bioinformaticians. It describes an activity for use to help introduce the idea of peer mentoring, potnetially acting as an opportunity to create peer-mentoring groups.
This book chapter describes the current Big Data problem in Bioinformatics and the resulting issues with performing reproducible computational research. The core of the chapter provides guidelines and summaries of current tools/techniques that a noncomputational researcher would need to learn to pe...
van Kampen, Antoine H. C.; Moerland, Perry D.
Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically
Maloney, Mark; Parker, Jeffrey; LeBlanc, Mark; Woodard, Craig T.; Glackin, Mary; Hanrahan, Michael
Recent advances involving high-throughput techniques for data generation and analysis have made familiarity with basic bioinformatics concepts and programs a necessity in the biological sciences. Undergraduate students increasingly need training in methods related to finding and retrieving information stored in vast databases. The rapid rise of…
Vaez Barzani, Ahmad
In this thesis we present an overview of bioinformatics-based approaches for genomic association mapping, with emphasis on human quantitative traits and their contribution to complex diseases. We aim to provide a comprehensive walk-through of the classic steps of genomic association mapping
Olsen, Lars Rønn; Campos, Benito; Barnkob, Mike Stein
therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes...
"The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...
Wang, Xiran; Jiang, Leiyu; Tang, Haoru
GSTF12 has always been known as a key factor of proanthocyanins accumulate in plant testa. Through bioinformatics analysis of the nucleotide and encoded protein sequence of GSTF12, it is more advantageous to the study of genes related to anthocyanin biosynthesis accumulation pathway. Therefore, we chosen GSTF12 gene of 11 kinds species, downloaded their nucleotide and protein sequence from NCBI as the research object, found strawberry GSTF12 gene via bioinformation analyse, constructed phylogenetic tree. At the same time, we analysed the strawberry GSTF12 gene of physical and chemical properties and its protein structure and so on. The phylogenetic tree showed that Strawberry and petunia were closest relative. By the protein prediction, we found that the protein owed one proper signal peptide without obvious transmembrane regions.
Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik
their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes...... to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse...
Feenstra, K. Anton; Abeln, Sanne
While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which
Attwood, Teresa K; Atwood, Teresa K; Bongcam-Rudloff, Erik; Brazas, Michelle E; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M; Schneider, Maria Victoria; van Gelder, Celia W G
In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.
Stephan, Christian; Hamacher, Michael; Blüggel, Martin; Körting, Gerhard; Chamrad, Daniel; Scheer, Christian; Marcus, Katrin; Reidegeld, Kai A; Lohaus, Christiane; Schäfer, Heike; Martens, Lennart; Jones, Philip; Müller, Michael; Auyeung, Kevin; Taylor, Chris; Binz, Pierre-Alain; Thiele, Herbert; Parkinson, David; Meyer, Helmut E; Apweiler, Rolf
The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On July 7, 2005 the members came together for the 5th time at the European Bioinformatics Institute (EBI) in Hinxton, UK, hosted by Rolf Apweiler. As a main result, the parameter set of the semi-automated data re-analysis of MS/MS spectra has been elaborated and the subsequent work steps have been defined.
Schweighofer, Karl; Pohorille, Andrew
Building on an existing prototype, we have fielded a facility with bioinformatics technologies that will help NASA meet its unique requirements for biological research. This facility consists of a cluster of computers capable of performing computationally intensive tasks, software tools, databases and knowledge management systems. Novel computational technologies for analyzing and integrating new biological data and already existing knowledge have been developed. With continued development and support, the facility will fulfill strategic NASA s bioinformatics needs in astrobiology and space exploration. . As a demonstration of these capabilities, we will present a detailed analysis of how spaceflight factors impact gene expression in the liver and kidney for mice flown aboard shuttle flight STS-108. We have found that many genes involved in signal transduction, cell cycle, and development respond to changes in microgravity, but that most metabolic pathways appear unchanged.
Ranganathan, Shoba; Tammi, Martti; Gribskov, Michael; Tan, Tin Wee
Abstract In 1998, the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5th annual conference of the Asia-...
Surangi W. Punyasena
Full Text Available Recent advances in microscopy, imaging, and data analyses have permitted both the greater application of quantitative methods and the collection of large data sets that can be used to investigate plant morphology. This special issue, the first for Applications in Plant Sciences, presents a collection of papers highlighting recent methods in the quantitative study of plant form. These emerging biometric and bioinformatic approaches to plant sciences are critical for better understanding how morphology relates to ecology, physiology, genotype, and evolutionary and phylogenetic history. From microscopic pollen grains and charcoal particles, to macroscopic leaves and whole root systems, the methods presented include automated classification and identification, geometric morphometrics, and skeleton networks, as well as tests of the limits of human assessment. All demonstrate a clear need for these computational and morphometric approaches in order to increase the consistency, objectivity, and throughput of plant morphological studies.
Scientific research in bio-informatics is often data-driven and supported by numerous biological databases. A biological database contains factual information collected from scientific experiments and computational analyses about areas including genomics, proteomics, metabolomics, microarray gene
Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan
This proceedings presents recent practical applications of Computational Biology and Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...
Transactivation of the Brassica napus napin promoter by ABI3 requires interaction of the conserved B2 and B3 domains of ABI3 with different cis-elements: B2 mediates activation through an ABRE, whereas B3 interacts with an RY/G-box.
Ezcurra, I; Wycliffe, P; Nehlin, L; Ellerström, M; Rask, L
The transcriptional activator ABI3 is a key regulator of gene expression during embryo maturation in crucifers. In monocots, the related VP1 protein regulates the Em promoter synergistically with abscisic acid (ABA). We identified cis-elements in the Brassica napus napin napA promoter mediating regulation by ABI3 and ABA, by analyzing substitution mutation constructs of napA in transgenic tobacco plantlets ectopically expressing ABI3. In transient analysis using particle bombardment of tobacco leaf sections, a tetramer of the distB ABRE (abscisic acid-responsive element) mediated transactivation by ABI3 and ABI3-dependent response to ABA, whereas a tetramer of the composite RY/G complex, containing RY repeats and a G-box, mediated only ABA-independent transactivation by ABI3. Deletion of the conserved B2 and B3 domains of ABI3 abolished transactivation of napA by ABI3. The two domains of ABI3 interact with different cis-elements: B2 is necessary for ABA-independent and ABA-dependent activations through the distB ABRE, whereas B3 interacts with the RY/G complex. Thus B2 mediates the interaction of ABI3 with the protein complex at the ABRE. The regulation of napA by ABI3 differs from Em regulation by VP1, in that the B3 domain of ABI3 is essential for the ABA-dependent regulation of napA.
Full Text Available Abstract In 1998, the Asia Pacific Bioinformatics Network (APBioNet, Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5th annual conference of the Asia-Pacific Bioinformatics Network, on Dec. 18–20, 2006 in New Delhi, India, following a series of successful events in Bangkok (Thailand, Penang (Malaysia, Auckland (New Zealand and Busan (South Korea. This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. It exemplifies a typical snapshot of the growing research excellence in bioinformatics of the region as we embark on a trajectory of establishing a solid bioinformatics research culture in the Asia Pacific that is able to contribute fully to the global bioinformatics community.
Ranganathan, Shoba; Hsu, Wen-Lian; Yang, Ueng-Cheng; Tan, Tin Wee
The 2008 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998, was organized as the 7th International Conference on Bioinformatics (InCoB), jointly with the Bioinformatics and Systems Biology in Taiwan (BIT 2008) Conference, Oct. 20-23, 2008 at Taipei, Taiwan. Besides bringing together scientists from the field of bioinformatics in this region, InCoB is actively involving researchers from the area of systems biology, to facilitate greater synergy between these two groups. Marking the 10th Anniversary of APBioNet, this InCoB 2008 meeting followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India) and Hong Kong. Additionally, tutorials and the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) immediately prior to the 20th Federation of Asian and Oceanian Biochemists and Molecular Biologists (FAOBMB) Taipei Conference provided ample opportunity for inducting mainstream biochemists and molecular biologists from the region into a greater level of awareness of the importance of bioinformatics in their craft. In this editorial, we provide a brief overview of the peer-reviewed manuscripts accepted for publication herein, grouped into thematic areas. As the regional research expertise in bioinformatics matures, the papers fall into thematic areas, illustrating the specific contributions made by APBioNet to global bioinformatics efforts.
Using a comparative genomic approach, we obtained 1797 bp of the CSN3 sequences from cattle, goat, horse, pig, rabbit and sheep. ... observed in phylogenetic tree of CSN3 gene which showed that the comparability of CSN3 gene sequences was highest between the goat and sheep and they evolved from a most recent ...
Weisstein, Anton E.
The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes—the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software—the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a ‘two-culture’ problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses. PMID:23821621
Jungck, John R; Weisstein, Anton E
The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes-the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software-the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a 'two-culture' problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses.
Weber, Tilmann; Kim, Hyun Uk
. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http...... analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work......Natural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly...
Explains the Human Genome Project (HGP) and efforts to sequence the human genome. Describes the role of bioinformatics in the project and considers it the genetics Swiss Army Knife, which has many different uses, for use in forensic science, medicine, agriculture, and environmental sciences. Discusses the use of bioinformatics in the high school…
This article describes a new approach to teaching bioinformatics using "Arabidopsis" genetic sequences. Several open-ended and inquiry-based laboratory exercises have been designed to help students grasp key concepts and gain practical skills in bioinformatics, using "Arabidopsis" leucine-rich repeat receptor-like kinase (LRR…
Heyer, Laurie J.
This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…
Bioinformatics is a scientific discipline that applies computer science and information technology to help understand biological processes. The NIH provides a list of free online bioinformatics tutorials, either generated by the NIH Library or other institutes, which includes introductory lectures and "how to" videos on using various tools.
Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.
Chakraborty, Chiranjib; George Priya Doss, C; Zhu, Hailong; Agoramoorthy, Govindasamy
Hong Kong's bioinformatics sector is attaining new heights in combination with its economic boom and the predominance of the working-age group in its population. Factors such as a knowledge-based and free-market economy have contributed towards a prominent position on the world map of bioinformatics. In this review, we have considered the educational measures, landmark research activities and the achievements of bioinformatics companies and the role of the Hong Kong government in the establishment of bioinformatics as strength. However, several hurdles remain. New government policies will assist computational biologists to overcome these hurdles and further raise the profile of the field. There is a high expectation that bioinformatics in Hong Kong will be a promising area for the next generation.
Full Text Available Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS, Software as a Service (SaaS, Platform as a Service (PaaS, and Infrastructure as a Service (IaaS, and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.
Harris, Nomi L; Cock, Peter J A; Chapman, Brad; Fields, Christopher J; Hokamp, Karsten; Lapp, Hilmar; Muñoz-Torres, Monica; Wiencko, Heather
Message from the ISCB: The Bioinformatics Open Source Conference (BOSC) is a yearly meeting organized by the Open Bioinformatics Foundation (OBF), a non-profit group dedicated to promoting the practice and philosophy of Open Source software development and Open Science within the biological research community. BOSC has been run since 2000 as a two-day Special Interest Group (SIG) before the annual ISMB conference. The 17th annual BOSC ( http://www.open-bio.org/wiki/BOSC_2016) took place in Orlando, Florida in July 2016. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community. The conference brought together nearly 100 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, and open and reproducible science.
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. 2012 Dai et al.; licensee BioMed Central Ltd.
Dai, Lin; Gao, Xin; Guo, Yan; Xiao, Jingfa; Zhang, Zhang
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.
Ménager, Hervé; Kalaš, Matúš; Rapacki, Kristoffer
The diversity and complexity of bioinformatics resources presents significant challenges to their localisation, deployment and use, creating a need for reliable systems that address these issues. Meanwhile, users demand increasingly usable and integrated ways to access and analyse data, especially......, a software component that will ease the integration of bioinformatics resources in a workbench environment, using their description provided by the existing ELIXIR Tools and Data Services Registry....
Fufezan, Christian; Specht, Michael
High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files). p3d's strength arises from the combination of a) very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP) tree, b) set theory and c) functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.
Full Text Available Abstract Background High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. Results p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files. p3d's strength arises from the combination of a very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP tree, b set theory and c functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. Conclusion p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.
Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi
Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
Segun A Fatumo
Full Text Available Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
Römer, Michael; Eichner, Johannes; Dräger, Andreas; Wrzodek, Clemens; Wrzodek, Finja; Zell, Andreas
Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT) Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/.
Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong
In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.
Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen
Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data.  Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.
Bioinformatics is an emerging scientific discipline that uses information ... complex biological questions. ... and computer programs for various purposes of primer ..... polymerase chain reaction: Human Immunodeficiency Virus 1 model studies.
Mudasser Fraz Wyne
Full Text Available Bioinformatics is a new field that is poorly served by any of the traditional science programs in Biology, Computer science or Biochemistry. Known to be a rapidly evolving discipline, Bioinformatics has emerged from experimental molecular biology and biochemistry as well as from the artificial intelligence, database, pattern recognition, and algorithms disciplines of computer science. While institutions are responding to this increased demand by establishing graduate programs in bioinformatics, entrance barriers for these programs are high, largely due to the significant prerequisite knowledge which is required, both in the fields of biochemistry and computer science. Although many schools currently have or are proposing graduate programs in bioinformatics, few are actually developing new undergraduate programs. In this paper I explore the blend of a multidisciplinary approach, discuss the response of academia and highlight challenges faced by this emerging field.
Melero, Juan L; Andrades, Sergi; Arola, Lluís; Romeu, Antoni
Psoriasis is an immune-mediated, inflammatory and hyperproliferative disease of the skin and joints. The cause of psoriasis is still unknown. The fundamental feature of the disease is the hyperproliferation of keratinocytes and the recruitment of cells from the immune system in the region of the affected skin, which leads to deregulation of many well-known gene expressions. Based on data mining and bioinformatic scripting, here we show a new dimension of the effect of psoriasis at the genomic level. Using our own pipeline of scripts in Perl and MySql and based on the freely available NCBI Gene Expression Omnibus (GEO) database: DataSet Record GDS4602 (Series GSE13355), we explore the extent of the effect of psoriasis on gene expression in the affected tissue. We give greater insight into the effects of psoriasis on the up-regulation of some genes in the cell cycle (CCNB1, CCNA2, CCNE2, CDK1) or the dynamin system (GBPs, MXs, MFN1), as well as the down-regulation of typical antioxidant genes (catalase, CAT; superoxide dismutases, SOD1-3; and glutathione reductase, GSR). We also provide a complete list of the human genes and how they respond in a state of psoriasis. Our results show that psoriasis affects all chromosomes and many biological functions. If we further consider the stable and mitotically inheritable character of the psoriasis phenotype, and the influence of environmental factors, then it seems that psoriasis has an epigenetic origin. This fit well with the strong hereditary character of the disease as well as its complex genetic background. Copyright © 2017 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.
Atwood, Teresa K.; Bongcam-Rudloff, Erik; Brazas, Michelle E.; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M.; Schneider, Maria Victoria; van Gelder, Celia W. G.
In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all. PMID:25856076
Oshita, Kazuki; Arakawa, Kazuharu; Tomita, Masaru
The availability of bioinformatics web-based services is rapidly proliferating, for their interoperability and ease of use. The next challenge is in the integration of these services in the form of workflows, and several projects are already underway, standardizing the syntax, semantics, and user interfaces. In order to deploy the advantages of web services with locally installed tools, here we describe a collection of proxy client tools for 42 major bioinformatics web services in the form of European Molecular Biology Open Software Suite (EMBOSS) UNIX command-line tools. EMBOSS provides sophisticated means for discoverability and interoperability for hundreds of tools, and our package, named the Keio Bioinformatics Web Service (KBWS), adds functionalities of local and multiple alignment of sequences, phylogenetic analyses, and prediction of cellular localization of proteins and RNA secondary structures. This software implemented in C is available under GPL from http://www.g-language.org/kbws/ and GitHub repository http://github.com/cory-ko/KBWS. Users can utilize the SOAP services implemented in Perl directly via WSDL file at http://soap.g-language.org/kbws.wsdl (RPC Encoded) and http://soap.g-language.org/kbws_dl.wsdl (Document/literal).
Full Text Available Abstract The availability of bioinformatics web-based services is rapidly proliferating, for their interoperability and ease of use. The next challenge is in the integration of these services in the form of workflows, and several projects are already underway, standardizing the syntax, semantics, and user interfaces. In order to deploy the advantages of web services with locally installed tools, here we describe a collection of proxy client tools for 42 major bioinformatics web services in the form of European Molecular Biology Open Software Suite (EMBOSS UNIX command-line tools. EMBOSS provides sophisticated means for discoverability and interoperability for hundreds of tools, and our package, named the Keio Bioinformatics Web Service (KBWS, adds functionalities of local and multiple alignment of sequences, phylogenetic analyses, and prediction of cellular localization of proteins and RNA secondary structures. This software implemented in C is available under GPL from http://www.g-language.org/kbws/ and GitHub repository http://github.com/cory-ko/KBWS. Users can utilize the SOAP services implemented in Perl directly via WSDL file at http://soap.g-language.org/kbws.wsdl (RPC Encoded and http://soap.g-language.org/kbws_dl.wsdl (Document/literal.
The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.
Mulder, Nicola J; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Ahmed, Azza; Ahmed, Rehab; Akanle, Bola; Alibi, Mohamed; Armstrong, Don L; Aron, Shaun; Ashano, Efejiro; Baichoo, Shakuntala; Benkahla, Alia; Brown, David K; Chimusa, Emile R; Fadlelmola, Faisal M; Falola, Dare; Fatumo, Segun; Ghedira, Kais; Ghouila, Amel; Hazelhurst, Scott; Isewon, Itunuoluwa; Jung, Segun; Kassim, Samar Kamal; Kayondo, Jonathan K; Mbiyavanga, Mamana; Meintjes, Ayton; Mohammed, Somia; Mosaku, Abayomi; Moussa, Ahmed; Muhammd, Mustafa; Mungloo-Dilmohamud, Zahra; Nashiru, Oyekanmi; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Osamor, Victor; Oyelade, Jellili; Sadki, Khalid; Salifu, Samson Pandam; Soyemi, Jumoke; Panji, Sumir; Radouani, Fouzia; Souiai, Oussama; Tastan Bishop, Özlem
Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for
Sirintrapun, S Joseph; Zehir, Ahmet; Syed, Aijazuddin; Gao, JianJiong; Schultz, Nikolaus; Cheng, Donavan T
Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease. This article details 3 projects that are hybrid applications of translational bioinformatics and clinical research (biomedical) informatics: The Cancer Genome Atlas, the cBioPortal for Cancer Genomics, and the Memorial Sloan Kettering Cancer Center clinical variants and results database, all designed to facilitate insights into cancer biology and clinical/therapeutic correlations. Copyright © 2015 Elsevier Inc. All rights reserved.
Papanicolaou, Alexie; Heckel, David G.
Motivation: Next-generation sequencing technologies have led to the widespread use of -omic applications. As a result, there is now a pronounced bioinformatic bottleneck. The general model organism database (GMOD) tool kit (http://gmod.org) has produced a number of resources aimed at addressing this issue. It lacks, however, a robust online solution that can deploy heterogeneous data and software within a Web content management system (CMS). Results: We present a bioinformatic framework for the Drupal CMS. It consists of three modules. First, GMOD-DBSF is an application programming interface module for the Drupal CMS that simplifies the programming of bioinformatic Drupal modules. Second, the Drupal Bioinformatic Software Bench (biosoftware_bench) allows for a rapid and secure deployment of bioinformatic software. An innovative graphical user interface (GUI) guides both use and administration of the software, including the secure provision of pre-publication datasets. Third, we present genes4all_experiment, which exemplifies how our work supports the wider research community. Conclusion: Given the infrastructure presented here, the Drupal CMS may become a powerful new tool set for bioinformaticians. The GMOD-DBSF base module is an expandable community resource that decreases development time of Drupal modules for bioinformatics. The biosoftware_bench module can already enhance biologists' ability to mine their own data. The genes4all_experiment module has already been responsible for archiving of more than 150 studies of RNAi from Lepidoptera, which were previously unpublished. Availability and implementation: Implemented in PHP and Perl. Freely available under the GNU Public License 2 or later from http://gmod-dbsf.googlecode.com Contact: firstname.lastname@example.org PMID:20971988
Papanicolaou, Alexie; Heckel, David G
Next-generation sequencing technologies have led to the widespread use of -omic applications. As a result, there is now a pronounced bioinformatic bottleneck. The general model organism database (GMOD) tool kit (http://gmod.org) has produced a number of resources aimed at addressing this issue. It lacks, however, a robust online solution that can deploy heterogeneous data and software within a Web content management system (CMS). We present a bioinformatic framework for the Drupal CMS. It consists of three modules. First, GMOD-DBSF is an application programming interface module for the Drupal CMS that simplifies the programming of bioinformatic Drupal modules. Second, the Drupal Bioinformatic Software Bench (biosoftware_bench) allows for a rapid and secure deployment of bioinformatic software. An innovative graphical user interface (GUI) guides both use and administration of the software, including the secure provision of pre-publication datasets. Third, we present genes4all_experiment, which exemplifies how our work supports the wider research community. Given the infrastructure presented here, the Drupal CMS may become a powerful new tool set for bioinformaticians. The GMOD-DBSF base module is an expandable community resource that decreases development time of Drupal modules for bioinformatics. The biosoftware_bench module can already enhance biologists' ability to mine their own data. The genes4all_experiment module has already been responsible for archiving of more than 150 studies of RNAi from Lepidoptera, which were previously unpublished. Implemented in PHP and Perl. Freely available under the GNU Public License 2 or later from http://gmod-dbsf.googlecode.com.
Abu-Jamous, Basel; Nandi, Asoke K
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
reaction (PCR), oligo hybridization and DNA sequencing. Proper primer design is actually one of the most important factors/steps in successful DNA sequencing. Various bioinformatics programs are available for selection of primer pairs from a template sequence. The plethora programs for PCR primer design reflects the.
Kelley, Scott; Alger, Christianna; Deutschman, Douglas
The importance of Bioinformatics tools and methodology in modern biological research underscores the need for robust and effective courses at the college level. This paper describes such a course designed on the principles of cooperative learning based on a computer software industry production model called "Extreme Programming" (EP).…
Ondrej, Vladan; Dvorak, Petr
Bioinformatics, biological databases, and the worldwide use of computers have accelerated biological research in many fields, such as evolutionary biology. Here, we describe a primer of nucleotide sequence management and the construction of a phylogenetic tree with two examples; the two selected are from completely different groups of organisms:…
Nielsen, Henrik; Sperotto, Maria Maddalena
)-based bioinformatics approach. The ANN was trained to recognize feature-based patterns in proteins that are considered to be associated with lipid rafts. The trained ANN was then used to predict protein raftophilicity. We found that, in the case of α-helical membrane proteins, their hydrophobic length does not affect...
Boyle, John A.
Bioinformatics has emerged as an important research tool in recent years. The ability to mine large databases for relevant information has become increasingly central to many different aspects of biochemistry and molecular biology. It is important that undergraduates be introduced to the available information and methodologies. We present a…
Computational workflows in bioinformatics are becoming increasingly important in the achievement of scientific advances. These workflows typically require the integrated use of multiple, distributed data sources and analytic tools. The BioExtract Server (http://bioextract.org) is a distributed servi...
In recent years, new bioinformatics technologies, such as gene expression microarray, genome-wide association study, proteomics, and metabolomics, have been widely used to simultaneously identify a huge number of human genomic/genetic biomarkers, generate a tremendously large amount of data, and dramatically increase the knowledge on human…
Belmann, Peter; Dröge, Johannes; Bremges, Andreas; McHardy, Alice C; Sczyrba, Alexander; Barton, Michael D
Software is now both central and essential to modern biology, yet lack of availability, difficult installations, and complex user interfaces make software hard to obtain and use. Containerisation, as exemplified by the Docker platform, has the potential to solve the problems associated with sharing software. We propose bioboxes: containers with standardised interfaces to make bioinformatics software interchangeable.
Thus, there is the need for appropriate strategies of introducing the basic components of this emerging scientific field to part of the African populace through the development of an online distance education learning tool. This study involved the design of a bioinformatics online distance educative tool an implementation of ...
Biological databases are having a growth spurt. Much of this results from research in genetics and biodiversity, coupled with fast-paced developments in information technology. The revolution in bioinformatics, defined by Sugden and Pennisi (2000) as the "tools and techniques for...
Bartlett, Joan C.; Ishimura, Yusuke; Kloda, Lorie A.
Purpose: The objective was to identify and understand the factors involved in scientists' selection of preferred bioinformatics tools, such as databases of gene or protein sequence information (e.g., GenBank) or programs that manipulate and analyse biological data (e.g., BLAST). Methods: Eight scientists maintained research diaries for a two-week…
Rideout, Jai Ram; Chase, John H; Bolyen, Evan; Ackermann, Gail; González, Antonio; Knight, Rob; Caporaso, J Gregory
Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are
Poe, D.; Venkatraman, N.; Hansen, C.; Singh, G.
There is an increasing need for an effective method of teaching bioinformatics. Increased progress and availability of computer-based tools for educating students have led to the implementation of a computer-based system for teaching bioinformatics as described in this paper. Bioinformatics is a recent, hybrid field of study combining elements of…
Luscombe, N M; Greenbaum, D; Gerstein, M
The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.
Full Text Available Cloud computing has started to change the way how bioinformatics research is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. The variability in data volume results in variable computing requirements. Therefore, bioinformatics researchers are pursuing more reliable and efficient methods for conducting sequencing analyses. This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. Experimental results show that G2LC guarantees the application performance, while resource is saved up to 20.14%.
Schönbach, Christian; Verma, Chandra; Bond, Peter J; Ranganathan, Shoba
The International Conference on Bioinformatics (InCoB) has been publishing peer-reviewed conference papers in BMC Bioinformatics since 2006. Of the 44 articles accepted for publication in supplement issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics and BMC Systems Biology, 24 articles with a bioinformatics or systems biology focus are reviewed in this editorial. InCoB2017 is scheduled to be held in Shenzen, China, September 20-22, 2017.
Full Text Available Flavivirus infections are the most prevalent arthropod-borne infections world wide, often causing severe disease especially among children, the elderly, and the immunocompromised. In the absence of effective antiviral treatment, prevention through vaccination would greatly reduce morbidity and mortality associated with flavivirus infections. Despite the success of the empirically developed vaccines against yellow fever virus, Japanese encephalitis virus and tick-borne encephalitis virus, there is an increasing need for a more rational design and development of safe and effective vaccines. Several bioinformatic tools are available to support such rational vaccine design. In doing so, several parameters have to be taken into account, such as safety for the target population, overall immunogenicity of the candidate vaccine, and efficacy and longevity of the immune responses triggered. Examples of how bio-informatics is applied to assist in the rational design and improvements of vaccines, particularly flavivirus vaccines, are presented and discussed.
Christopher L Williams
Full Text Available Objective: Within the information technology (IT industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise′s overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Context: Bioinformatics relies on nimble IT framework which can adapt to changing requirements. Aims: To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics Conclusions: Use of the microservices framework
Williams, Christopher L; Sica, Jeffrey C; Killen, Robert T; Balis, Ulysses G J
Within the information technology (IT) industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise's overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Bioinformatics relies on nimble IT framework which can adapt to changing requirements. To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics. Use of the microservices framework is an effective methodology for the fabrication and
Williams, Christopher L.; Sica, Jeffrey C.; Killen, Robert T.; Balis, Ulysses G. J.
Objective: Within the information technology (IT) industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise's overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Context: Bioinformatics relies on nimble IT framework which can adapt to changing requirements. Aims: To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics Conclusions: Use of the microservices framework is an effective
Kunz, Meik; Xiao, Ke; Liang, Chunguang; Viereck, Janika; Pachel, Christina; Frantz, Stefan; Thum, Thomas; Dandekar, Thomas
MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs and are highly conserved among species. Moreover, miRNAs regulate gene expression of a large number of genes associated with important biological functions and signaling pathways. Recently, several miRNAs have been found to be associated with cardiovascular diseases. Thus, investigating the complex regulatory effect of miRNAs may lead to a better understanding of their functional role in the heart. To achieve this, bioinformatics approaches have to be coupled with validation and screening experiments to understand the complex interactions of miRNAs with the genome. This will boost the subsequent development of diagnostic markers and our understanding of the physiological and therapeutic role of miRNAs in cardiac remodeling. In this review, we focus on and explain different bioinformatics strategies and algorithms for the identification and analysis of miRNAs and their regulatory elements to better understand cardiac miRNA biology. Starting with the biogenesis of miRNAs, we present approaches such as LocARNA and miRBase for combining sequence and structure analysis including phylogenetic comparisons as well as detailed analysis of RNA folding patterns, functional target prediction, signaling pathway as well as functional analysis. We also show how far bioinformatics helps to tackle the unprecedented level of complexity and systemic effects by miRNA, underlining the strong therapeutic potential of miRNA and miRNA target structures in cardiovascular disease. In addition, we discuss drawbacks and limitations of bioinformatics algorithms and the necessity of experimental approaches for miRNA target identification. This article is part of a Special Issue entitled 'Non-coding RNAs'. Copyright © 2014 Elsevier Ltd. All rights reserved.
Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets
Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter
Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly
Ma, Shuangge; Huang, Jian
In bioinformatics studies, supervised classification with high-dimensional input variables is frequently encountered. Examples routinely arise in genomic, epigenetic and proteomic studies. Feature selection can be employed along with classifier construction to avoid over-fitting, to generate more reliable classifier and to provide more insights into the underlying causal relationships. In this article, we provide a review of several recently developed penalized feature selection and classific...
Schneider, M.V.; Watson, J.; Attwood, T.
As bioinformatics becomes increasingly central to research in the molecular life sciences, the need to train non-bioinformaticians to make the most of bioinformatics resources is growing. Here, we review the key challenges and pitfalls to providing effective training for users of bioinformatics...... services, and discuss successful training strategies shared by a diverse set of bioinformatics trainers. We also identify steps that trainers in bioinformatics could take together to advance the state of the art in current training practices. The ideas presented in this article derive from the first...
Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H
Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. © The Author 2015. Published by Oxford University Press.
Robson da Silva Lopes
Full Text Available Bioinformatics and other well-established sciences, such as molecular biology, genetics, and biochemistry, provide a scientific approach for the analysis of data generated through “omics” projects that may be used in studies of chronobiology. The results of studies that apply these techniques demonstrate how they significantly aided the understanding of chronobiology. However, bioinformatics tools alone cannot eliminate the need for an understanding of the field of research or the data to be considered, nor can such tools replace analysts and researchers. It is often necessary to conduct an evaluation of the results of a data mining effort to determine the degree of reliability. To this end, familiarity with the field of investigation is necessary. It is evident that the knowledge that has been accumulated through chronobiology and the use of tools derived from bioinformatics has contributed to the recognition and understanding of the patterns and biological rhythms found in living organisms. The current work aims to develop new and important applications in the near future through chronobiology research.
Cohen, K Bretonnel; Hunter, Lawrence E
Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.
Zhang, Zhang; Cheung, Kei-Hoi; Townsend, Jeffrey P
Enabling deft data integration from numerous, voluminous and heterogeneous data sources is a major bioinformatic challenge. Several approaches have been proposed to address this challenge, including data warehousing and federated databasing. Yet despite the rise of these approaches, integration of data from multiple sources remains problematic and toilsome. These two approaches follow a user-to-computer communication model for data exchange, and do not facilitate a broader concept of data sharing or collaboration among users. In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learning platform in education. We discuss lessons from information technology, predict the next generation of Web (Web 3.0), and describe its potential impact on the future of bioinformatics studies.
Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.
Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469
Flanagan Keith; Nakjang Sirintra; Hallinan Jennifer; Harwood Colin; Hirt Robert P.; Pocock Matthew R.; Wipat Anil
As bioinformatics datasets grow ever larger, and analyses become increasingly complex, there is a need for data handling infrastructures to keep pace with developing technology. One solution is to apply Grid and Cloud technologies to address the computational requirements of analysing high throughput datasets. We present an approach for writing new, or wrapping existing applications, and a reference implementation of a framework, Microbase2.0, for executing those applications using Grid and C...
Arredondo, Tomás; Ormazábal, Wladimir
This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.
Gu, Peiqin; Chen, Huajun
Traditional Chinese medicine (TCM) is gaining increasing attention with the emergence of integrative medicine and personalized medicine, characterized by pattern differentiation on individual variance and treatments based on natural herbal synergism. Investigating the effectiveness and safety of the potential mechanisms of TCM and the combination principles of drug therapies will bridge the cultural gap with Western medicine and improve the development of integrative medicine. Dealing with rapidly growing amounts of biomedical data and their heterogeneous nature are two important tasks among modern biomedical communities. Bioinformatics, as an emerging interdisciplinary field of computer science and biology, has become a useful tool for easing the data deluge pressure by automating the computation processes with informatics methods. Using these methods to retrieve, store and analyze the biomedical data can effectively reveal the associated knowledge hidden in the data, and thus promote the discovery of integrated information. Recently, these techniques of bioinformatics have been used for facilitating the interactional effects of both Western medicine and TCM. The analysis of TCM data using computational technologies provides biological evidence for the basic understanding of TCM mechanisms, safety and efficacy of TCM treatments. At the same time, the carrier and targets associated with TCM remedies can inspire the rethinking of modern drug development. This review summarizes the significant achievements of applying bioinformatics techniques to many aspects of the research in TCM, such as analysis of TCM-related '-omics' data and techniques for analyzing biological processes and pharmaceutical mechanisms of TCM, which have shown certain potential of bringing new thoughts to both sides. © The Author 2013. Published by Oxford University Press. For Permissions, please email: email@example.com.
Handl, Julia; Kell, Douglas B; Knowles, Joshua
This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.
Lue, Jaw-Chyng L.; Fang, Wai-Chi
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
The general audience for these lectures is mainly physicists, computer scientists, engineers or the general public wanting to know more about what’s going on in the biosciences. What’s bioinformatics and why is all this fuss being made about it ? What’s this revolution triggered by the human genome project ? Are there any results yet ? What are the problems ? What new avenues of research have been opened up ? What about the technology ? These new developments will be compared with what happened at CERN earlier in its evolution, and it is hoped that the similiraties and contrasts will stimulate new curiosity and provoke new thoughts.
Magana, Alejandra J.; Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari
Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the…
He, Yongqun; Xiang, Zuoshuang
Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Bioinformatics curation and ontological representation of Brucella vaccines
Williams, Jennifer M; Mangan, Mary E; Perreault-Micale, Cynthia; Lathe, Scott; Sirohi, Neeraj; Lathe, Warren C
The amount of biological data is increasing rapidly, and will continue to increase as new rapid technologies are developed. Professionals in every area of bioscience will have data management needs that require publicly available bioinformatics resources. Not all scientists desire a formal bioinformatics education but would benefit from more informal educational sources of learning. Effective bioinformatics education formats will address a broad range of scientific needs, will be aimed at a variety of user skill levels, and will be delivered in a number of different formats to address different learning styles. Informal sources of bioinformatics education that are effective are available, and will be explored in this review.
Wen, Feng; Zhu, Hong; Li, Peng; Jiang, Min; Mao, Wenqing; Ong, Chermaine; Chu, Zhaoqing
Members of plant WRKY gene family are ancient transcription factors that function in plant growth and development and respond to biotic and abiotic stresses. In our present study, we have investigated WRKY family genes in Brachypodium distachyon, a new model plant of family Poaceae. We identified a total of 86 WRKY genes from B. distachyon and explored their chromosomal distribution and evolution, domain alignment, promoter cis-elements, and expression profiles. Combining the analysis of phylogenetic tree of BdWRKY genes and the result of expression profiling, results showed that most of clustered gene pairs had higher similarities in the WRKY domain, suggesting that they might be functionally redundant. Neighbour-joining analysis of 301 WRKY domains from Oryza sativa, Arabidopsis thaliana, and B. distachyon suggested that BdWRKY domains are evolutionarily more closely related to O. sativa WRKY domains than those of A. thaliana. Moreover, tissue-specific expression profile of BdWRKY genes and their responses to phytohormones and several biotic or abiotic stresses were analysed by quantitative real-time PCR. The results showed that the expression of BdWRKY genes was rapidly regulated by stresses and phytohormones, and there was a strong correlation between promoter cis-elements and the phytohormones-induced BdWRKY gene expression. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
Accardi, L.; Freudenberg, Wolfgang; Ohya, Masanori
/ H. Kamimura -- Massive collection of full-length complementary DNA clones and microarray analyses: keys to rice transcriptome analysis / S. Kikuchi -- Changes of influenza A(H5) viruses by means of entropic chaos degree / K. Sato and M. Ohya -- Basics of genome sequence analysis in bioinformatics - its fundamental ideas and problems / T. Suzuki and S. Miyazaki -- A basic introduction to gene expression studies using microarray expression data analysis / D. Wanke and J. Kilian -- Integrating biological perspectives: a quantum leap for microarray expression analysis / D. Wanke ... [et al.].
Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H
Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European
Full Text Available The emergence of next-generation sequencing (NGS platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a large number of softwares already exist for analyzing NGS data. These tools can be fit into many general categories including alignment of sequence reads to a reference, base-calling and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection and genome browsing. This manuscript aims to guide readers in the choice of the available computational tools that can be used to face the several steps of the data analysis workflow.
Yukinawa, N; Ishii, S; Takenouchi, T; Oba, S
Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods
Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H
The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.
ACADEMIC TRAINING LECTURE SERIES 27, 28 February 1, 2, 3 March 2006 from 11:00 to 12:00 - Auditorium, bldg. 500 Decoding the Genome A special series of 5 lectures on: Recent extraordinary advances in the life sciences arising through new detection technologies and bioinformatics The past five years have seen an extraordinary change in the information and tools available in the life sciences. The sequencing of the human genome, the discovery that we possess far fewer genes than foreseen, the measurement of the tiny changes in the genomes that differentiate us, the sequencing of the genomes of many pathogens that lead to diseases such as malaria are all examples of completely new information that is now available in the quest for improved healthcare. New tools have allowed similar strides in the discovery of the associated protein structures, providing invaluable information for those searching for new drugs. New DNA microarray chips permit simultaneous measurement of the state of expression of tens...
Ramlo, Susan E.; McConnell, David; Duan, Zhong-Hui; Moore, Francisco B.
Faculty at a Midwestern metropolitan public university recently developed a course on bioinformatics that emphasized collaboration and inquiry. Bioinformatics, essentially the application of computational tools to biological data, is inherently interdisciplinary. Thus part of the challenge of creating this course was serving the needs and…
Jungck, John R; Donovan, Samuel S; Weisstein, Anton E; Khiripet, Noppadon; Everse, Stephen J
Bioinformatics is central to biology education in the 21st century. With the generation of terabytes of data per day, the application of computer-based tools to stored and distributed data is fundamentally changing research and its application to problems in medicine, agriculture, conservation and forensics. In light of this 'information revolution,' undergraduate biology curricula must be redesigned to prepare the next generation of informed citizens as well as those who will pursue careers in the life sciences. The BEDROCK initiative (Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting together) has fostered an international community of bioinformatics educators. The initiative's goals are to: (i) Identify and support faculty who can take leadership roles in bioinformatics education; (ii) Highlight and distribute innovative approaches to incorporating evolutionary bioinformatics data and techniques throughout undergraduate education; (iii) Establish mechanisms for the broad dissemination of bioinformatics resource materials and teaching models; (iv) Emphasize phylogenetic thinking and problem solving; and (v) Develop and publish new software tools to help students develop and test evolutionary hypotheses. Since 2002, BEDROCK has offered more than 50 faculty workshops around the world, published many resources and supported an environment for developing and sharing bioinformatics education approaches. The BEDROCK initiative builds on the established pedagogical philosophy and academic community of the BioQUEST Curriculum Consortium to assemble the diverse intellectual and human resources required to sustain an international reform effort in undergraduate bioinformatics education.
Bioinformatics is an interdisciplinary subject, which uses computer application, statistics, mathematics and engineering for the analysis and management of biological information. It has become an important tool for basic and applied research in veterinary sciences. Bioinformatics has brought about advancements into ...
Life sciences research and development has opened up new challenges and opportunities for bioinformatics. The contribution of bioinformatics advances made possible the mapping of the entire human genome and genomes of many other organisms in just over a decade. These discoveries, along with current efforts to ...
Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…
Howard, David R.; Miskowski, Jennifer A.; Grunwald, Sandra K.; Abler, Michael L.
At the University of Wisconsin-La Crosse, we have undertaken a program to integrate the study of bioinformatics across the undergraduate life science curricula. Our efforts have included incorporating bioinformatics exercises into courses in the biology, microbiology, and chemistry departments, as well as coordinating the efforts of faculty within…
Bioinformatics has advanced the course of research and future veterinary vaccines development because it has provided new tools for identification of vaccine targets from sequenced biological data of organisms. In Nigeria, there is lack of bioinformatics training in the universities, expect for short training courses in which ...
The main bottleneck in advancing genomics in present times is the lack of expertise in using bioinformatics tools and approaches for data mining in raw DNA sequences generated by modern high throughput technologies such as next generation sequencing. Although bioinformatics has been making major progress and ...
Harris, Nomi L; Cock, Peter J A; Lapp, Hilmar; Chapman, Brad; Davey, Rob; Fields, Christopher; Hokamp, Karsten; Munoz-Torres, Monica
The Bioinformatics Open Source Conference (BOSC) is organized by the Open Bioinformatics Foundation (OBF), a nonprofit group dedicated to promoting the practice and philosophy of open source software development and open science within the biological research community. Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community. BOSC offers a focused environment for developers and users to interact and share ideas about standards; software development practices; practical techniques for solving bioinformatics problems; and approaches that promote open science and sharing of data, results, and software. BOSC is run as a two-day special interest group (SIG) before the annual Intelligent Systems in Molecular Biology (ISMB) conference. BOSC 2015 took place in Dublin, Ireland, and was attended by over 125 people, about half of whom were first-time attendees. Session topics included "Data Science;" "Standards and Interoperability;" "Open Science and Reproducibility;" "Translational Bioinformatics;" "Visualization;" and "Bioinformatics Open Source Project Updates". In addition to two keynote talks and dozens of shorter talks chosen from submitted abstracts, BOSC 2015 included a panel, titled "Open Source, Open Door: Increasing Diversity in the Bioinformatics Open Source Community," that provided an opportunity for open discussion about ways to increase the diversity of participants in BOSC in particular, and in open source bioinformatics in general. The complete program of BOSC 2015 is available online at http://www.open-bio.org/wiki/BOSC_2015_Schedule.
When bioinformatics education is considered, several issues are addressed. At the undergraduate level, the main issue revolves around conveying information from two main and different fields: biology and computer science. At the graduate level, the main issue is bridging the gap between biology students and computer science students. However, there is an educational component that is rarely addressed within the context of bioinformatics education: the ethics component. Here, a different perspective is provided on bioinformatics education, and the current status of ethics is analyzed within the existing bioinformatics programs. Analysis of the existing undergraduate and graduate programs, in both Europe and the United States, reveals the minimal attention given to ethics within bioinformatics education. Given that bioinformaticians speedily and effectively shape the biomedical sciences and hence their implications for society, here redesigning of the bioinformatics curricula is suggested in order to integrate the necessary ethics education. Unique ethical problems awaiting bioinformaticians and bioinformatics ethics as a separate field of study are discussed. In addition, a template for an "Ethics in Bioinformatics" course is provided.
Full Text Available Abstract Background Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. Results To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'. A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption. An add-on module ('NuBio' facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures and functionality (e.g., to parse/write standard file formats. Conclusions PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and
Barker, Daniel; Ferrier, David Ek; Holland, Peter Wh; Mitchell, John Bo; Plaisier, Heleen; Ritchie, Michael G; Smart, Steven D
Teaching bioinformatics at universities is complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. For a future career in biology or bioinformatics, the installation of software is a useful skill. We propose that this may be taught by running the course on GNU/Linux running on inexpensive Raspberry Pi computer hardware, for which students may be granted full administrator access. We release 4273π, an operating system image for Raspberry Pi based on Raspbian Linux. This includes minor customisations for classroom use and includes our Open Access bioinformatics course, 4273π Bioinformatics for Biologists. This is based on the final-year undergraduate module BL4273, run on Raspberry Pi computers at the University of St Andrews, Semester 1, academic year 2012-2013. 4273π is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost.
Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu
Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.
Mulder, Nicola; Schwartz, Russell; Brazas, Michelle D; Brooksbank, Cath; Gaeta, Bruno; Morgan, Sarah L; Pauley, Mark A; Rosenwald, Anne; Rustici, Gabriella; Sierk, Michael; Warnow, Tandy; Welch, Lonnie
Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.
Brooksbank, Cath; Morgan, Sarah L.; Rosenwald, Anne; Warnow, Tandy; Welch, Lonnie
Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans. PMID:29390004
Ranganathan, Shoba; Gribskov, Michael; Tan, Tin Wee
We provide a 2007 update on the bioinformatics research in the Asia-Pacific from the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998. From 2002, APBioNet has organized the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2007 Conference was organized as the 6th annual conference of the Asia-Pacific Bioinformatics Network, on Aug. 27-30, 2007 at Hong Kong, following a series of successful events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea) and New Delhi (India). Besides a scientific meeting at Hong Kong, satellite events organized are a pre-conference training workshop at Hanoi, Vietnam and a post-conference workshop at Nansha, China. This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. We have organized the papers into thematic areas, highlighting the growing contribution of research excellence from this region, to global bioinformatics endeavours.
Brazas, Michelle D; Ouellette, B F Francis
Bioinformatics.ca has been hosting continuing education programs in introductory and advanced bioinformatics topics in Canada since 1999 and has trained more than 2,000 participants to date. These workshops have been adapted over the years to keep pace with advances in both science and technology as well as the changing landscape in available learning modalities and the bioinformatics training needs of our audience. Post-workshop surveys have been a mandatory component of each workshop and are used to ensure appropriate adjustments are made to workshops to maximize learning. However, neither bioinformatics.ca nor others offering similar training programs have explored the long-term impact of bioinformatics continuing education training. Bioinformatics.ca recently initiated a look back on the impact its workshops have had on the career trajectories, research outcomes, publications, and collaborations of its participants. Using an anonymous online survey, bioinformatics.ca analyzed responses from those surveyed and discovered its workshops have had a positive impact on collaborations, research, publications, and career progression.
Full Text Available ABSTRACT:The traditional methods for mining foods for bioactive peptides are tedious and long. Similar to the drug industry, the length of time to identify and deliver a commercial health ingredient that reduces disease symptoms can take anything between 5 to 10 years. Reducing this time and effort is crucial in order to create new commercially viable products with clear and important health benefits. In the past few years, bioinformatics, the science that brings together fast computational biology, and efficient genome mining, is appearing as the long awaited solution to this problem. By quickly mining food genomes for characteristics of certain food therapeutic ingredients, researchers can potentially find new ones in a matter of a few weeks. Yet, surprisingly, very little success has been achieved so far using bioinformatics in mining for food bioactives.The absence of food specific bioinformatic mining tools, the slow integration of both experimental mining and bioinformatics, and the important difference between different experimental platforms are some of the reasons for the slow progress of bioinformatics in the field of functional food and more specifically in bioactive peptide discovery.In this paper I discuss some methods that could be easily translated, using a rational peptide bioinformatics design, to food bioactive peptide mining. I highlight the need for an integrated food peptide database. I also discuss how to better integrate experimental work with bioinformatics in order to improve the mining of food for bioactive peptides, therefore achieving a higher success rates.
Suciu, Radu M; Aydin, Emir; Chen, Brian E
With the exponential increase and widespread availability of genomic, transcriptomic, and proteomic data, accessing these '-omics' data is becoming increasingly difficult. The current resources for accessing and analyzing these data have been created to perform highly specific functions intended for specialists, and thus typically emphasize functionality over user experience. We have developed a web-based application, GeneDig.org, that allows any general user access to genomic information with ease and efficiency. GeneDig allows for searching and browsing genes and genomes, while a dynamic navigator displays genomic, RNA, and protein information simultaneously for co-navigation. We demonstrate that our application allows more than five times faster and efficient access to genomic information than any currently available methods. We have developed GeneDig as a platform for bioinformatics integration focused on usability as its central design. This platform will introduce genomic navigation to broader audiences while aiding the bioinformatics analyses performed in everyday biology research.
Mayer, Gerhard; Quast, Christian; Felden, Janine; Lange, Matthias; Prinz, Manuel; Pühler, Alfred; Lawerenz, Chris; Scholz, Uwe; Glöckner, Frank Oliver; Müller, Wolfgang; Marcus, Katrin; Eisenacher, Martin
Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific 'service provision units' is introduced together with the factors influencing them and the main underlying assumptions for these 'value influencing factors'. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared. © The Author 2017. Published by Oxford University Press.
Horbach, D.Y.; Usanov, S.A.
One of the mechanisms of external signal transduction (ionizing radiation, toxicants, stress) to the target cell is the existence of membrane and intracellular proteins with intrinsic tyrosine kinase activity. No wonder that etiology of malignant growth links to abnormalities in signal transduction through tyrosine kinases. The epidermal growth factor receptor (EGFR) tyrosine kinases play fundamental roles in development, proliferation and differentiation of tissues of epithelial, mesenchymal and neuronal origin. There are four types of EGFR: EGF receptor (ErbB1/HER1), ErbB2/Neu/HER2, ErbB3/HER3 and ErbB4/HER4. Abnormal expression of EGFR, appearance of receptor mutants with changed ability to protein-protein interactions or increased tyrosine kinase activity have been implicated in the malignancy of different types of human tumors. Bioinformatics is currently using in investigation on design and selection of drugs that can make alterations in structure or competitively bind with receptors and so display antagonistic characteristics. (authors)
Horbach, D Y [International A. Sakharov environmental univ., Minsk (Belarus); Usanov, S A [Inst. of bioorganic chemistry, National academy of sciences of Belarus, Minsk (Belarus)
One of the mechanisms of external signal transduction (ionizing radiation, toxicants, stress) to the target cell is the existence of membrane and intracellular proteins with intrinsic tyrosine kinase activity. No wonder that etiology of malignant growth links to abnormalities in signal transduction through tyrosine kinases. The epidermal growth factor receptor (EGFR) tyrosine kinases play fundamental roles in development, proliferation and differentiation of tissues of epithelial, mesenchymal and neuronal origin. There are four types of EGFR: EGF receptor (ErbB1/HER1), ErbB2/Neu/HER2, ErbB3/HER3 and ErbB4/HER4. Abnormal expression of EGFR, appearance of receptor mutants with changed ability to protein-protein interactions or increased tyrosine kinase activity have been implicated in the malignancy of different types of human tumors. Bioinformatics is currently using in investigation on design and selection of drugs that can make alterations in structure or competitively bind with receptors and so display antagonistic characteristics. (authors)
Basyuni, M.; Wasilah, M.; Sumardi
This study describes the bioinformatics methods to analyze eight actin genes from mangrove plants on DDBJ/EMBL/GenBank as well as predicted the structure, composition, subcellular localization, similarity, and phylogenetic. The physical and chemical properties of eight mangroves showed variation among the genes. The percentage of the secondary structure of eight mangrove actin genes followed the order of a helix > random coil > extended chain structure for BgActl, KcActl, RsActl, and A. corniculatum Act. In contrast to this observation, the remaining actin genes were random coil > extended chain structure > a helix. This study, therefore, shown the prediction of secondary structure was performed for necessary structural information. The values of chloroplast or signal peptide or mitochondrial target were too small, indicated that no chloroplast or mitochondrial transit peptide or signal peptide of secretion pathway in mangrove actin genes. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove actin genes. To clarify the relationship among the mangrove actin gene, a phylogenetic tree was constructed. Three groups of mangrove actin genes were formed, the first group contains B. gymnorrhiza BgAct and R. stylosa RsActl. The second cluster which consists of 5 actin genes the largest group, and the last branch consist of one gene, B. sexagula Act. The present study, therefore, supported the previous results that plant actin genes form distinct clusters in the tree.
Pinho, Jorge; Sobral, João Luis; Rocha, Miguel
A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Gentleman, R.C.; Carey, V.J.; Bates, D.M.
The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisci......The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry...... into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples....
Fu, Zhiyan; Lin, Jing
The rapidly increasing number of characterized allergens has created huge demands for advanced information storage, retrieval, and analysis. Bioinformatics and machine learning approaches provide useful tools for the study of allergens and epitopes prediction, which greatly complement traditional laboratory techniques. The specific applications mainly include identification of B- and T-cell epitopes, and assessment of allergenicity and cross-reactivity. In order to facilitate the work of clinical and basic researchers who are not familiar with bioinformatics, we review in this chapter the most important databases, bioinformatic tools, and methods with relevance to the study of allergens.
de Groot Joost CW
Full Text Available Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1 a web based, graphical user interface (GUI that enables a pipeline operator to manage the system; 2 the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3 the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.
Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela
Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.
Revote, Jerico; Watson-Haigh, Nathan S; Quenette, Steve; Bethwaite, Blair; McGrath, Annette; Shang, Catherine A
The Bioinformatics Training Platform (BTP) has been developed to provide access to the computational infrastructure required to deliver sophisticated hands-on bioinformatics training courses. The BTP is a cloud-based solution that is in active use for delivering next-generation sequencing training to Australian researchers at geographically dispersed locations. The BTP was built to provide an easy, accessible, consistent and cost-effective approach to delivering workshops at host universities and organizations with a high demand for bioinformatics training but lacking the dedicated bioinformatics training suites required. To support broad uptake of the BTP, the platform has been made compatible with multiple cloud infrastructures. The BTP is an open-source and open-access resource. To date, 20 training workshops have been delivered to over 700 trainees at over 10 venues across Australia using the BTP. © The Author 2016. Published by Oxford University Press.
Whyte, Barry James
The National Science Foundation has awarded the Virginia Bioinformatics Institute at Virginia Tech $918,000 to expand its education and outreach program in Cyberinfrastructure - Training, Education, Advancement and Mentoring, commonly known as the CI-TEAM.
Bonny, Talal; Salama, Khaled N.; Zidan, Mohammed A.
Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we
Michael R Clay
Full Text Available Training anatomic and clinical pathology residents in the principles of bioinformatics is a challenging endeavor. Most residents receive little to no formal exposure to bioinformatics during medical education, and most of the pathology training is spent interpreting histopathology slides using light microscopy or focused on laboratory regulation, management, and interpretation of discrete laboratory data. At a minimum, residents should be familiar with data structure, data pipelines, data manipulation, and data regulations within clinical laboratories. Fellowship-level training should incorporate advanced principles unique to each subspecialty. Barriers to bioinformatics education include the clinical apprenticeship training model, ill-defined educational milestones, inadequate faculty expertise, and limited exposure during medical training. Online educational resources, case-based learning, and incorporation into molecular genomics education could serve as effective educational strategies. Overall, pathology bioinformatics training can be incorporated into pathology resident curricula, provided there is motivation to incorporate, institutional support, educational resources, and adequate faculty expertise.
Phosphoenolpyruvate carboxykinase (PEPCK), a critical gluconeogenic enzyme, catalyzes the first committed step in the diversion of tricarboxylic acid cycle intermediates toward gluconeogenesis. According to the relative conservation of homologous gene, a bioinformatics strategy was applied to clone Fusarium ...
Diaz Acosta, B.
The Microsoft Biology Initiative (MBI) is an effort in Microsoft Research to bring new technology and tools to the area of bioinformatics and biology. This initiative is comprised of two primary components, the Microsoft Biology Foundation (MBF) and the Microsoft Biology Tools (MBT). MBF is a language-neutral bioinformatics toolkit built as an extension to the Microsoft .NET Framework—initially aimed at the area of Genomics research. Currently, it implements a range of parsers for common bioinformatics file formats; a range of algorithms for manipulating DNA, RNA, and protein sequences; and a set of connectors to biological web services such as NCBI BLAST. MBF is available under an open source license, and executables, source code, demo applications, documentation and training materials are freely downloadable from http://research.microsoft.com/bio. MBT is a collection of tools that enable biology and bioinformatics researchers to be more productive in making scientific discoveries.
Bioinformatics tools for development of fast and cost effective simple sequence repeat ... comparative mapping and exploration of functional genetic diversity in the ... Already, a number of computer programs have been implemented that aim at ...
The Skate Genome Project, a pilot project of the North East Cyber infrastructure Consortium, aims to produce a draft genome sequence of Leucoraja erinacea, the Little Skate. The pilot project was designed to also develop expertise in large scale collaborations across the NECC region. An overview of the bioinformatics and infrastructure challenges faced during the first year of the project will be presented. Results to date and lessons learned from the perspective of a bioinformatics core will be highlighted.
Vand, Kasra; Wahlestedt, Thor; Khomtchouk, Kelly; Sayed, Mohammed; Wahlestedt, Claes; Khomtchouk, Bohdan
We propose a search engine and file retrieval system for all bioinformatics databases worldwide. PubData searches biomedical data in a user-friendly fashion similar to how PubMed searches biomedical literature. PubData is built on novel network programming, natural language processing, and artificial intelligence algorithms that can patch into the file transfer protocol servers of any user-specified bioinformatics database, query its contents, retrieve files for download, and adapt to the use...
Full Text Available Abstract Background Recent advances in experimental and computational technologies have fueled the development of many sophisticated bioinformatics programs. The correctness of such programs is crucial as incorrectly computed results may lead to wrong biological conclusion or misguide downstream experimentation. Common software testing procedures involve executing the target program with a set of test inputs and then verifying the correctness of the test outputs. However, due to the complexity of many bioinformatics programs, it is often difficult to verify the correctness of the test outputs. Therefore our ability to perform systematic software testing is greatly hindered. Results We propose to use a novel software testing technique, metamorphic testing (MT, to test a range of bioinformatics programs. Instead of requiring a mechanism to verify whether an individual test output is correct, the MT technique verifies whether a pair of test outputs conform to a set of domain specific properties, called metamorphic relations (MRs, thus greatly increases the number and variety of test cases that can be applied. To demonstrate how MT is used in practice, we applied MT to test two open-source bioinformatics programs, namely GNLab and SeqMap. In particular we show that MT is simple to implement, and is effective in detecting faults in a real-life program and some artificially fault-seeded programs. Further, we discuss how MT can be applied to test programs from various domains of bioinformatics. Conclusion This paper describes the application of a simple, effective and automated technique to systematically test a range of bioinformatics programs. We show how MT can be implemented in practice through two real-life case studies. Since many bioinformatics programs, particularly those for large scale simulation and data analysis, are hard to test systematically, their developers may benefit from using MT as part of the testing strategy. Therefore our work
Velloso, Henrique; Vialle, Ricardo A; Ortega, J Miguel
Bioinformaticians face a range of difficulties to get locally-installed tools running and producing results; they would greatly benefit from a system that could centralize most of the tools, using an easy interface for input and output. Web services, due to their universal nature and widely known interface, constitute a very good option to achieve this goal. Bioinformatics open web services (BOWS) is a system based on generic web services produced to allow programmatic access to applications running on high-performance computing (HPC) clusters. BOWS intermediates the access to registered tools by providing front-end and back-end web services. Programmers can install applications in HPC clusters in any programming language and use the back-end service to check for new jobs and their parameters, and then to send the results to BOWS. Programs running in simple computers consume the BOWS front-end service to submit new processes and read results. BOWS compiles Java clients, which encapsulate the front-end web service requisitions, and automatically creates a web page that disposes the registered applications and clients. Bioinformatics open web services registered applications can be accessed from virtually any programming language through web services, or using standard java clients. The back-end can run in HPC clusters, allowing bioinformaticians to remotely run high-processing demand applications directly from their machines.
Kent, Jack W
New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.
Full Text Available Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets; workflow platform(s enabling accessible, reproducible, portable analyses, through a flexible set of interfaces; highly available, scalable computational resources; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise.We designed and implemented the Genomics Virtual Laboratory (GVL as a middleware layer of machine images, cloud management tools, and online services that enable researchers to build arbitrarily sized compute clusters on demand, pre-populated with fully configured bioinformatics tools, reference datasets and workflow and visualisation options. The platform is flexible in that users can conduct analyses through web-based (Galaxy, RStudio, IPython Notebook or command-line interfaces, and add/remove compute nodes and data resources as required. Best-practice tutorials and protocols provide a path from introductory training to practice. The GVL is available on the OpenStack-based Australian Research Cloud (http://nectar.org.au and the Amazon Web Services cloud. The principles, implementation and build process are designed to be cloud-agnostic.This paper provides a blueprint for the design and implementation of a cloud-based Genomics Virtual Laboratory. We discuss scope, design considerations and technical and logistical constraints
Afgan, Enis; Sloggett, Clare; Goonasekera, Nuwan; Makunin, Igor; Benson, Derek; Crowe, Mark; Gladman, Simon; Kowsar, Yousef; Pheasant, Michael; Horst, Ron; Lonie, Andrew
Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets; workflow platform(s) enabling accessible, reproducible, portable analyses, through a flexible set of interfaces; highly available, scalable computational resources; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise. We designed and implemented the Genomics Virtual Laboratory (GVL) as a middleware layer of machine images, cloud management tools, and online services that enable researchers to build arbitrarily sized compute clusters on demand, pre-populated with fully configured bioinformatics tools, reference datasets and workflow and visualisation options. The platform is flexible in that users can conduct analyses through web-based (Galaxy, RStudio, IPython Notebook) or command-line interfaces, and add/remove compute nodes and data resources as required. Best-practice tutorials and protocols provide a path from introductory training to practice. The GVL is available on the OpenStack-based Australian Research Cloud (http://nectar.org.au) and the Amazon Web Services cloud. The principles, implementation and build process are designed to be cloud-agnostic. This paper provides a blueprint for the design and implementation of a cloud-based Genomics Virtual Laboratory. We discuss scope, design considerations and technical and logistical constraints, and explore the
Full Text Available As a focal point of biotechnology, bioinformatics integrates knowledge from biology, mathematics, physics, chemistry, computer science and information science. It generally deals with genome informatics, protein structure and drug design. However, the data or information thus acquired from the main areas of bioinformatics may not be effective. Some researchers combined bioinformatics with wireless sensor network (WSN into biosensor and other tools, and applied them to such areas as fermentation, environmental monitoring, food engineering, clinical medicine and military. In the combination, the WSN is used to collect data and information. The reliability of the WSN in bioinformatics is the prerequisite to effective utilization of information. It is greatly influenced by factors like quality, benefits, service, timeliness and stability, some of them are qualitative and some are quantitative. Hence, it is necessary to develop a method that can handle both qualitative and quantitative assessment of information. A viable option is the fuzzy linguistic method, especially 2-tuple linguistic model, which has been extensively used to cope with such issues. As a result, this paper introduces 2-tuple linguistic representation to assist experts in giving their opinions on different WSNs in bioinformatics that involve multiple factors. Moreover, the author proposes a novel way to determine attribute weights and uses the method to weigh the relative importance of different influencing factors which can be considered as attributes in the assessment of the WSN in bioinformatics. Finally, an illustrative example is given to provide a reasonable solution for the assessment.
Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W
Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. firstname.lastname@example.org. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com
Vamathevan, J; Birney, E
Objectives: To highlight and provide insights into key developments in translational bioinformatics between 2014 and 2016. Methods: This review describes some of the most influential bioinformatics papers and resources that have been published between 2014 and 2016 as well as the national genome sequencing initiatives that utilize these resources to routinely embed genomic medicine into healthcare. Also discussed are some applications of the secondary use of patient data followed by a comprehensive view of the open challenges and emergent technologies. Results: Although data generation can be performed routinely, analyses and data integration methods still require active research and standardization to improve streamlining of clinical interpretation. The secondary use of patient data has resulted in the development of novel algorithms and has enabled a refined understanding of cellular and phenotypic mechanisms. New data storage and data sharing approaches are required to enable diverse biomedical communities to contribute to genomic discovery. Conclusion: The translation of genomics data into actionable knowledge for use in healthcare is transforming the clinical landscape in an unprecedented way. Exciting and innovative models that bridge the gap between clinical and academic research are set to open up the field of translational bioinformatics for rapid growth in a digital era. Georg Thieme Verlag KG Stuttgart.
Ibrahim, Bashar; Arkhipova, Ksenia; Andeweg, Arno C; Posada-Céspedes, Susana; Enault, François; Gruber, Arthur; Koonin, Eugene V; Kupczok, Anne; Lemey, Philippe; McHardy, Alice C; McMahon, Dino P; Pickett, Brett E; Robertson, David L; Scheuermann, Richard H; Zhernakova, Alexandra; Zwart, Mark P; Schönhuth, Alexander; Dutilh, Bas E; Marz, Manja
The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.
van Gelder, Celia W G; Hooft, Rob W W; van Rijswijk, Merlijn N; van den Berg, Linda; Kok, Ruben G; Reinders, Marcel; Mons, Barend; Heringa, Jaap
This review provides a historical overview of the inception and development of bioinformatics research in the Netherlands. Rooted in theoretical biology by foundational figures such as Paulien Hogeweg (at Utrecht University since the 1970s), the developments leading to organizational structures supporting a relatively large Dutch bioinformatics community will be reviewed. We will show that the most valuable resource that we have built over these years is the close-knit national expert community that is well engaged in basic and translational life science research programmes. The Dutch bioinformatics community is accustomed to facing the ever-changing landscape of data challenges and working towards solutions together. In addition, this community is the stable factor on the road towards sustainability, especially in times where existing funding models are challenged and change rapidly. © The Author 2017. Published by Oxford University Press.
Jung, Sook; Main, Dorrie
Recent technological advances in biology promise unprecedented opportunities for rapid and sustainable advancement of crop quality. Following this trend, the Rosaceae research community continues to generate large amounts of genomic, genetic and breeding data. These include annotated whole genome sequences, transcriptome and expression data, proteomic and metabolomic data, genotypic and phenotypic data, and genetic and physical maps. Analysis, storage, integration and dissemination of these data using bioinformatics tools and databases are essential to provide utility of the data for basic, translational and applied research. This review discusses the currently available genomics and bioinformatics resources for the Rosaceae family.
Manning, Timmy; Sleator, Roy D; Walsh, Paul
For decades, computer scientists have looked to nature for biologically inspired solutions to computational problems; ranging from robotic control to scheduling optimization. Paradoxically, as we move deeper into the post-genomics era, the reverse is occurring, as biologists and bioinformaticians look to computational techniques, to solve a variety of biological problems. One of the most common biologically inspired techniques are genetic algorithms (GAs), which take the Darwinian concept of natural selection as the driving force behind systems for solving real world problems, including those in the bioinformatics domain. Herein, we provide an overview of genetic algorithms and survey some of the most recent applications of this approach to bioinformatics based problems.
Ditty, Jayna L.; Kvaal, Christopher A.; Goodner, Brad; Freyermuth, Sharyn K.; Bailey, Cheryl; Britton, Robert A.; Gordon, Stuart G.; Heinhorst, Sabine; Reed, Kelynne; Xu, Zhaohui; Sanders-Lorenz, Erin R.; Axen, Seth; Kim, Edwin; Johns, Mitrick; Scott, Kathleen; Kerfeld, Cheryl A.
Undergraduate life sciences education needs an overhaul, as clearly described in the National Research Council of the National Academies publication BIO 2010: Transforming Undergraduate Education for Future Research Biologists. Among BIO 2010's top recommendations is the need to involve students in working with real data and tools that reflect the nature of life sciences research in the 21st century. Education research studies support the importance of utilizing primary literature, designing and implementing experiments, and analyzing results in the context of a bona fide scientific question in cultivating the analytical skills necessary to become a scientist. Incorporating these basic scientific methodologies in undergraduate education leads to increased undergraduate and post-graduate retention in the sciences. Toward this end, many undergraduate teaching organizations offer training and suggestions for faculty to update and improve their teaching approaches to help students learn as scientists, through design and discovery (e.g., Council of Undergraduate Research [www.cur.org] and Project Kaleidoscope [www.pkal.org]). With the advent of genome sequencing and bioinformatics, many scientists now formulate biological questions and interpret research results in the context of genomic information. Just as the use of bioinformatic tools and databases changed the way scientists investigate problems, it must change how scientists teach to create new opportunities for students to gain experiences reflecting the influence of genomics, proteomics, and bioinformatics on modern life sciences research. Educators have responded by incorporating bioinformatics into diverse life science curricula. While these published exercises in, and guidelines for, bioinformatics curricula are helpful and inspirational, faculty new to the area of bioinformatics inevitably need training in the theoretical underpinnings of the algorithms. Moreover, effectively integrating bioinformatics
Nguyen, Thao Thi; Chon, Tae-Soo; Kim, Jaehan; Seo, Young-Su; Heo, Muyoung
Secreted proteins (secretomes) play crucial roles during bacterial pathogenesis in both plant and human hosts. The identification and characterization of secretomes in the two plant pathogens Burkholderia glumae BGR1 and B. gladioli BSR3, which cause diseases in rice such as seedling blight, panicle blight, and grain rot, are important steps to not only understand the disease-causing mechanisms but also find remedies for the diseases. Here, we identified two datasets of secretomes in B. glumae BGR1 and B. gladioli BSR3, which consist of 118 and 111 proteins, respectively, using mass spectrometry approach and literature curation. Next, we characterized the functional properties, potential secretion pathways and sequence information properties of secretomes of two plant pathogens in a comparative analysis by various computational approaches. The ratio of potential non-classically secreted proteins (NCSPs) to classically secreted proteins (CSPs) in B. glumae BGR1 was greater than that in B. gladioli BSR3. For CSPs, the putative hydrophobic regions (PHRs) which are essential for secretion process of CSPs were screened in detail at their N-terminal sequences using hidden Markov model (HMM)-based method. Total 31 pairs of homologous proteins in two bacterial secretomes were indicated based on the global alignment (identity ≥ 70%). Our results may facilitate the understanding of the species-specific features of secretomes in two plant pathogenic Burkholderia species.
Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho
High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.
Lima, Andre O. S.; Garces, Sergio P. S.
Bioinformatics is one of the fastest growing scientific areas over the last decade. It focuses on the use of informatics tools for the organization and analysis of biological data. An example of their importance is the availability nowadays of dozens of software programs for genomic and proteomic studies. Thus, there is a growing field (private…
A Bioinformatic Strategy to Rapidly Characterize cDNA LibrariesG. Charles Ostermeier1, David J. Dix2 and Stephen A. Krawetz1.1Departments of Obstetrics and Gynecology, Center for Molecular Medicine and Genetics, & Institute for Scientific Computing, Wayne State Univer...
van Gelder, Celia W.G.; Hooft, Rob; van Rijswijk, Merlijn; van den Berg, Linda; Kok, Ruben; Reinders, M.J.T.; Mons, Barend; Heringa, Jaap
This review provides a historical overview of the inception and development of bioinformatics research in the Netherlands. Rooted in theoretical biology by foundational figures such as Paulien Hogeweg (at Utrecht University since the 1970s), the developments leading to organizational structures
Bioinformatics has become an essential tool not only for basic research but also for applied research in biotechnology and biomedical sciences. Optimal primer sequence and appropriate primer concentration are essential for maximal specificity and efficiency of PCR. A poorly designed primer can result in little or no ...
Rasmussen, Morten; Thaysen-Andersen, Morten; Højrup, Peter
We have developed "GLYCANthrope " - CROSSWORKS for glycans: a bioinformatics tool, which assists in identifying N-linked glycosylated peptides as well as their glycan moieties from MS2 data of enzymatically digested glycoproteins. The program runs either as a stand-alone application or as a plug...
Gelbart, Hadas; Yarden, Anat
Following the rationale that learning is an active process of knowledge construction as well as enculturation into a community of experts, we developed a novel web-based learning environment in bioinformatics for high-school biology majors in Israel. The learning environment enables the learners to actively participate in a guided inquiry process…
Lewis, Jamie; Bartlett, Andrew; Atkinson, Paul
Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised…
Chapman, Barbara S.; Christmann, James L.; Thatcher, Eileen F.
We describe an innovative bioinformatics course developed under grants from the National Science Foundation and the California State University Program in Research and Education in Biotechnology for undergraduate biology students. The project has been part of a continuing effort to offer students classroom experiences focused on principles and…
Cazals, Frédéric; Dreyfus, Tom
Software in structural bioinformatics has mainly been application driven. To favor practitioners seeking off-the-shelf applications, but also developers seeking advanced building blocks to develop novel applications, we undertook the design of the Structural Bioinformatics Library ( SBL , http://sbl.inria.fr ), a generic C ++/python cross-platform software library targeting complex problems in structural bioinformatics. Its tenet is based on a modular design offering a rich and versatile framework allowing the development of novel applications requiring well specified complex operations, without compromising robustness and performances. The SBL involves four software components (1-4 thereafter). For end-users, the SBL provides ready to use, state-of-the-art (1) applications to handle molecular models defined by unions of balls, to deal with molecular flexibility, to model macro-molecular assemblies. These applications can also be combined to tackle integrated analysis problems. For developers, the SBL provides a broad C ++ toolbox with modular design, involving core (2) algorithms , (3) biophysical models and (4) modules , the latter being especially suited to develop novel applications. The SBL comes with a thorough documentation consisting of user and reference manuals, and a bugzilla platform to handle community feedback. The SBL is available from http://sbl.inria.fr. Frederic.Cazals@inria.fr. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org
Rapid cloning and bioinformatic analysis of spinach Y chromosome- specific EST sequences. Chuan-Liang Deng, Wei-Li Zhang, Ying Cao, Shao-Jing Wang, ... Arabidopsis thaliana mRNA for mitochondrial half-ABC transporter (STA1 gene). 389 2.31E-13. 98.96. SP3−12. Betula pendula histidine kinase 3 (HK3) mRNA, ...
The newly established RNA Biology Laboratory (RBL) at the Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH) in Frederick, Maryland is recruiting a Staff Scientist with strong expertise in RNA bioinformatics to join the Intramural Research Program’s mission of high impact, high reward science. The RBL is the equivalent of an
Full Text Available Xiao Yang,1 Shaoming Zhu,2 Li Li,3 Li Zhang,1 Shu Xian,1 Yanqing Wang,1 Yanxiang Cheng1 1Department of Obstetrics and Gynecology, 2Department of Urology, Renmin Hospital of Wuhan University, 3Department of Pharmacology, Wuhan University Health Science Center, Wuhan, Hubei, People’s Republic of China Background: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. Results: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs and were deeply analyzed by bioinformatics methods. The gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the
Full Text Available We had analyzed 10 exome sequencing data and single nucleotide polymorphism chips for blood cancer provided by the PGM21 (The National Project for Personalized Genomic Medicine Award program. We had removed sample G06 because the pair is not correct and G10 because of possible contamination. In-house software somatic copy-number and heterozygosity alteration estimation (SCHALE was used to detect one loss of heterozygosity region in G05. We had discovered 27 functionally important mutations. Network and pathway analyses gave us clues that NPM1, GATA2, and CEBPA were major driver genes. By comparing with previous somatic mutation profiles, we had concluded that the provided data originated from acute myeloid leukemia. Protein structure modeling showed that somatic mutations in IDH2, RASGEF1B, and MSH4 can affect protein structures.
Full Text Available Abstract Background There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no sucessful attempts have been made to integrate chemo- and bioinformatics into a single framework. Results Bioclipse is an advanced workbench for resources in chemo- and bioinformatics, such as molecules, proteins, sequences, spectra, and scripts. It provides 2D-editing, 3D-visualization, file format conversion, calculation of chemical properties, and much more; all fully integrated into a user-friendly desktop application. Editing supports standard functions such as cut and paste, drag and drop, and undo/redo. Bioclipse is written in Java and based on the Eclipse Rich Client Platform with a state-of-the-art plugin architecture. This gives Bioclipse an advantage over other systems as it can easily be extended with functionality in any desired direction. Conclusion Bioclipse is a powerful workbench for bio- and chemoinformatics as well as an advanced integration platform. The rich functionality, intuitive user interface, and powerful plugin architecture make Bioclipse the most advanced and user-friendly open source workbench for chemo- and bioinformatics. Bioclipse is released under Eclipse Public License (EPL, an open source license which sets no constraints on external plugin licensing; it is totally open for both open source plugins as well as commercial ones. Bioclipse is freely available at http://www.bioclipse.net.
Stringer-Calvert David WJ
Full Text Available Abstract Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the
Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D
This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.
Reddy, B P Niranjan; Shrestha, Sony; Hart, Kevin J; Liang, Xiaoying; Kemirembe, Karen; Cui, Liwang; Lindner, Scott E
The malaria parasites in the genus Plasmodium have a very complicated life cycle involving an invertebrate vector and a vertebrate host. RNA-binding proteins (RBPs) are critical factors involved in every aspect of the development of these parasites. However, very few RBPs have been functionally characterized to date in the human parasite Plasmodium falciparum. Using different bioinformatic methods and tools we searched P. falciparum genome to list and annotate RBPs. A representative 3D models for each of the RBD domain identified in P. falciparum was created using I-TESSAR and SWISS-MODEL. Microarray and RNAseq data analysis pertaining PfRBPs was performed using MeV software. Finally, Cytoscape was used to create protein-protein interaction network for CITH-Dozi and Caf1-CCR4-Not complexes. We report the identification of 189 putative RBP genes belonging to 13 different families in Plasmodium, which comprise 3.5% of all annotated genes. Almost 90% (169/189) of these genes belong to six prominent RBP classes, namely RNA recognition motifs, DEAD/H-box RNA helicases, K homology, Zinc finger, Puf and Alba gene families. Interestingly, almost all of the identified RNA-binding helicases and KH genes have cognate homologs in model species, suggesting their evolutionary conservation. Exploration of the existing P. falciparum blood-stage transcriptomes revealed that most RBPs have peak mRNA expression levels early during the intraerythrocytic development cycle, which taper off in later stages. Nearly 27% of RBPs have elevated expression in gametocytes, while 47 and 24% have elevated mRNA expression in ookinete and asexual stages. Comparative interactome analyses using human and Plasmodium protein-protein interaction datasets suggest extensive conservation of the PfCITH/PfDOZI and PfCaf1-CCR4-NOT complexes. The Plasmodium parasites possess a large number of putative RBPs belonging to most of RBP families identified so far, suggesting the presence of extensive post
Nehm, Ross H.; Budd, Ann F.
NMITA is a reef coral biodiversity database that we use to introduce students to the expansive realm of bioinformatics beyond genetics. We introduce a series of lessons that have students use this database, thereby accessing real data that can be used to test hypotheses about biodiversity and evolution while targeting the "National Science …
Full Text Available Precision medicine (PM requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of i warranting the integration and the traceability of data, ii ensuring the correct processing and analyses of genomic data and iii applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.
Treu, Laura; Campanaro, Stefano; De Francisci, Davide
16S hypervariable regions, especially when working with the not high quality very short reads characteristics of next generation sequencers (Mande S.S. et al., 2012). Previous works analysed the microbial community composition in biogas reactors via 16S rDNA sequencing (Luo, G. et al., 2013; Werner......, J.J. et al., 2011). For this reason we developed a bioinformatics strategy in order to create a tool to review the generated dataset and to obtain a more strict control on the bacterial composition at the species level, with estimation of its reliability. The program perform local similarity search...... in the same genus, while others give multiple matches with the same probability. The software was used to analyse samples taken during the digestion process in three independent biogas reactors continuously fed with raw cattle manure. Among the most represented (>1%) considering the relative abundance...
Attwood, Terri K.; Selimas, Ioannis; Buis, Rob; Altenburg, Ruud; Herzog, Robert; Ledent, Valerie; Ghita, Viorica; Fernandes, Pedro; Marques, Isabel; Brugman, Marc
EMBER was a European project aiming to develop bioinformatics teaching materials on the Web and CD-ROM to help address the recognised skills shortage in bioinformatics. The project grew out of pilot work on the development of an interactive web-based bioinformatics tutorial and the desire to repackage that resource with the help of a professional…
Shachak, Aviv; Ophir, Ron; Rubin, Eitan
The need to support bioinformatics training has been widely recognized by scientists, industry, and government institutions. However, the discussion of instructional methods for teaching bioinformatics is only beginning. Here we report on a systematic attempt to design two bioinformatics workshops for graduate biology students on the basis of…
Inlow, Jennifer K.; Miller, Paige; Pittman, Bethany
We describe two bioinformatics exercises intended for use in a computer laboratory setting in an upper-level undergraduate biochemistry course. To introduce students to bioinformatics, the exercises incorporate several commonly used bioinformatics tools, including BLAST, that are freely available online. The exercises build upon the students'…
Furge, Laura Lowe; Stevens-Truss, Regina; Moore, D. Blaine; Langeland, James A.
Bioinformatics education for undergraduates has been approached primarily in two ways: introduction of new courses with largely bioinformatics focus or introduction of bioinformatics experiences into existing courses. For small colleges such as Kalamazoo, creation of new courses within an already resource-stretched setting has not been an option.…
Zoukhri, Driss; Rawe, Ian; Singh, Mabi; Brown, Ashley; Kublin, Claire L; Dawson, Kevin; Haddon, William F; White, Earl L; Hanley, Kathleen M; Tusé, Daniel; Malyj, Wasyl; Papas, Athena
The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.
Full Text Available Transcriptional regulation is an important mechanism underlying gene expression and has played a crucial role in evolution. The number, position and interactions between cis-elements and transcription factors (TFs determine the expression pattern of a gene. To identify functionally relevant cis-elements in gene promoters, a phylogenetic shadowing approach with a lipase gene (LIP1 was used. As a proof of concept, in silico analyses of several Brassicaceae LIP1 promoters identified a highly conserved sequence (LIP1 element that is sufficient to drive strong expression of a reporter gene in planta. A collection of ca. 1,200 Arabidopsis thaliana TF open reading frames (ORFs was arrayed in a 96-well format (RR library and a convenient mating based yeast one hybrid (Y1H screening procedure was established. We constructed an episomal plasmid (pTUY1H to clone the LIP1 element and used it as bait for Y1H screenings. A novel interaction with an HD-ZIP (AtML1 TF was identified and abolished by a 2 bp mutation in the LIP1 element. A role of this interaction in transcriptional regulation was confirmed in planta. In addition, we validated our strategy by reproducing the previously reported interaction between a MYB-CC (PHR1 TF, a central regulator of phosphate starvation responses, with a conserved promoter fragment (IPS1 element containing its cognate binding sequence. Finally, we established that the LIP1 and IPS1 elements were differentially bound by HD-ZIP and MYB-CC family members in agreement with their genetic redundancy in planta. In conclusion, combining in silico analyses of orthologous gene promoters with Y1H screening of the RR library represents a powerful approach to decipher cis- and trans-regulatory codes.
Yao, Li; Wang, Heming; Song, Yuanyuan; Sui, Guangchao
With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analyse these data. However, these tools concentrate mainly on their syntax and design paradigms, and dispatch jobs based on users' experience about the resources needed by the execution of a certain step in a protocol. As a result, it is difficult for these tools to maximize the potential of computing resources, and avoid errors caused by overload, such as memory overflow. Here, we have developed BioQueue, a web-based framework that contains a checkpoint before each step to automatically estimate the system resources (CPU, memory and disk) needed by the step and then dispatch jobs accordingly. BioQueue possesses a shell command-like syntax instead of implementing a new script language, which means most biologists without computer programming background can access the efficient queue system with ease. BioQueue is freely available at https://github.com/liyao001/BioQueue. The extensive documentation can be found at http://bioqueue.readthedocs.io. email@example.com or firstname.lastname@example.org. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com
Park, Doori; Park, Su-Hyun; Ban, Yong Wook; Kim, Youn Shic; Park, Kyoung-Cheul; Kim, Nam-Soo; Kim, Ju-Kon; Choi, Ik-Young
Genetically modified crops (GM crops) have been developed to improve the agricultural traits of modern crop cultivars. Safety assessments of GM crops are of paramount importance in research at developmental stages and before releasing transgenic plants into the marketplace. Sequencing technology is developing rapidly, with higher output and labor efficiencies, and will eventually replace existing methods for the molecular characterization of genetically modified organisms. To detect the transgenic insertion locations in the three GM rice gnomes, Illumina sequencing reads are mapped and classified to the rice genome and plasmid sequence. The both mapped reads are classified to characterize the junction site between plant and transgene sequence by sequence alignment. Herein, we present a next generation sequencing (NGS)-based molecular characterization method, using transgenic rice plants SNU-Bt9-5, SNU-Bt9-30, and SNU-Bt9-109. Specifically, using bioinformatics tools, we detected the precise insertion locations and copy numbers of transfer DNA, genetic rearrangements, and the absence of backbone sequences, which were equivalent to results obtained from Southern blot analyses. NGS methods have been suggested as an effective means of characterizing and detecting transgenic insertion locations in genomes. Our results demonstrate the use of a combination of NGS technology and bioinformatics approaches that offers cost- and time-effective methods for assessing the safety of transgenic plants.
At the end of January I travelled to the States to speak at and attend the first O'Reilly Bioinformatics Technology Conference. It was a large, well-organized and diverse meeting with an interesting history. Although the meeting was not a typical academic conference, its style will, I am sure, become more typical of meetings in both biological and computational sciences.Speakers at the event included prominent bioinformatics researchers such as Ewan Birney, Terry Gaasterland and Lincoln Stein; authors and leaders in the open source programming community like Damian Conway and Nat Torkington; and representatives from several publishing companies including the Nature Publishing Group, Current Science Group and the President of O'Reilly himself, Tim O'Reilly. There were presentations, tutorials, debates, quizzes and even a 'jam session' for musical bioinformaticists.
Vetrivel, Umashankar; Pilla, Kalabharath
Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery - a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in.
Christos A Ouzounis
Full Text Available The field of bioinformatics and computational biology has gone through a number of transformations during the past 15 years, establishing itself as a key component of new biology. This spectacular growth has been challenged by a number of disruptive changes in science and technology. Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. These trends appear to be pointing to a redefinition of certain objectives, milestones, and possibly the field itself.
Full Text Available With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.
Calabrese, Barbara; Cannataro, Mario
High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.
Varma, B Sharat Chandra; Balakrishnan, M
This book presents an evaluation methodology to design future FPGA fabrics incorporating hard embedded blocks (HEBs) to accelerate applications. This methodology will be useful for selection of blocks to be embedded into the fabric and for evaluating the performance gain that can be achieved by such an embedding. The authors illustrate the use of their methodology by studying the impact of HEBs on two important bioinformatics applications: protein docking and genome assembly. The book also explains how the respective HEBs are designed and how hardware implementation of the application is done using these HEBs. It shows that significant speedups can be achieved over pure software implementations by using such FPGA-based accelerators. The methodology presented in this book may also be used for designing HEBs for accelerating software implementations in other domains besides bioinformatics. This book will prove useful to students, researchers, and practicing engineers alike.
Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan
This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis. .
Full Text Available The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems.
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
Palma, Jonathan P.; Benitz, William E.; Tarczy-Hornoch, Peter; Butte, Atul J.; Longhurst, Christopher A.
The future of neonatal informatics will be driven by the availability of increasingly vast amounts of clinical and genetic data. The field of translational bioinformatics is concerned with linking and learning from these data and applying new findings to clinical care to transform the data into proactive, predictive, preventive, and participatory health. As a result of advances in translational informatics, the care of neonates will become more data driven, evidence based, and personalized. PMID:22924023
Background Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. Results BIRCH (Biological Research Computing Hierarchy) is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment) graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. Conclusion BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere. PMID:17291351
Full Text Available Designers have a saying that "the joy of an early release lasts but a short time. The bitterness of an unusable system lasts for years." It is indeed disappointing to discover that your data resources are not being used to their full potential. Not only have you invested your time, effort, and research grant on the project, but you may face costly redesigns if you want to improve the system later. This scenario would be less likely if the product was designed to provide users with exactly what they need, so that it is fit for purpose before its launch. We work at EMBL-European Bioinformatics Institute (EMBL-EBI, and we consult extensively with life science researchers to find out what they need from biological data resources. We have found that although users believe that the bioinformatics community is providing accurate and valuable data, they often find the interfaces to these resources tricky to use and navigate. We believe that if you can find out what your users want even before you create the first mock-up of a system, the final product will provide a better user experience. This would encourage more people to use the resource and they would have greater access to the data, which could ultimately lead to more scientific discoveries. In this paper, we explore the need for a user-centred design (UCD strategy when designing bioinformatics resources and illustrate this with examples from our work at EMBL-EBI. Our aim is to introduce the reader to how selected UCD techniques may be successfully applied to software design for bioinformatics.
Budd, Aidan; Corpas, Manuel; Brazas, Michelle D.; Fuller, Jonathan C.; Goecks, Jeremy; Mulder, Nicola J.; Michaut, Magali; Ouellette, B. F. Francis; Pawlik, Aleksandra; Blomberg, Niklas
“Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop “The ‘How To Guide’ for Establishing a Successful Bioinformatics Network” at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB). PMID:25654371
The cluster orchestration tool Kubernetes enables easy deployment and reproducibility of life science research by utilizing the advantages of the container technology. The container technology allows for easy tool creation, sharing and runs on any Linux system once it has been built. The applicability of Kubernetes as an approach to run bioinformatic workflows was evaluated and resulted in some examples of how Kubernetes and containers could be used within the field of life science and how th...
Full Text Available Abstract Background Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. Results BIRCH (Biological Research Computing Hierarchy is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. Conclusion BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere.
Díaz-Del-Pino, Sergio; Falgueras, Juan; Perez-Wohlfeil, Esteban; Trelles, Oswaldo
Nearly 10 years have passed since the first mobile apps appeared. Given the fact that bioinformatics is a web-based world and that mobile devices are endowed with web-browsers, it seemed natural that bioinformatics would transit from personal computers to mobile devices but nothing could be further from the truth. The transition demands new paradigms, designs and novel implementations. Throughout an in-depth analysis of requirements of existing bioinformatics applications we designed and deployed an easy-to-use web-based lightweight mobile client. Such client is able to browse, select, compose automatically interface parameters, invoke services and monitor the execution of Web Services using the service's metadata stored in catalogs or repositories. mORCA is available at http://bitlab-es.com/morca/app as a web-app. It is also available in the App store by Apple and Play Store by Google. The software will be available for at least 2 years. firstname.lastname@example.org. Source code, final web-app, training material and documentation is available at http://bitlab-es.com/morca. © The Author(s) 2017. Published by Oxford University Press.
Repin, Rul Aisyah Mat; Mutalib, Sahilah Abdul; Shahimi, Safiyyah; Khalid, Rozida Mohd.; Ayob, Mohd. Khan; Bakar, Mohd. Faizal Abu; Isa, Mohd Noor Mat
In this study, we performed bioinformatics analysis toward genome sequence of Lysinibacillussphaericus (L. sphaericus) to determine gene encoded for gelatinase. L. sphaericus was isolated from soil and gelatinase species-specific bacterium to porcine and bovine gelatin. This bacterium offers the possibility of enzymes production which is specific to both species of meat, respectively. The main focus of this research is to identify the gelatinase encoded gene within the bacteria of L. Sphaericus using bioinformatics analysis of partially sequence genome. From the research study, three candidate gene were identified which was, gelatinase candidate gene 1 (P1), NODE_71_length_93919_cov_158.931839_21 which containing 1563 base pair (bp) in size with 520 amino acids sequence; Secondly, gelatinase candidate gene 2 (P2), NODE_23_length_52851_cov_190.061386_17 which containing 1776 bp in size with 591 amino acids sequence; and Thirdly, gelatinase candidate gene 3 (P3), NODE_106_length_32943_cov_169.147919_8 containing 1701 bp in size with 566 amino acids sequence. Three pairs of oligonucleotide primers were designed and namely as, F1, R1, F2, R2, F3 and R3 were targeted short sequences of cDNA by PCR. The amplicons were reliably results in 1563 bp in size for candidate gene P1 and 1701 bp in size for candidate gene P3. Therefore, the results of bioinformatics analysis of L. Sphaericus resulting in gene encoded gelatinase were identified.
Sarachan, B D; Simmons, M K; Subramanian, P; Temkin, J M
Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21 st century toward new diagnoses, prognoses, and treatments. Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology). Initial predictive models have been developed for a pilot study in Huntington's disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation. A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21 st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.
Fourment, Mathieu; Gillings, Michael R
The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python. Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found. Source code and additional information are available from http://www.bioinformatics.org/benchmark/. This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.
Full Text Available Abstract This paper presents the Bioinformatics Computational Journal (BCJ, a framework for conducting and managing computational experiments in bioinformatics and computational biology. These experiments often involve series of computations, data searches, filters, and annotations which can benefit from a structured environment. Systems to manage computational experiments exist, ranging from libraries with standard data models to elaborate schemes to chain together input and output between applications. Yet, although such frameworks are available, their use is not widespread–ad hoc scripts are often required to bind applications together. The BCJ explores another solution to this problem through a computer based environment suitable for on-site use, which builds on the traditional laboratory notebook paradigm. It provides an intuitive, extensible paradigm designed for expressive composition of applications. Extensive features facilitate sharing data, computational methods, and entire experiments. By focusing on the bioinformatics and computational biology domain, the scope of the computational framework was narrowed, permitting us to implement a capable set of features for this domain. This report discusses the features determined critical by our system and other projects, along with design issues. We illustrate the use of our implementation of the BCJ on two domain-specific examples.
Niu, Sheng-Yong; Yang, Jinyu; McDermaid, Adam; Zhao, Jing; Kang, Yu; Ma, Qin
Metagenomic and metatranscriptomic sequencing approaches are more frequently being used to link microbiota to important diseases and ecological changes. Many analyses have been used to compare the taxonomic and functional profiles of microbiota across habitats or individuals. While a large portion of metagenomic analyses focus on species-level profiling, some studies use strain-level metagenomic analyses to investigate the relationship between specific strains and certain circumstances. Metatranscriptomic analysis provides another important insight into activities of genes by examining gene expression levels of microbiota. Hence, combining metagenomic and metatranscriptomic analyses will help understand the activity or enrichment of a given gene set, such as drug-resistant genes among microbiome samples. Here, we summarize existing bioinformatics tools of metagenomic and metatranscriptomic data analysis, the purpose of which is to assist researchers in deciding the appropriate tools for their microbiome studies. Additionally, we propose an Integrated Meta-Function mapping pipeline to incorporate various reference databases and accelerate functional gene mapping procedures for both metagenomic and metatranscriptomic analyses. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com.
Rocha, Miguel; Fdez-Riverola, Florentino; Santana, Juan
Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...
Mohamad, Mohd; Rocha, Miguel; Paz, Juan; Pinto, Tiago
Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of r...
Jimenez-Gutierrez, L. R.; Barrios-Hernández, C. J.; Pedraza-Ferreira, G. R.; Vera-Cala, L.; Martinez-Perez, F.
Recently, bioinformatics has become a new field of science, indispensable in the analysis of millions of nucleic acids sequences, which are currently deposited in international databases (public or private); these databases contain information of genes, RNA, ORF, proteins, intergenic regions, including entire genomes from some species. The analysis of this information requires computer programs; which were renewed in the use of new mathematical methods, and the introduction of the use of artificial intelligence. In addition to the constant creation of supercomputing units trained to withstand the heavy workload of sequence analysis. However, it is still necessary the innovation on platforms that allow genomic analyses, faster and more effectively, with a technological understanding of all biological processes.
The non-protein amino acid γ-aminobutyric acid (GABA) accumulates in plants in response to a wide variety of environmental cues. Recent data point toward an involvement of GABA in tricarboxylic acid (TCA) cycle activity and respiration, especially in stressed roots. To gain further insights into potential GABA functions in plants, phylogenetic and bioinformatic approaches were undertaken. Phylogenetic reconstruction of the GABA transaminase (GABA-T) protein family revealed the monophyletic nature of plant GABA-Ts. However, this analysis also pointed to the common origin of several plant aminotransferases families, which were found more similar to plant GABA-Ts than yeast and human GABA-Ts. A computational analysis of AtGABA-T co-expressed genes was performed in roots and in stress conditions. This second approach uncovered a strong connection between GABA metabolism and glyoxylate cycle during stress. Both in silico analyses open new perspectives and hypotheses for GABA metabolic functions in plants.
Rocha, Miguel; Fdez-Riverola, Florentino; Mayo, Francisco; Paz, Juan
Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...
Rein, Diane C
Purdue University is a major agricultural, engineering, biomedical, and applied life science research institution with an increasing focus on bioinformatics research that spans multiple disciplines and campus academic units. The Purdue University Libraries (PUL) hired a molecular biosciences specialist to discover, engage, and support bioinformatics needs across the campus. After an extended period of information needs assessment and environmental scanning, the specialist developed a week of focused bioinformatics instruction (Bioinformatics Week) to launch system-wide, library-based bioinformatics services. The specialist employed a two-tiered approach to assess user information requirements and expectations. The first phase involved careful observation and collection of information needs in-context throughout the campus, attending laboratory meetings, interviewing department chairs and individual researchers, and engaging in strategic planning efforts. Based on the information gathered during the integration phase, several survey instruments were developed to facilitate more critical user assessment and the recovery of quantifiable data prior to planning. Given information gathered while working with clients and through formal needs assessments, as well as the success of instructional approaches used in Bioinformatics Week, the specialist is developing bioinformatics support services for the Purdue community. The specialist is also engaged in training PUL faculty librarians in bioinformatics to provide a sustaining culture of library-based bioinformatics support and understanding of Purdue's bioinformatics-related decision and policy making.
Yang, Jack Y; Yang, Mary Qu; Zhu, Mengxia Michelle; Arabnia, Hamid R; Deng, Youping
Bioinformatics and Genomics are closely related disciplines that hold great promises for the advancement of research and development in complex biomedical systems, as well as public health, drug design, comparative genomics, personalized medicine and so on. Research and development in these two important areas are impacting the science and technology.High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing, statistical learning and artificial intelligence approaches to handle the massive bioinformatics and personalized healthcare data, which will obviously have a profound effect on how biomedical research will be conducted toward the improvement of human health and prolonging of human life in the future. The International Society of Intelligent Biological Medicine (http://www.isibm.org) and its official journals, the International Journal of Functional Informatics and Personalized Medicine (http://www.inderscience.com/ijfipm) and the International Journal of Computational Biology and Drug Design (http://www.inderscience.com/ijcbdd) in collaboration with International Conference on Bioinformatics and Computational Biology (Biocomp), touch tomorrow's bioinformatics and personalized medicine throughout today's efforts in promoting the research, education and awareness of the upcoming integrated inter/multidisciplinary field. The 2007 international conference on Bioinformatics and Computational Biology (BIOCOMP07) was held in Las Vegas, the United States of American on June 25-28, 2007. The conference attracted over 400 papers, covering broad research areas in the genomics, biomedicine and bioinformatics. The Biocomp 2007 provides a common platform for the cross fertilization of ideas, and to help shape knowledge and
Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue
Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion. PMID:20495527
Pharmacogenetics refers to the study of the individual pharmacological response based on the genotype. Its objective is to optimize treatment in an individual basis, thereby creating a more efficient and safe personalized therapy. In the second part of this review, the molecular methods of study in pharmacogenetics, including microarray technology or DNA chips, are discussed. Among them we highlight the microarrays used to determine the gene expression that detect specific RNA sequences, and the microarrays employed to determine the genotype that detect specific DNA sequences, including polymorphisms, particularly single nucleotide polymorphisms (SNPs). The relationship between pharmacogenetics, bioinformatics and ethical concerns is reviewed.
Wiwanitkit, Somsri; Wiwanitkit, Viroj
The role of microRNA in the pathogenesis of pulmonary tuberculosis is the interesting topic in chest medicine at present. Recently, it was proposed that the microRNA can be a useful biomarker for monitoring of pulmonary tuberculosis and might be the important part in pathogenesis of disease. Here, the authors perform a bioinformatics study to assess the microRNA within known tuberculosis RNA. The microRNA part can be detected and this can be important key information in further study of the p...
Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano
The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical databases and analysis software and the creation of
Full Text Available Abstract Background The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS, can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. Results We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. Conclusion We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical
Rezig, Slim; Sakhri, Saber
Salmonellas are the main responsible agent for the frequent food-borne gastrointestinal diseases. Their detection using classical methods are laborious and their results take a lot of time to be revealed. In this context, we tried to set up a revealing technique of the invA virulence gene, found in the majority of Salmonella species. After amplification with PCR using specific primers created and verified by bioinformatics programs, two couples of primers were set up and they appeared to be very specific and sensitive for the detection of invA gene. (Author)
Commercial success or failure of innovation in bioinformatics and in-silico biology requires the appropriate use of legal tools for protecting and exploiting intellectual property. These tools include patents, copyrights, trademarks, design rights, and limiting information in the form of 'trade secrets'. Potentially patentable components of bioinformatics programmes include lines of code, algorithms, data content, data structure and user interfaces. In both the US and the European Union, copyright protection is granted for software as a literary work, and most other major industrial countries have adopted similar rules. Nonetheless, the grant of software patents remains controversial and is being challenged in some countries. Current debate extends to aspects such as whether patents can claim not only the apparatus and methods but also the data signals and/or products, such as a CD-ROM, on which the programme is stored. The patentability of substances discovered using in-silico methods is a separate debate that is unlikely to be resolved in the near future.
Full Text Available Our previous study demonstrated that human KIAA0100 gene was a novel acute monocytic leukemia-associated antigen (MLAA gene. But the functional characterization of human KIAA0100 gene has remained unknown to date. Here, firstly, bioinformatic prediction of human KIAA0100 gene was carried out using online softwares; Secondly, Human KIAA0100 gene expression was downregulated by the clustered regularly interspaced short palindromic repeats (CRISPR/CRISPR-associated (Cas 9 system in U937 cells. Cell proliferation and apoptosis were next evaluated in KIAA0100-knockdown U937 cells. The bioinformatic prediction showed that human KIAA0100 gene was located on 17q11.2, and human KIAA0100 protein was located in the secretory pathway. Besides, human KIAA0100 protein contained a signalpeptide, a transmembrane region, three types of secondary structures (alpha helix, extended strand, and random coil , and four domains from mitochondrial protein 27 (FMP27. The observation on functional characterization of human KIAA0100 gene revealed that its downregulation inhibited cell proliferation, and promoted cell apoptosis in U937 cells. To summarize, these results suggest human KIAA0100 gene possibly comes within mitochondrial genome; moreover, it is a novel anti-apoptotic factor related to carcinogenesis or progression in acute monocytic leukemia, and may be a potential target for immunotherapy against acute monocytic leukemia.
Ramírez, Sergio; Muñoz-Mérida, Antonio; Karlsson, Johan; García, Maximiliano; Pérez-Pulido, Antonio J.; Claros, M. Gonzalo; Trelles, Oswaldo
The productivity of any scientist is affected by cumbersome, tedious and time-consuming tasks that try to make the heterogeneous web services compatible so that they can be useful in their research. MOWServ, the bioinformatic platform offered by the Spanish National Institute of Bioinformatics, was released to provide integrated access to databases and analytical tools. Since its release, the number of available services has grown dramatically, and it has become one of the main contributors of registered services in the EMBRACE Biocatalogue. The ontology that enables most of the web-service compatibility has been curated, improved and extended. The service discovery has been greatly enhanced by Magallanes software and biodataSF. User data are securely stored on the main server by an authentication protocol that enables the monitoring of current or already-finished user’s tasks, as well as the pipelining of successive data processing services. The BioMoby standard has been greatly extended with the new features included in the MOWServ, such as management of additional information (metadata such as extended descriptions, keywords and datafile examples), a qualified registry, error handling, asynchronous services and service replication. All of them have increased the MOWServ service quality, usability and robustness. MOWServ is available at http://www.inab.org/MOWServ/ and has a mirror at http://www.bitlab-es.com/MOWServ/. PMID:20525794
Pauling, Josch; Klipp, Edda
Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolomics is a broad field under the omics umbrella that may also relate to lipids, lipidomics is an emerging field which specializes in the identification, quantification and functional interpretation of complex lipidomes. Today, it is possible to identify and distinguish lipids in a high-resolution, high-throughput manner and simultaneously with a lot of structural detail. However, doing so may produce thousands of mass spectra in a single experiment which has created a high demand for specialized computational support to analyze these spectral libraries. The computational biology and bioinformatics community has so far established methodology in genomics, transcriptomics and proteomics but there are many (combinatorial) challenges when it comes to structural diversity of lipids and their identification, quantification and interpretation. This review gives an overview and outlook on lipidomics research and illustrates ongoing computational and bioinformatics efforts. These efforts are important and necessary steps to advance the lipidomics field alongside analytic, biochemistry, biomedical and biology communities and to close the gap in available computational methodology between lipidomics and other omics sub-branches.
Protsyuk Ivan V.
Full Text Available Unipro UGENE is an open-source bioinformatics toolkit that integrates popular tools along with original instruments for molecular biologists within a unified user interface. Nowadays, most bioinformatics desktop applications, including UGENE, make use of a local data model while processing different types of data. Such an approach causes an inconvenience for scientists working cooperatively and relying on the same data. This refers to the need of making multiple copies of certain files for every workplace and maintaining synchronization between them in case of modifications. Therefore, we focused on delivering a collaborative work into the UGENE user experience. Currently, several UGENE installations can be connected to a designated shared database and users can interact with it simultaneously. Such databases can be created by UGENE users and be used at their discretion. Objects of each data type, supported by UGENE such as sequences, annotations, multiple alignments, etc., can now be easily imported from or exported to a remote storage. One of the main advantages of this system, compared to existing ones, is the almost simultaneous access of client applications to shared data regardless of their volume. Moreover, the system is capable of storing millions of objects. The storage itself is a regular database server so even an inexpert user is able to deploy it. Thus, UGENE may provide access to shared data for users located, for example, in the same laboratory or institution. UGENE is available at: http://ugene.net/download.html.
Martín-Requena, Victoria; Ríos, Javier; García, Maximiliano; Ramírez, Sergio; Trelles, Oswaldo
Web services technology is becoming the option of choice to deploy bioinformatics tools that are universally available. One of the major strengths of this approach is that it supports machine-to-machine interoperability over a network. However, a weakness of this approach is that various Web Services differ in their definition and invocation protocols, as well as their communication and data formats-and this presents a barrier to service interoperability. jORCA is a desktop client aimed at facilitating seamless integration of Web Services. It does so by making a uniform representation of the different web resources, supporting scalable service discovery, and automatic composition of workflows. Usability is at the top of the jORCA agenda; thus it is a highly customizable and extensible application that accommodates a broad range of user skills featuring double-click invocation of services in conjunction with advanced execution-control, on the fly data standardization, extensibility of viewer plug-ins, drag-and-drop editing capabilities, plus a file-based browsing style and organization of favourite tools. The integration of bioinformatics Web Services is made easier to support a wider range of users. .
Ramirez, Sergio; Karlsson, Johan; Trelles, Oswaldo
Bioinformatics is commonly featured as a well assorted list of available web resources. Although diversity of services is positive in general, the proliferation of tools, their dispersion and heterogeneity complicate the integrated exploitation of such data processing capacity. To facilitate the construction of software clients and make integrated use of this variety of tools, we present a modular programmatic application interface (MAPI) that provides the necessary functionality for uniform representation of Web Services metadata descriptors including their management and invocation protocols of the services which they represent. This document describes the main functionality of the framework and how it can be used to facilitate the deployment of new software under a unified structure of bioinformatics Web Services. A notable feature of MAPI is the modular organization of the functionality into different modules associated with specific tasks. This means that only the modules needed for the client have to be installed, and that the module functionality can be extended without the need for re-writing the software client. The potential utility and versatility of the software library has been demonstrated by the implementation of several currently available clients that cover different aspects of integrated data processing, ranging from service discovery to service invocation with advanced features such as workflows composition and asynchronous services calls to multiple types of Web Services including those registered in repositories (e.g. GRID-based, SOAP, BioMOBY, R-bioconductor, and others).
Full Text Available Human G-protein coupled receptors (hGPCRs constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.
Bokulich, Nicholas A; Rideout, Jai Ram; Mercurio, William G; Shiffer, Arron; Wolfe, Benjamin; Maurice, Corinne F; Dutton, Rachel J; Turnbaugh, Peter J; Knight, Rob; Caporaso, J Gregory
Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/. The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community.
Full Text Available Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L of ethynylestradiol (EE2 and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs, which were subjected to over-representation analysis methods (ORA. Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and
Full Text Available We propose the formation of an International PsychoSocial and Cultural Bioinformatics Project (IPCBP to explore the research foundations of Integrative Medical Insights (IMI on all levels from the molecular-genomic to the psychological, cultural, social, and spiritual. Just as The Human Genome Project identified the molecular foundations of modern medicine with the new technology of sequencing DNA during the past decade, the IPCBP would extend and integrate this neuroscience knowledge base with the technology of gene expression via DNA/proteomic microarray research and brain imaging in development, stress, healing, rehabilitation, and the psychotherapeutic facilitation of existentional wellness. We anticipate that the IPCBP will require a unique international collaboration of, academic institutions, researchers, and clinical practioners for the creation of a new neuroscience of mind-body communication, brain plasticity, memory, learning, and creative processing during optimal experiential states of art, beauty, and truth. We illustrate this emerging integration of bioinformatics with medicine with a videotape of the classical 4-stage creative process in a neuroscience approach to psychotherapy.
Full Text Available We propose the formation of an International Psycho-Social and Cultural Bioinformatics Project (IPCBP to explore the research foundations of Integrative Medical Insights (IMI on all levels from the molecular-genomic to the psychological, cultural, social, and spiritual. Just as The Human Genome Project identified the molecular foundations of modern medicine with the new technology of sequencing DNA during the past decade, the IPCBP would extend and integrate this neuroscience knowledge base with the technology of gene expression via DNA/proteomic microarray research and brain imaging in development, stress, healing, rehabilitation, and the psychotherapeutic facilitation of existentional wellness. We anticipate that the IPCBP will require a unique international collaboration of, academic institutions, researchers, and clinical practioners for the creation of a new neuroscience of mind-body communication, brain plasticity, memory, learning, and creative processing during optimal experiential states of art, beauty, and truth. We illustrate this emerging integration of bioinformatics with medicine with a videotape of the classical 4-stage creative process in a neuroscience approach to psychotherapy.
Yuen Macaire MS
Full Text Available Abstract Background We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL calls that are implemented in a set of Application Programming Interfaces (APIs. The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD, Biomolecular Interaction Network Database (BIND, Database of Interacting Proteins (DIP, Molecular Interactions Database (MINT, IntAct, NCBI Taxonomy, Gene Ontology (GO, Online Mendelian Inheritance in Man (OMIM, LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First
cognized by transcription factors of the bZIP family. The core ACGT element occurs at different relative positions in one or more copies upstream of the minimal promoter region. Protein-DNA interaction studies have shown that sequences flanking the ACGT core affect bZIP protein binding specificity. The bZIP transcription ...
Richards, Stephen; Liu, Yue; Bettencourt, Brian R.
years (Myr) since the pseudoobscura/melanogaster divergence. Genes expressed in the testes had higher amino acid sequence divergence than the genome-wide average, consistent with the rapid evolution of sex-specific proteins. Cis-regulatory sequences are more conserved than random and nearby sequences......We have sequenced the genome of a second Drosophila species, Drosophila pseudoobscura, and compared this to the genome sequence of Drosophila melanogaster, a primary model organism. Throughout evolution the vast majority of Drosophila genes have remained on the same chromosome arm, but within each...... between the species-but the difference is slight, suggesting that the evolution of cis-regulatory elements is flexible. Overall, a pattern of repeat-mediated chromosomal rearrangement, and high coadaptation of both male genes and cis-regulatory sequences emerges as important themes of genome divergence...
David, Aldana P; Margarit, Ezequiel; Domizi, Pablo; Banchio, Claudia; Armas, Pablo; Calcaterra, Nora B
G-quadruplexes are dynamic structures folded in G-rich single-stranded DNA regions. These structures have been recognized as a potential nucleic acid based mechanism for regulating multiple cellular processes such as replication, transcription and genomic maintenance. So far, their transcriptional role in vivo during vertebrate embryonic development has not yet been addressed. Here, we performed an in silico search to find conserved putative G-quadruplex sequences (PQSs) within proximal promoter regions of human, mouse and zebrafish developmental genes. Among the PQSs able to fold in vitro as G-quadruplex, those present in nog3, col2a1 and fzd5 promoters were selected for further studies. In cellulo studies revealed that the selected G-quadruplexes affected the transcription of luciferase controlled by the SV40 nonrelated promoter. G-quadruplex disruption in vivo by microinjection in zebrafish embryos of either small ligands or DNA oligonucleotides complementary to the selected PQSs resulted in lower transcription of the targeted genes. Moreover, zebrafish embryos and larvae phenotypes caused by the presence of complementary oligonucleotides fully resembled those ones reported for nog3, col2a1 and fzd5 morphants. To our knowledge, this is the first work revealing in vivo the role of conserved G-quadruplexes in the embryonic development, one of the most regulated processes of the vertebrates biology. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Full Text Available Abstract Background Much of the organismal variation we observe in nature is due to differences in organ size. The observation that even closely related species can show large, stably inherited differences in organ size indicates a strong genetic component to the control of organ size. Despite recent progress in identifying factors controlling organ growth in plants, our overall understanding of this process remains limited, partly because the individual factors have not yet been connected into larger regulatory pathways or networks. To begin addressing this aim, we have studied the upstream regulation of expression of BIG BROTHER (BB, a central growth-control gene in Arabidopsis thaliana that prevents overgrowth of organs. Final organ size and BB expression levels are tightly correlated, implying the need for precise control of its expression. BB expression mirrors proliferative activity, yet the gene functions to limit proliferation, suggesting that it acts in an incoherent feedforward loop downstream of growth activators to prevent over-proliferation. Results To investigate the upstream regulation of BB we combined a promoter deletion analysis with a phylogenetic footprinting approach. We were able to narrow down important, highly conserved, cis-regulatory elements within the BB promoter. Promoter sequences of other Brassicaceae species were able to partially complement the A. thaliana bb-1 mutant, suggesting that at least within the Brassicaceae family the regulatory pathways are conserved. Conclusions This work underlines the complexity involved in precise quantitative control of gene expression and lays the foundation for identifying important upstream regulators that determine BB expression levels and thus final organ size.
Sebastian, Alvaro; Contreras-Moreira, Bruno
Traditional and high-throughput techniques for determining transcription factor (TF) binding specificities are generating large volumes of data of uneven quality, which are scattered across individual databases. FootprintDB integrates some of the most comprehensive freely available libraries of curated DNA binding sites and systematically annotates the binding interfaces of the corresponding TFs. The first release contains 2422 unique TF sequences, 10 112 DNA binding sites and 3662 DNA motifs. A survey of the included data sources, organisms and TF families was performed together with proprietary database TRANSFAC, finding that footprintDB has a similar coverage of multicellular organisms, while also containing bacterial regulatory data. A search engine has been designed that drives the prediction of DNA motifs for input TFs, or conversely of TF sequences that might recognize input regulatory sequences, by comparison with database entries. Such predictions can also be extended to a single proteome chosen by the user, and results are ranked in terms of interface similarity. Benchmark experiments with bacterial, plant and human data were performed to measure the predictive power of footprintDB searches, which were able to correctly recover 10, 55 and 90% of the tested sequences, respectively. Correctly predicted TFs had a higher interface similarity than the average, confirming its diagnostic value. Web site implemented in PHP,Perl, MySQL and Apache. Freely available from http://floresta.eead.csic.es/footprintdb.
Richards, Stephen; Liu, Yue; Bettencourt, Brian R.; Hradecky, Pavel; Letovsky, Stan; Nielsen, Rasmus; Thornton, Kevin; Todd, Melissa J.; Chen, Rui; Meisel, Richard P.; Couronne, Olivier; Hua, Sujun; Smith, Mark A.; Bussemaker, Harmen J.; van Batenburg, Marinus F.; Howells, Sally L.; Scherer, Steven E.; Sodergren, Erica; Matthews, Beverly B.; Crosby, Madeline A.; Schroeder, Andrew J.; Ortiz-Barrientos, Daniel; Rives, Catherine M.; Metzker, Michael L.; Muzny, Donna M.; Scott, Graham; Steffen, David; Wheeler, David A.; Worley, Kim C.; Havlak, Paul; Durbin, K. James; Egan, Amy; Gill, Rachel; Hume, Jennifer; Morgan, Margaret B.; Miner, George; Hamilton, Cerissa; Huang, Yanmei; Waldron, Lenee; Verduzco, Daniel; Blankenburg, Kerstin P.; Dubchak, Inna; Noor, Mohamed A.F.; Anderson, Wyatt; White, Kevin P.; Clark, Andrew G.; Schaeffer, Stephen W.; Gelbart, William; Weinstock, George M.; Gibbs, Richard A.
The genome sequence of a second fruit fly, D. pseudoobscura, presents an opportunity for comparative analysis of a primary model organism D. melanogaster. The vast majority of Drosophila genes have remained on the same arm, but within each arm gene order has been extensively reshuffled leading to the identification of approximately 1300 syntenic blocks. A repetitive sequence is found in the D. pseudoobscura genome at many junctions between adjacent syntenic blocks. Analysis of this novel repetitive element family suggests that recombination between offset elements may have given rise to many paracentric inversions, thereby contributing to the shuffling of gene order in the D. pseudoobscura lineage. Based on sequence similarity and synteny, 10,516 putative orthologs have been identified as a core gene set conserved over 35 My since divergence. Genes expressed in the testes had higher amino acid sequence divergence than the genome wide average consistent with the rapid evolution of sex-specific proteins. Cis-regulatory sequences are more conserved than control sequences between the species but the difference is slight, suggesting that the evolution of cis-regulatory elements is flexible. Overall, a picture of repeat mediated chromosomal rearrangement, and high co-adaptation of both male genes and cis-regulatory sequences emerges as important themes of genome divergence between these species of Drosophila.
Zhou, Yinhua; Datta, Saheli; Salter, Charlotte
The governments of China, India, and the United Kingdom are unanimous in their belief that bioinformatics should supply the link between basic life sciences research and its translation into health benefits for the population and the economy. Yet at the same time, as ambitious states vying for position in the future global bioeconomy they differ considerably in the strategies adopted in pursuit of this goal. At the heart of these differences lies the interaction between epistemic change within the scientific community itself and the apparatus of the state. Drawing on desk-based research and thirty-two interviews with scientists and policy makers in the three countries, this article analyzes the politics that shape this interaction. From this analysis emerges an understanding of the variable capacities of different kinds of states and political systems to work with science in harnessing the potential of new epistemic territories in global life sciences innovation. PMID:27546935
Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the graphics processing unit (GPU) and the central processing unit (CPU). It adapts to the implementation according to the number of CPUs given as input by efficiently distributing the workload between the processing units. Using existing resources (GPU and CPU) in an efficient way is a novel approach. The peak performance achieved for the platforms GPU + CPU, GPU + 2CPUs, and GPU + 3CPUs is 10.4 GCUPS, 13.7 GCUPS, and 18.6 GCUPS, respectively (with the query length of 511 amino acid). © 2010 IEEE.
Samish, Ilan; Bourne, Philip E; Najmanovich, Rafael J
The field of structural bioinformatics and computational biophysics has undergone a revolution in the last 10 years. Developments that are captured annually through the 3DSIG meeting, upon which this article reflects. An increase in the accessible data, computational resources and methodology has resulted in an increase in the size and resolution of studied systems and the complexity of the questions amenable to research. Concomitantly, the parameterization and efficiency of the methods have markedly improved along with their cross-validation with other computational and experimental results. The field exhibits an ever-increasing integration with biochemistry, biophysics and other disciplines. In this article, we discuss recent achievements along with current challenges within the field. © The Author 2014. Published by Oxford University Press.
Andrew F. Hill
Full Text Available Extracellular vesicles (EVs are the collective term for the various vesicles that are released by cells into the extracellular space. Such vesicles include exosomes and microvesicles, which vary by their size and/or protein and genetic cargo. With the discovery that EVs contain genetic material in the form of RNA (evRNA has come the increased interest in these vesicles for their potential use as sources of disease biomarkers and potential therapeutic agents. Rapid developments in the availability of deep sequencing technologies have enabled the study of EV-related RNA in detail. In October 2012, the International Society for Extracellular Vesicles (ISEV held a workshop on “evRNA analysis and bioinformatics.” Here, we report the conclusions of one of the roundtable discussions where we discussed evRNA analysis technologies and provide some guidelines to researchers in the field to consider when performing such analysis.
Sahinidis, N V; Harandi, M T; Heath, M T; Murphy, L; Snir, M; Wheeler, R P; Zukoski, C F
The development of the Bioinformatics MS degree program at the University of Illinois, the challenges and opportunities associated with such a process, and the current structure of the program is described. This program has departed from earlier University practice in significant ways. Despite the existence of several interdisciplinary programs at the University, a few of which grant degrees, this is the first interdisciplinary program that grants degrees and formally recognises departmental specialisation areas. The program, which is not owned by any particular department but by the Graduate College itself, is operated in a franchise-like fashion via several departmental concentrations. With four different colleges and many more departments involved in establishing and operating the program, the logistics of the operation are of considerable complexity but result in significant interactions across the entire campus.
Huynh, Tien; Rigoutsos, Isidore; Parida, Laxmi; Platt, Daniel; Shibuya, Tetsuo
We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.
Leclère, Valérie; Weber, Tilmann; Jacques, Philippe
-dimensional structure of the peptides can be compared with the structural patterns of all known NRPs. The presented workflow leads to an efficient and rapid screening of genomic data generated by high throughput technologies. The exploration of such sequenced genomes may lead to the discovery of new drugs (i......This chapter helps in the use of bioinformatics tools relevant to the discovery of new nonribosomal peptides (NRPs) produced by microorganisms. The strategy described can be applied to draft or fully assembled genome sequences. It relies on the identification of the synthetase genes...... and the deciphering of the domain architecture of the nonribosomal peptide synthetases (NRPSs). In the next step, candidate peptides synthesized by these NRPSs are predicted in silico, considering the specificity of incorporated monomers together with their isomery. To assess their novelty, the two...
Full Text Available The emerging single-cell RNA-Seq (scRNA-Seq technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal the intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to reveal the complexity in scRNA-Seq data is just as challenging. Here we review the current state-of-the-art bioinformatics tools and methods for scRNA-Seq analysis, as well as addressing some critical analytical challenges that the field faces.
Scheuermann, Richard H; Sinkovits, Robert S; Schenkelberg, Theodore; Koff, Wayne C
Biomedical research has become a data intensive science in which high throughput experimentation is producing comprehensive data about biological systems at an ever-increasing pace. The Human Vaccines Project is a new public-private partnership, with the goal of accelerating development of improved vaccines and immunotherapies for global infectious diseases and cancers by decoding the human immune system. To achieve its mission, the Project is developing a Bioinformatics Hub as an open-source, multidisciplinary effort with the overarching goal of providing an enabling infrastructure to support the data processing, analysis and knowledge extraction procedures required to translate high throughput, high complexity human immunology research data into biomedical knowledge, to determine the core principles driving specific and durable protective immune responses.
Goto, Naohisa; Prins, Pjotr; Nakao, Mitsuteru; Bonnal, Raoul; Aerts, Jan; Katayama, Toshiaki
The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO. BioRuby comes with a tutorial, documentation and an interactive environment, which can be used in the shell, and in the web browser. BioRuby is free and open source software, made available under the Ruby license. BioRuby runs on all platforms that support Ruby, including Linux, Mac OS X and Windows. And, with JRuby, BioRuby runs on the Java Virtual Machine. The source code is available from http://www.bioruby.org/. firstname.lastname@example.org
Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J
DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.
Full Text Available Bioinformatics tools are recently used in various sectors of biology. Many questions regarding Neurodevelopmental disorder which arises as a major health issue recently can be solved by using various bioinformatics databases. Schizophrenia is such a mental disorder which is now arises as a major threat in young age people because it is mostly seen in case of people during their late adolescence or early adulthood period. Databases like DISGENET, GWAS, PHARMGKB, and DRUGBANK have huge repository of genes associated with schizophrenia. We found a lot of genes are being associated with schizophrenia, but approximately 200 genes are found to be present in any of these databases. After further screening out process 20 genes are found to be highly associated with each other and are also a common genes in many other diseases also. It is also found that they all are serves as a common targeting gene in many antipsychotic drugs. After analysis of various biological properties, molecular function it is found that these 20 genes are mostly involved in biological regulation process and are having receptor activity. They are belonging mainly to receptor protein class. Among these 20 genes CYP2C9, CYP3A4, DRD2, HTR1A, HTR2A are shown to be a main targeting genes of most of the antipsychotic drugs and are associated with more than 40% diseases. The basic findings of the present study enumerated that a suitable combined drug can be design by targeting these genes which can be used for the better treatment of schizophrenia.
Although the era of big data has produced many bioinformatics tools and databases, using them effectively often requires specialized knowledge. Many groups lack bioinformatics expertise, and frequently find that software documentation is inadequate and local colleagues may be overburdened or unfamil...
Gammeltoft, Steen; Christensen, Søren Tvorup; Joachimiak, Marcin
Tetrahymena, bioinformatics, cilia, evolution, signaling, TtPTK1, PTK, Grb2, SH-PTP 2, Plcy, Src, PTP, PI3K, SH2, SH3, PH......Tetrahymena, bioinformatics, cilia, evolution, signaling, TtPTK1, PTK, Grb2, SH-PTP 2, Plcy, Src, PTP, PI3K, SH2, SH3, PH...
Hettne, K.M.; Kleinjans, J.; Stierum, R.H.; Boorsma, A.; Kors, J.A.
This chapter concerns the application of bioinformatics methods to the analysis of toxicogenomics data. The chapter starts with an introduction covering how bioinformatics has been applied in toxicogenomics data analysis, and continues with a description of the foundations of a specific
Sutcliffe, Iain C.; Cummings, Stephen P.
Bioinformatics has emerged as an important discipline within the biological sciences that allows scientists to decipher and manage the vast quantities of data (such as genome sequences) that are now available. Consequently, there is an obvious need to provide graduates in biosciences with generic, transferable skills in bioinformatics. We present…
An introductory bioinformatics laboratory experiment focused on protein analysis has been developed that is suitable for undergraduate students in introductory biochemistry courses. The laboratory experiment is designed to be potentially used as a "stand-alone" activity in which students are introduced to basic bioinformatics tools and…
Vincent, Antony T.; Bourbonnais, Yves; Brouard, Jean-Simon; Deveau, Hélène; Droit, Arnaud; Gagné, Stéphane M.; Guertin, Michel; Lemieux, Claude; Rathier, Louis; Charette, Steve J.; Lagüe, Patrick
A recent scientific discipline, bioinformatics, defined as using informatics for the study of biological problems, is now a requirement for the study of biological sciences. Bioinformatics has become such a powerful and popular discipline that several academic institutions have created programs in this field, allowing students to become…
Grisham, William; Schottler, Natalie A.; Valli-Marill, Joanne; Beck, Lisa; Beatty, Jackson
This completely computer-based module's purpose is to introduce students to bioinformatics resources. We present an easy-to-adopt module that weaves together several important bioinformatic tools so students can grasp how these tools are used in answering research questions. Students integrate information gathered from websites dealing with…
We incorporated a bioinformatics component into the freshman biology course that allows students to explore cystic fibrosis (CF), a common genetic disorder, using bioinformatics tools and skills. Students learn about CF through searching genetic databases, analyzing genetic sequences, and observing the three-dimensional structures of proteins…
Floraino, Wely B.
This article discusses the challenges that bioinformatics education is facing and describes a bioinformatics course that is successfully taught at the California State Polytechnic University, Pomona, to the fourth year undergraduate students in biological sciences, chemistry, and computer science. Information on lecture and computer practice…
The purpose of this paper is to investigate the inclusion of bioinformatics in program curricula in the Middle East, focusing on educational institutions in the Arabian Gulf. Bioinformatics is a multidisciplinary field which has emerged in response to the need for efficient data storage and retrieval, and accurate and fast computational and…
Likic, Vladimir A.
This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…
Face-to-face bioinformatics courses commonly include a weekly, in-person computer lab to facilitate active learning, reinforce conceptual material, and teach practical skills. Similarly, fully-online bioinformatics courses employ hands-on exercises to achieve these outcomes, although students typically perform this work offsite. Combining a…
Wefer, Stephen H.; Sheppard, Keith
The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics…
The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics, an...
Krilowicz, Beverly; Johnston, Wendie; Sharp, Sandra B.; Warter-Perez, Nancy; Momand, Jamil
A summer program was created for undergraduates and graduate students that teaches bioinformatics concepts, offers skills in professional development, and provides research opportunities in academic and industrial institutions. We estimate that 34 of 38 graduates (89%) are in a career trajectory that will use bioinformatics. Evidence from…
Wightman, Bruce; Hark, Amy T.
The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this…
Background: Scientific research in bio-informatics is often data-driven and supported by biolog- ical databases. In a growing number of research projects, researchers like to ask questions that require the combination of information from more than one database. Most bio-informatics papers do not
Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu
Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.
Background Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists’ toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment. Results We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy’s capability for enriching, modifying and querying biomedical ontologies. Conclusions Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses. PMID:23286517
Brazas, Michelle D; Yim, David; Yeung, Winston; Ouellette, B F Francis
The 2012 Bioinformatics Links Directory update marks the 10th special Web Server issue from Nucleic Acids Research. Beginning with content from their 2003 publication, the Bioinformatics Links Directory in collaboration with Nucleic Acids Research has compiled and published a comprehensive list of freely accessible, online tools, databases and resource materials for the bioinformatics and life science research communities. The past decade has exhibited significant growth and change in the types of tools, databases and resources being put forth, reflecting both technology changes and the nature of research over that time. With the addition of 90 web server tools and 12 updates from the July 2012 Web Server issue of Nucleic Acids Research, the Bioinformatics Links Directory at http://bioinformatics.ca/links_directory/ now contains an impressive 134 resources, 455 databases and 1205 web server tools, mirroring the continued activity and efforts of our field.
Ranganathan, Shoba; Eisenhaber, Frank; Tong, Joo Chuan; Tan, Tin Wee
The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation dating back to 1998, was organized as the 8th International Conference on Bioinformatics (InCoB), Sept. 7-11, 2009 at Biopolis, Singapore. Besides bringing together scientists from the field of bioinformatics in this region, InCoB has actively engaged clinicians and researchers from the area of systems biology, to facilitate greater synergy between these two groups. InCoB2009 followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India), Hong Kong and Taipei (Taiwan), with InCoB2010 scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010. The Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and symposia on Clinical Bioinformatics (CBAS), the Singapore Symposium on Computational Biology (SYMBIO) and training tutorials were scheduled prior to the scientific meeting, and provided ample opportunity for in-depth learning and special interest meetings for educators, clinicians and students. We provide a brief overview of the peer-reviewed bioinformatics manuscripts accepted for publication in this supplement, grouped into thematic areas. In order to facilitate scientific reproducibility and accountability, we have, for the first time, introduced minimum information criteria for our pubilcations, including compliance to a Minimum Information about a Bioinformatics Investigation (MIABi). As the regional research expertise in bioinformatics matures, we have delineated a minimum set of bioinformatics skills required for addressing the computational challenges of the "-omics" era.
Cheung David W
Full Text Available Abstract Background Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applications are available through the web, but it is difficult to automate interoperation because: 1 the platforms on which the applications run are heterogeneous, 2 their web interface is not machine-friendly, 3 they use a non-standard format for data input and output, 4 they do not exploit standards to define application interface and message exchange, and 5 existing protocols for remote messaging are often not firewall-friendly. To overcome these issues, web services have emerged as a standard XML-based model for message exchange between heterogeneous applications. Web services engines have been developed to manage the configuration and execution of a web services workflow. Results To demonstrate the benefit of using web services over traditional web interfaces, we compare the two implementations of HAPI, a gene expression analysis utility developed by the University of California San Diego (UCSD that allows visual characterization of groups or clusters of genes based on the biomedical literature. This utility takes a set of microarray spot IDs as input and outputs a hierarchy of MeSH Keywords that correlates to the input and is grouped by Medical Subject Heading (MeSH category. While the HTML output is easy for humans to visualize, it is difficult for computer applications to interpret semantically. To facilitate the capability of machine processing, we have created a workflow of three web services that replicates the HAPI functionality. These web services use document-style messages, which means that messages are encoded in an XML-based format. We compared three approaches to the implementation of an XML-based workflow: a hard coded Java application, Collaxa BPEL Server and Taverna Workbench. The Java program functions as a web services engine and interoperates
Wren, Jonathan D
To analyze the relative proportion of bioinformatics papers and their non-bioinformatics counterparts in the top 20 most cited papers annually for the past two decades. When defining bioinformatics papers as encompassing both those that provide software for data analysis or methods underlying data analysis software, we find that over the past two decades, more than a third (34%) of the most cited papers in science were bioinformatics papers, which is approximately a 31-fold enrichment relative to the total number of bioinformatics papers published. More than half of the most cited papers during this span were bioinformatics papers. Yet, the average 5-year JIF of top 20 bioinformatics papers was 7.7, whereas the average JIF for top 20 non-bioinformatics papers was 25.8, significantly higher (P papers, bioinformatics journals tended to have higher Gini coefficients, suggesting that development of novel bioinformatics resources may be somewhat 'hit or miss'. That is, relative to other fields, bioinformatics produces some programs that are extremely widely adopted and cited, yet there are fewer of intermediate success. email@example.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org.
Orozco, Allan; Morera, Jessica; Jiménez, Sergio; Boza, Ricardo
Today, Bioinformatics has become a scientific discipline with great relevance for the Molecular Biosciences and for the Omics sciences in general. Although developed countries have progressed with large strides in Bioinformatics education and research, in other regions, such as Central America, the advances have occurred in a gradual way and with little support from the Academia, either at the undergraduate or graduate level. To address this problem, the University of Costa Rica's Medical School, a regional leader in Bioinformatics in Central America, has been conducting a series of Bioinformatics workshops, seminars and courses, leading to the creation of the region's first Bioinformatics Master's Degree. The recent creation of the Central American Bioinformatics Network (BioCANET), associated to the deployment of a supporting computational infrastructure (HPC Cluster) devoted to provide computing support for Molecular Biology in the region, is providing a foundational stone for the development of Bioinformatics in the area. Central American bioinformaticians have participated in the creation of as well as co-founded the Iberoamerican Bioinformatics Society (SOIBIO). In this article, we review the most recent activities in education and research in Bioinformatics from several regional institutions. These activities have resulted in further advances for Molecular Medicine, Agriculture and Biodiversity research in Costa Rica and the rest of the Central American countries. Finally, we provide summary information on the first Central America Bioinformatics International Congress, as well as the creation of the first Bioinformatics company (Indromics Bioinformatics), spin-off the Academy in Central America and the Caribbean.
Smith, David Roy
Advancements in high-throughput nucleotide sequencing techniques have brought with them state-of-the-art bioinformatics programs and software packages. Given the importance of molecular sequence data in contemporary life science research, these software suites are becoming an essential component of many labs and classrooms, and as such are frequently designed for non-computer specialists and marketed as one-stop bioinformatics toolkits. Although beautifully designed and powerful, user-friendly bioinformatics packages can be expensive and, as more arrive on the market each year, it can be difficult for researchers, teachers and students to choose the right software for their needs, especially if they do not have a bioinformatics background. This review highlights some of the currently available and most popular commercial bioinformatics packages, discussing their prices, usability, features and suitability for teaching. Although several commercial bioinformatics programs are arguably overpriced and overhyped, many are well designed, sophisticated and, in my opinion, worth the investment. If you are just beginning your foray into molecular sequence analysis or an experienced genomicist, I encourage you to explore proprietary software bundles. They have the potential to streamline your research, increase your productivity, energize your classroom and, if anything, add a bit of zest to the often dry detached world of bioinformatics. © The Author 2014. Published by Oxford University Press.
Full Text Available Abstract Background The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories. Interfaces developed by public laboratories are often created with limited developer resources. In such environments, reducing the time spent on creating user interfaces allows for a better deployment of resources for specialised tasks, such as data integration or analysis. Laboratories maintaining data resources are challenged to reconcile requirements for software that is reliable, functional and flexible with limitations on software development resources. Results This paper proposes a model-driven approach for the partial generation of user interfaces for searching and browsing bioinformatics data repositories. Inspired by the Model Driven Architecture (MDA of the Object Management Group (OMG, we have developed a system that generates interfaces designed for use with bioinformatics resources. This approach helps laboratory domain experts decrease the amount of time they have to spend dealing with the repetitive aspects of user interface development. As a result, the amount of time they can spend on gathering requirements and helping develop specialised features increases. The resulting system is known as Pierre, and has been validated through its application to use cases in the life sciences, including the PEDRoDB proteomics database and the e-Fungi data warehouse. Conclusion MDAs focus on generating software from models that describe aspects of service capabilities, and can be applied to support rapid development of repository
Kleftogiannis, Dimitrios A.
Enhancers are cis-acting DNA elements that play critical roles in distal regulation of gene expression. Identifying enhancers is an important step for understanding distinct gene expression programs that may reflect normal and pathogenic cellular conditions. Experimental identification of enhancers is constrained by the set of conditions used in the experiment. This requires multiple experiments to identify enhancers, as they can be active under specific cellular conditions but not in different cell types/tissues or cellular states. This has opened prospects for computational prediction methods that can be used for high-throughput identification of putative enhancers to complement experimental approaches. Potential functions and properties of predicted enhancers have been catalogued and summarized in several enhancer-oriented databases. Because the current methods for the computational prediction of enhancers produce significantly different enhancer predictions, it will be beneficial for the research community to have an overview of the strategies and solutions developed in this field. In this review, we focus on the identification and analysis of enhancers by bioinformatics approaches. First, we describe a general framework for computational identification of enhancers, present relevant data types and discuss possible computational solutions. Next, we cover over 30 existing computational enhancer identification methods that were developed since 2000. Our review highlights advantages, limitations and potentials, while suggesting pragmatic guidelines for development of more efficient computational enhancer prediction methods. Finally, we discuss challenges and open problems of this topic, which require further consideration.
Full Text Available As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.
Wattam, Alice R.; Abraham, David; Dalay, Oral; Disz, Terry L.; Driscoll, Timothy; Gabbard, Joseph L.; Gillespie, Joseph J.; Gough, Roger; Hix, Deborah; Kenyon, Ronald; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olson, Robert; Overbeek, Ross; Pusch, Gordon D.; Shukla, Maulik; Schulman, Julie; Stevens, Rick L.; Sullivan, Daniel E.; Vonstein, Veronika; Warren, Andrew; Will, Rebecca; Wilson, Meredith J.C.; Yoo, Hyun Seung; Zhang, Chengdong; Zhang, Yan; Sobral, Bruno W.
The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein–protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue. PMID:24225323
Daniluk, Paweł; Wilczyński, Bartek; Lesyng, Bogdan
One of the requirements for a successful scientific tool is its availability. Developing a functional web service, however, is usually considered a mundane and ungratifying task, and quite often neglected. When publishing bioinformatic applications, such attitude puts additional burden on the reviewers who have to cope with poorly designed interfaces in order to assess quality of presented methods, as well as impairs actual usefulness to the scientific community at large. In this note we present WeBIAS-a simple, self-contained solution to make command-line programs accessible through web forms. It comprises a web portal capable of serving several applications and backend schedulers which carry out computations. The server handles user registration and authentication, stores queries and results, and provides a convenient administrator interface. WeBIAS is implemented in Python and available under GNU Affero General Public License. It has been developed and tested on GNU/Linux compatible platforms covering a vast majority of operational WWW servers. Since it is written in pure Python, it should be easy to deploy also on all other platforms supporting Python (e.g. Windows, Mac OS X). Documentation and source code, as well as a demonstration site are available at http://bioinfo.imdik.pan.pl/webias . WeBIAS has been designed specifically with ease of installation and deployment of services in mind. Setting up a simple application requires minimal effort, yet it is possible to create visually appealing, feature-rich interfaces for query submission and presentation of results.
Graña, Osvaldo; López-Fernández, Hugo; Fdez-Riverola, Florentino; González Pisano, David; Glez-Peña, Daniel
High-throughput sequencing of bisulfite-converted DNA is a technique used to measure DNA methylation levels. Although a considerable number of computational pipelines have been developed to analyze such data, none of them tackles all the peculiarities of the analysis together, revealing limitations that can force the user to manually perform additional steps needed for a complete processing of the data. This article presents bicycle, an integrated, flexible analysis pipeline for bisulfite sequencing data. Bicycle analyzes whole genome bisulfite sequencing data, targeted bisulfite sequencing data and hydroxymethylation data. To show how bicycle overtakes other available pipelines, we compared them on a defined number of features that are summarized in a table. We also tested bicycle with both simulated and real datasets, to show its level of performance, and compared it to different state-of-the-art methylation analysis pipelines. Bicycle is publicly available under GNU LGPL v3.0 license at http://www.sing-group.org/bicycle. Users can also download a customized Ubuntu LiveCD including bicycle and other bisulfite sequencing data pipelines compared here. In addition, a docker image with bicycle and its dependencies, which allows a straightforward use of bicycle in any platform (e.g. Linux, OS X or Windows), is also available. email@example.com or firstname.lastname@example.org. Supplementary data are available at Bioinformatics online.
Full Text Available Background and Objectives: Cardiovascular disease is one of the main causes of death in developed and Third World countries. According to the statement of the World Health Organization, it is predicted that death due to heart disease will rise to 23 million by 2030. According to the latest statistics reported by Iran’s Minister of health, 3.39% of all deaths are attributed to cardiovascular diseases and 19.5% are related to myocardial infarction. The aim of this study was to predict coronary artery disease using data mining algorithms. Methods: In this study, various bioinformatics algorithms, such as decision trees, neural networks, support vector machines, clustering, etc., were used to predict coronary heart disease. The data used in this study was taken from several valid databases (including 14 data. Results: In this research, data mining techniques can be effectively used to diagnose different diseases, including coronary artery disease. Also, for the first time, a prediction system based on support vector machine with the best possible accuracy was introduced. Conclusion: The results showed that among the features, thallium scan variable is the most important feature in the diagnosis of heart disease. Designation of machine prediction models, such as support vector machine learning algorithm can differentiate between sick and healthy individuals with 100% accuracy.
Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H
Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.
A comprehensive range of mass spectrometric tools is required to investigate todays life science applications and a strong focus is on addressing the needs of functional proteomics. Application examples are given showing the streamlined process of protein identification from low femtomole amounts of digests. Sample preparation is achieved with a convertible robot for automated 2D gel picking, and MALDI target dispensing. MALDI-TOF or ESI-MS subsequent to enzymatic digestion. A choice of mass spectrometers including Q-q-TOF with multipass capability, MALDI-MS/MS with unsegmented PSD, Ion Trap and FT-MS are discussed for their respective strengths and applications. Bioinformatics software that allows both database work and novel peptide mass spectra interpretation is reviewed. The automated database searching uses either entire digest LC-MS n ESI Ion Trap data or MALDI MS and MS/MS spectra. It is shown how post translational modifications are interactively uncovered and de-novo sequencing of peptides is facilitated
Full Text Available Mitogen‐activated protein kinase kinase kinase (MAPKKK is a component of the MAPK cascade pathway that plays an important role in plant growth, development, and response to abiotic stress, the functions of which have been well characterized in several plant species, such as Arabidopsis, rice, and maize. In this study, we performed genome‐wide and systemic bioinformatics analysis of MAPKKK family genes in Medicago truncatula. In total, there were 73 MAPKKK family members identified by search of homologs, and they were classified into three subfamilies, MEKK, ZIK, and RAF. Based on the genomic duplication function, 72 MtMAPKKK genes were located throughout all chromosomes, but they cluster in different chromosomes. Using microarray data and high‐throughput sequencing‐data, we assessed their expression profiles in growth and development processes; these results provided evidence for exploring their important functions in developmental regulation, especially in the nodulation process. Furthermore, we investigated their expression in abiotic stresses by RNA‐seq, which confirmed their critical roles in signal transduction and regulation processes under stress. In summary, our genome‐wide, systemic characterization and expressional analysis of MtMAPKKK genes will provide insights that will be useful for characterizing the molecular functions of these genes in M. truncatula.
Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.
Enhancers are cis-acting DNA elements that play critical roles in distal regulation of gene expression. Identifying enhancers is an important step for understanding distinct gene expression programs that may reflect normal and pathogenic cellular conditions. Experimental identification of enhancers is constrained by the set of conditions used in the experiment. This requires multiple experiments to identify enhancers, as they can be active under specific cellular conditions but not in different cell types/tissues or cellular states. This has opened prospects for computational prediction methods that can be used for high-throughput identification of putative enhancers to complement experimental approaches. Potential functions and properties of predicted enhancers have been catalogued and summarized in several enhancer-oriented databases. Because the current methods for the computational prediction of enhancers produce significantly different enhancer predictions, it will be beneficial for the research community to have an overview of the strategies and solutions developed in this field. In this review, we focus on the identification and analysis of enhancers by bioinformatics approaches. First, we describe a general framework for computational identification of enhancers, present relevant data types and discuss possible computational solutions. Next, we cover over 30 existing computational enhancer identification methods that were developed since 2000. Our review highlights advantages, limitations and potentials, while suggesting pragmatic guidelines for development of more efficient computational enhancer prediction methods. Finally, we discuss challenges and open problems of this topic, which require further consideration.
Wattam, Alice R; Abraham, David; Dalay, Oral; Disz, Terry L; Driscoll, Timothy; Gabbard, Joseph L; Gillespie, Joseph J; Gough, Roger; Hix, Deborah; Kenyon, Ronald; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K; Olson, Robert; Overbeek, Ross; Pusch, Gordon D; Shukla, Maulik; Schulman, Julie; Stevens, Rick L; Sullivan, Daniel E; Vonstein, Veronika; Warren, Andrew; Will, Rebecca; Wilson, Meredith J C; Yoo, Hyun Seung; Zhang, Chengdong; Zhang, Yan; Sobral, Bruno W
The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10,000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.
Wang, Liming; Zhu, L; Luan, R; Wang, L; Fu, J; Wang, X; Sui, L
Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.
Full Text Available Dilated cardiomyopathy (DCM is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs and microRNAs (miRNAs of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family. Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1, potential TFs, as well as potential miRNAs, might be involved in DCM.
Cochrane, Guy; Apweiler, Rolf; Birney, Ewan
Abstract The European Bioinformatics Institute (EMBL-EBI) supports life-science research throughout the world by providing open data, open-source software and analytical tools, and technical infrastructure (https://www.ebi.ac.uk). We accommodate an increasingly diverse range of data types and integrate them, so that biologists in all disciplines can explore life in ever-increasing detail. We maintain over 40 data resources, many of which are run collaboratively with partners in 16 countries (https://www.ebi.ac.uk/services). Submissions continue to increase exponentially: our data storage has doubled in less than two years to 120 petabytes. Recent advances in cellular imaging and single-cell sequencing techniques are generating a vast amount of high-dimensional data, bringing to light new cell types and new perspectives on anatomy. Accordingly, one of our main focus areas is integrating high-quality information from bioimaging, biobanking and other types of molecular data. This is reflected in our deep involvement in Open Targets, stewarding of plant phenotyping standards (MIAPPE) and partnership in the Human Cell Atlas data coordination platform, as well as the 2017 launch of the Omics Discovery Index. This update gives a birds-eye view of EMBL-EBI’s approach to data integration and service development as genomics begins to enter the clinic. PMID:29186510
Gonzalo S. Nido
Full Text Available We propose here a working unit for teaching basic concepts of structural bioinformatics and evolution through the example of a wooden snake puzzle, strikingly similar to toy models widely used in the literature of protein folding. In our experience, developed at a Master’s course at the Universidad Autónoma de Madrid (Spain, the concreteness of this example helps to overcome difficulties caused by the interdisciplinary nature of this field and its high level of abstraction, in particular for students coming from traditional disciplines. The puzzle will allow us discussing a simple algorithm for finding folded solutions, through which we will introduce the concept of the configuration space and the contact matrix representation. This is a central tool for comparing protein structures, for studying simple models of protein energetics, and even for a qualitative discussion of folding kinetics, through the concept of the Contact Order. It also allows a simple representation of misfolded conformations and their free energy. These concepts will motivate evolutionary questions, which we will address by simulating a structurally constrained model of protein evolution, again modelled on the snake puzzle. In this way, we can discuss the analogy between evolutionary concepts and statistical mechanics that facilitates the understanding of both concepts. The proposed examples and literature are accessible, and we provide supplementary material (see ‘Data Availability’ to reproduce the numerical experiments. We also suggest possible directions to expand the unit. We hope that this work will further stimulate the adoption of games in teaching practice.
Velankar, S; McNeil, P; Mittard-Runte, V; Suarez, A; Barrell, D; Apweiler, R; Henrick, K
The Macromolecular Structure Database (MSD) group (http://www.ebi.ac.uk/msd/) continues to enhance the quality and consistency of macromolecular structure data in the worldwide Protein Data Bank (wwPDB) and to work towards the integration of various bioinformatics data resources. One of the major obstacles to the improved integration of structural databases such as MSD and sequence databases like UniProt is the absence of up to date and well-maintained mapping between corresponding entries. We have worked closely with the UniProt group at the EBI to clean up the taxonomy and sequence cross-reference information in the MSD and UniProt databases. This information is vital for the reliable integration of the sequence family databases such as Pfam and Interpro with the structure-oriented databases of SCOP and CATH. This information has been made available to the eFamily group (http://www.efamily.org.uk/) and now forms the basis of the regular interchange of information between the member databases (MSD, UniProt, Pfam, Interpro, SCOP and CATH). This exchange of annotation information has enriched the structural information in the MSD database with annotation from wider sequence-oriented resources. This work was carried out under the 'Structure Integration with Function, Taxonomy and Sequences (SIFTS)' initiative (http://www.ebi.ac.uk/msd-srv/docs/sifts) in the MSD group.
Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.
Connor, Thomas R; Loman, Nicholas J; Thompson, Simon; Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius; Sheppard, Samuel K; Pallen, Mark J
The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.
Full Text Available This paper presents development in the bioinformatics services industry value chain, based on cloud computing paradigm. As genome sequencing costs per Megabase exponentially drop, industry needs to adopt. Paper has two parts: theoretical analysis and practical example of Seven Bridges Genomics Company. We are focused on explaining organizational, business and financial aspects of new business model in bioinformatics services, rather than technical side of the problem. In the light of that we present twofold business model fit for core bioinformatics research and Information and Communication Technologie (ICT support in the new environment, with higher level of capital utilization and better resistance to business risks.
Costantini, S; Malerba, G; Contreas, G; Corradi, M; Marin Vargas, S P; Giorgetti, A; Maffeis, C
Heterozygous loss-of-function mutations in the glucokinase (GCK) gene cause maturity-onset diabetes of the young (MODY) subtype GCK (GCK-MODY/MODY2). GCK sequencing revealed 16 distinct mutations (13 missense, 1 nonsense, 1 splice site, and 1 frameshift-deletion) co-segregating with hyperglycaemia in 23 GCK-MODY families. Four missense substitutions (c.718A>G/p.Asn240Asp, c.757G>T/p.Val253Phe, c.872A>C/p.Lys291Thr, and c.1151C>T/p.Ala384Val) were novel and a founder effect for the nonsense mutation (c.76C>T/p.Gln26*) was supposed. We tested whether an accurate bioinformatics approach could strengthen family-genetic evidence for missense variant pathogenicity in routine diagnostics, where wet-lab functional assays are generally unviable. In silico analyses of the novel missense variants, including orthologous sequence conservation, amino acid substitution (AAS)-pathogenicity predictors, structural modeling and splicing predictors, suggested that the AASs and/or the underlying nucleotide changes are likely to be pathogenic. This study shows how a careful bioinformatics analysis could provide effective suggestions to help molecular-genetic diagnosis in absence of wet-lab validations. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Kumaran, Sharmilah Kumari; Bakar, Mohd Faizal Abu; Mohd-Padil, Hirzahida; Mat-Sharani, Shuhaila; Sakinah, S; Poorani, K; Alsaeedy, Hiba; Peli, Amira; Wei, Teh Seoh; Ling, Mok Pooi; Hamat, Rukman Awang; Neela, Vasantha Kumari; Higuchi, Akon; Alarfaj, Abdullah A; Rajan, Mariappan; Benelli, Giovanni; Arulselvan, Palanisamy; Kumar, S Suresh
Leptospirosis is a widespread zoonotic disease caused by pathogenic Leptospira species (Leptospiraceae). LipL32 is an abundant lipoprotein from the outer membrane proteins (OMPs) group, highly conserved among pathogenic and intermediate Leptospira species. Several studies used LipL32 as a specific gene to identify the presence of leptospires. This research was aimed to study the characteristics of LipL32 protein gene code, to fill the knowledge gap concerning the most appropriate gene that can be used as antigen to detect the Leptospira. Here, we investigated the features of LipL32 in fourteen Leptospira pathogenic strains based on comparative analyses of their primary, secondary structures and 3D modeling using a bioinformatics approach. Furthermore, the physicochemical properties of LipL32 in different strains were studied, shedding light on the identity of signal peptides, as well as on the secondary and tertiary structure of the LipL32 protein, supported by 3D modelling assays. The results showed that the LipL32 gene was present in all the fourteen pathogenic Leptospira strains used in this study, with limited diversity in terms of sequence conservation, hydrophobic group, hydrophilic group and number of turns (random coil). Overall, these results add basic knowledge to the characteristics of LipL32 protein, contributing to the identification of potential antigen candidates in future research, in order to ensure prompt and reliable detection of pathogenic Leptospira species. Copyright © 2017 Elsevier B.V. All rights reserved.
Gadzalski, Marek; Sakowicz, Tomasz
Although short interspersed elements (SINEs) were discovered nearly 30 years ago, the studies of these genomic repeats were mostly limited to animal genomes. Very little is known about SINEs in legumes--one of the most important plant families. Here we report identification, genomic distribution and molecular features of six novel SINE elements in Lotus japonicus (named LJ_SINE-1, -2, -3) and Medicago truncatula (MT_SINE-1, -2, -3), model species of legume. They possess all the structural features commonly found in short interspersed elements including RNA polymerase III promoter, polyA tail and flanking repeats. SINEs described here are present in low to moderate copy numbers from 150 to 3000. Bioinformatic analyses were used to searched public databases, we have shown that three of new SINE elements from M. truncatula seem to be characteristic of Medicago and Trifolium genera. Two SINE families have been found in L. japonicus and one is present in both M. truncatula and L. japonicus. In addition, we are discussing potential activities of the described elements. Copyright © 2011 Elsevier B.V. All rights reserved.
Zhu, S W; Liu, Z J; Li, M; Zhu, H Q; Duan, L P
To assess whether the same biological conclusion, diagnostic or curative effects regarding microbial composition of irritable bowel syndrome (IBS) patients could be reached through different bioinformatics pipelines, we used two common bioinformatics pipelines (Uparse V2.0 and Mothur V1.39.5)to analyze the same fecal microbial 16S rRNA high-throughput sequencing data. The two pipelines were used to analyze the diversity and richness of fecal microbial 16S rRNA high-throughput sequencing data of 27 samples, including 9 healthy controls (HC group), 9 diarrhea IBS patients before (IBS group) and after Rifaximin treatment (IBS-treatment, IBSt group). Analyses such as microbial diversity, principal co-ordinates analysis (PCoA), nonmetric multidimensional scaling (NMDS) and linear discriminant analysis effect size (LEfSe) were used to find out the microbial differences among HC group vs. IBS group and IBS group vs. IBSt group. (1) Microbial composition comparison of the 27 samples in the two pipelines showed significant variations at both family and genera levels while no significant variations at phylum level; (2) There was no significant difference in the comparison of HC vs. IBS or IBS vs. IBSt (Uparse: HC vs. IBS, F=0.98, P=0.445; IBS vs. IBSt, F=0.47,P=0.926; Mothur: HC vs.IBS, F=0.82, P=0.646; IBS vs. IBSt, F=0.37, P=0.961). The Shannon index was significantly decreased in IBSt; (3) Both workshops distinguished the significantly enriched genera between HC and IBS groups. For example, Nitrosomonas and Paraprevotella increased while Pseudoalteromonadaceae and Anaerotruncus decreased in HC group through Uparse pipeline, nevertheless Roseburia 62 increased while Butyricicoccus and Moraxellaceae decreased in HC group through Mothur pipeline.Only Uparse pipeline could pick out significant genera between IBS and IBSt, such as Pseudobutyricibrio, Clostridiaceae 1 and Clostridiumsensustricto 1. There were taxonomic and phylogenetic diversity differences between the two
Epp, Laura S.; Boessenkool, Sanne; Bellemain, Eva P.
was systematically evaluated by (i) in silico PCRs using all standard sequences in the EMBL public database as templates, (ii) in vitro PCRs of DNA extracts from surface soil samples from a site in Varanger, northern Norway and (iii) in vitro PCRs of DNA extracts from permanently frozen sediment samples of late......Metabarcoding approaches use total and typically degraded DNA from environmental samples to analyse biotic assemblages and can potentially be carried out for any kinds of organisms in an ecosystem. These analyses rely on specific markers, here called metabarcodes, which should be optimized...... for taxonomic resolution, minimal bias in amplification of the target organism group and short sequence length. Using bioinformatic tools, we developed metabarcodes for several groups of organisms: fungi, bryophytes, enchytraeids, beetles and birds. The ability of these metabarcodes to amplify the target groups...
Singh, Gautam B
This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...
Schneider, Maria Victoria; Griffin, Philippa C; Tyagi, Sonika; Flannery, Madison; Dayalan, Saravanan; Gladman, Simon; Watson-Haigh, Nathan; Bayer, Philipp E; Charleston, Michael; Cooke, Ira; Cook, Rob; Edwards, Richard J; Edwards, David; Gorse, Dominique; McConville, Malcolm; Powell, David; Wilkins, Marc R; Lonie, Andrew
EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia's capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas-Tools, Data, Standards, Platforms, Compute and Training-are described in this article. © The Author 2017. Published by Oxford University Press.
Bonnal, R.J.P.; Smant, G.; Prins, J.C.P.
Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software
Noar, Roslyn D; Daub, Margaret E
Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity) for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity) to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that they may encode
Becerra, José María
Full Text Available We propose the founding of a Natural History bioinformatics framework, which would solve one of the main problems in Natural History: data which is scattered around in many incompatible systems (not only computer systems, but also paper ones. This framework consists of computer resources (hardware and software, methodologies that ease the circulation of data, and staff expert in dealing with computers, who will develop software solutions to the problems encountered by naturalists. This system is organized in three layers: acquisition, data and analysis. Each layer is described, and an account of the elements that constitute it given.
Se presentan las bases de una estructura bioinformática para Historia Natural, que trata de resolver uno de los principales problemas en ésta: la presencia de datos distribuidos a lo largo de muchos sistemas incompatibles entre sí (y no sólo hablamos de sistemas informáticos, sino también en papel. Esta estructura se sustenta en recursos informáticos (en sus dos vertientes: hardware y software, en metodologías que permitan la fácil circulación de los datos, y personal experto en el uso de ordenadores que se encargue de desarrollar soluciones software a los problemas que plantean los naturalistas. Este sistema estaría organizado en tres capas: de adquisición, de datos y de análisis. Cada una de estas capas se describe, indicando los elementos que la componen.
Roslyn D Noar
Full Text Available Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that
Moreews, François; Sallou, Olivier; Ménager, Hervé; Le Bras, Yvan; Monjeaud, Cyril; Blanchet, Christophe; Collin, Olivier
Linux container technologies, as represented by Docker, provide an alternative to complex and time-consuming installation processes needed for scientiﬁc software. The ease of deployment and the process isolation they enable, as well as the reproducibility they permit across environments and versions, are among the qualities that make them interesting candidates for the construction of bioinformatic infrastructures, at any scale from single workstations to high throughput computing architectures. The Docker Hub is a public registry which can be used to distribute bioinformatic software as Docker images. However, its lack of curation and its genericity make it difﬁcult for a bioinformatics user to ﬁnd the most appropriate images needed. BioShaDock is a bioinformatics-focused Docker registry, which provides a local and fully controlled environment to build and publish bioinformatic software as portable Docker images. It provides a number of improvements over the base Docker registry on authentication and permissions management, that enable its integration in existing bioinformatic infrastructures such as computing platforms. The metadata associated with the registered images are domain-centric, including for instance concepts deﬁned in the EDAM ontology, a shared and structured vocabulary of commonly used terms in bioinformatics. The registry also includes user deﬁned tags to facilitate its discovery, as well as a link to the tool description in the ELIXIR registry if it already exists. If it does not, the BioShaDock registry will synchronize with the registry to create a new description in the Elixir registry, based on the BioShaDock entry metadata. This link will help users get more information on the tool such as its EDAM operations, input and output types. This allows integration with the ELIXIR Tools and Data Services Registry, thus providing the appropriate visibility of such images to the bioinformatics community.
Oulas, Anastasis; Minadakis, George; Zachariou, Margarita; Sokratous, Kleitos; Bourdakou, Marilena M; Spyrou, George M
Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine. © The Author 2017. Published by Oxford University Press.
Bultet, Lisandra Aguilar; Aguilar Rodriguez, Jose; Ahrens, Christian H; Ahrne, Erik Lennart; Ai, Ni; Aimo, Lucila; Akalin, Altuna; Aleksiev, Tyanko; Alocci, Davide; Altenhoff, Adrian; Alves, Isabel; Ambrosini, Giovanna; Pedone, Pascale Anderle; Angelina, Paolo; Anisimova, Maria
The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB'...
Evdokim Kovach; Alexey Alekhin; Eduardo Pareja Tobes; Raquel Tobes; Eduardo Pareja; Marina Manrique
Nowadays it is widely accepted that the bioinformatics data analysis is a real bottleneck in many research activities related to life sciences. High-throughput technologies like Next Generation Sequencing (NGS) have completely reshaped the biology and bioinformatics landscape. Undoubtedly NGS has allowed important progress in many life-sciences related fields but has also presented interesting challenges in terms of computation capabilities and algorithms. Many kinds of tasks related with NGS...
Butt, Davin; Roger, Andrew J; Blouin, Christian
Background An increasing number of bioinformatics methods are considering the phylogenetic relationships between biological sequences. Implementing new methodologies using the maximum likelihood phylogenetic framework can be a time consuming task. Results The bioinformatics library libcov is a collection of C++ classes that provides a high and low-level interface to maximum likelihood phylogenetics, sequence analysis and a data structure for structural biological methods. libcov can be used ...
Wang, Daxi; Korhonen, Pasi K; Gasser, Robin B; Young, Neil D
Clonorchis sinensis (family Opisthorchiidae) is an important foodborne parasite that has a major socioeconomic impact on ~35 million people predominantly in China, Vietnam, Korea and the Russian Far East. In humans, infection with C. sinensis causes clonorchiasis, a complex hepatobiliary disease that can induce cholangiocarcinoma (CCA), a malignant cancer of the bile ducts. Central to understanding the epidemiology of this disease is knowledge of genetic variation within and among populations of this parasite. Although most published molecular studies seem to suggest that C. sinensis represents a single species, evidence of karyotypic variation within C. sinensis and cryptic species within a related opisthorchiid fluke (Opisthorchis viverrini) emphasise the importance of studying and comparing the genes and genomes of geographically distinct isolates of C. sinensis. Recently, we sequenced, assembled and characterised a draft nuclear genome of a C. sinensis isolate from Korea and compared it with a published draft genome of a Chinese isolate of this species using a bioinformatic workflow established for comparing draft genome assemblies and their gene annotations. We identified that 50.6% and 51.3% of the Korean and Chinese C. sinensis genomic scaffolds were syntenic, respectively. Within aligned syntenic blocks, the genomes had a high level of nucleotide identity (99.1%) and encoded 15 variable proteins likely to be involved in diverse biological processes. Here, we review current technical challenges of using draft genome assemblies to undertake comparative genomic analyses to quantify genetic variation between isolates of the same species. Using a workflow that overcomes these challenges, we report on a high-quality draft genome for C. sinensis from Korea and comparative genomic analyses, as a basis for future investigations of the genetic structures of C. sinensis populations, and discuss the biotechnological implications of these explorations. Copyright © 2018
Full Text Available RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069. Subsequent statistical analysis determined differentially expressed transcripts ± 1.5-fold change from saline control with P ≤ 0.05. Gene ontology of differentially expressed transcripts was annotated by DAVID and Panther. Physiological characteristics of the study animals are presented in a figure. Bioinformatic analysis by Ingenuity Pathway Analysis was curated, compiled, and presented in tables. A dataset comparison with similar microarray analyses was performed and bioinformatics analysis by Ingenuity Pathway Analysis, DAVID, Panther, and String of differentially expressed genes from each dataset as well as the differentially expressed genes common to all three datasets were curated, compiled, and presented in tables. Finally, a table comparing four bioinformatics tools’ predictions of functions associated with genes common to all three datasets is presented. These data have been further analyzed and interpreted in the companion article “Early transcriptome responses of the bovine mid-cycle corpus luteum to prostaglandin F2 alpha includes cytokine signaling” .
Full Text Available This study was aimed to identify the expression pattern of vascular endothelial growth factor (VEGF in non-small cell lung cancer (NSCLC and to explore its potential correlation with the progression of NSCLC.Gene expression profile GSE39345 was downloaded from the Gene Expression Omnibus database. Twenty healthy controls and 32 NSCLC samples before chemotherapy were analyzed to identify the differentially expressed genes (DEGs. Then pathway enrichment analysis of the DEGs was performed and protein-protein interaction networks were constructed. Particularly, VEGF genes and the VEGF signaling pathway were analyzed. The sub-network was constructed followed by functional enrichment analysis.Total 1666 up-regulated and 1542 down-regulated DEGs were identified. The down-regulated DEGs were mainly enriched in the pathways associated with cancer. VEGFA and VEGFB were found to be the initiating factor of VEGF signaling pathway. In addition, in the epidermal growth factor receptor (EGFR, VEGFA and VEGFB associated sub-network, kinase insert domain receptor (KDR, fibronectin 1 (FN1, transforming growth factor beta induced (TGFBI and proliferating cell nuclear antigen (PCNA were found to interact with at least two of the three hub genes. The DEGs in this sub-network were mainly enriched in Gene Ontology terms related to cell proliferation.EGFR, KDR, FN1, TGFBI and PCNA may interact with VEGFA to play important roles in NSCLC tumorigenesis. These genes and corresponding proteins may have the potential to be used as the targets for either diagnosis or treatment of patients with NSCLC.
Simon C Wagstaff
Full Text Available Snake venom is a potentially lethal and complex mixture of hundreds of functionally diverse proteins that are difficult to purify and hence difficult to characterize. These difficulties have inhibited the development of toxin-targeted therapy, and conventional antivenom is still generated from the sera of horses or sheep immunized with whole venom. Although life-saving, antivenoms contain an immunoglobulin pool of unknown antigen specificity and known redundancy, which necessitates the delivery of large volumes of heterologous immunoglobulin to the envenomed victim, thus increasing the risk of anaphylactoid and serum sickness adverse effects. Here we exploit recent molecular sequence analysis and DNA immunization tools to design more rational toxin-targeted antivenom.We developed a novel bioinformatic strategy that identified sequences encoding immunogenic and structurally significant epitopes from an expressed sequence tag database of a venom gland cDNA library of Echis ocellatus, the most medically important viper in Africa. Focusing upon snake venom metalloproteinases (SVMPs that are responsible for the severe and frequently lethal hemorrhage in envenomed victims, we identified seven epitopes that we predicted would be represented in all isomers of this multimeric toxin and that we engineered into a single synthetic multiepitope DNA immunogen (epitope string. We compared the specificity and toxin-neutralizing efficacy of antiserum raised against the string to antisera raised against a single SVMP toxin (or domains or antiserum raised by conventional (whole venom immunization protocols. The SVMP string antiserum, as predicted in silico, contained antibody specificities to numerous SVMPs in E. ocellatus venom and venoms of several other African vipers. More significantly, the antiserum cross-specifically neutralized hemorrhage induced by E. ocellatus and Cerastes cerastes cerastes venoms.These data provide valuable sequence and structure
Jingyuan Fu promoveert op een onderzoek naar genetische analyses. Onder andere werkte ze aan een nieuw softwarepakket MetaNetwork, dat hulp biedt bij het zoeken naar een optimaal ontwerp van experimenten op het gebied van genetical genomics.
Full Text Available There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy – to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen–scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public.
Wendelsdorf, Katherine; Shah, Sohela
There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS) technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy - to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC) is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen-scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public.
Fan, Zhigang; Zhang, Lingmin; Yan, Guogang; Wu, Qiang; Gan, Xiufeng; Zhong, Saifeng; Lin, Guifen
To analyse the structure and function of NADPH-cytochrome p450 reductase (CYPOR or CPR) from Plasmodium falciparum (Pf), and to predict its' drug target and vaccine target. The structure, function, drug target and vaccine target of CPR from Plasmodium falciparum were analyzed and predicted by bioinformatics methods. PfCPR, which was older CPR, had close relationship with the CPR from other Plasmodium species, but it was distant from its hosts, such as Homo sapiens and Anopheles. PfCPR was located in the cellular nucleus of Plasmodium falciparum. 335aa-352aa and 591aa - 608aa were inserted the interior side of the nuclear membrane, while 151aa-265aa was located in the nucleolus organizer regions. PfCPR had 40 function sites and 44 protein-protein binding sites in amino acid sequence. The teriary structure of 1aa-700aa was forcep-shaped with wings. 15 segments of PfCPR had no homology with Homo sapien CPR and most were exposed on the surface of the protein. These segments had 25 protein-protein binding sites. While 13 other segments all possessed function sites. The evolution or genesis of Plasmodium falciparum is earlier than those of Homo sapiens. PfCPR is a possible resistance site of antimalarial drug and may involve immune evasion, which is associated with parasite of sporozoite in hepatocytes. PfCPR is unsuitable as vaccine target, but it has at least 13 ideal drug targets. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.
Troshin, Peter V; Procter, James B; Sherstnev, Alexander; Barton, Daniel L; Madeira, Fábio; Barton, Geoffrey J
JABAWS 2.2 is a computational framework that simplifies the deployment of web services for Bioinformatics. In addition to the five multiple sequence alignment (MSA) algorithms in JABAWS 1.0, JABAWS 2.2 includes three additional MSA programs (Clustal Omega, MSAprobs, GLprobs), four protein disorder prediction methods (DisEMBL, IUPred, Ronn, GlobPlot), 18 measures of protein conservation as implemented in AACon, and RNA secondary structure prediction by the RNAalifold program. JABAWS 2.2 can be deployed on a variety of in-house or hosted systems. JABAWS 2.2 web services may be accessed from the Jalview multiple sequence analysis workbench (Version 2.8 and later), as well as directly via the JABAWS command line interface (CLI) client. JABAWS 2.2 can be deployed on a local virtual server as a Virtual Appliance (VA) or simply as a Web Application Archive (WAR) for private use. Improvements in JABAWS 2.2 also include simplified installation and a range of utility tools for usage statistics collection, and web services querying and monitoring. The JABAWS CLI client has been updated to support all the new services and allow integration of JABAWS 2.2 services into conventional scripts. A public JABAWS 2 server has been in production since December 2011 and served over 800 000 analyses for users worldwide. JABAWS 2.2 is made freely available under the Apache 2 license and can be obtained from: http://www.compbio.dundee.ac.uk/jabaws. email@example.com.
Guo, Xing-Ya; He, Chong-Xin; Wang, Yu-Qin; Sun, Chao; Li, Guang-Ming; Su, Qing; Pan, Qin; Fan, Jian-Gao
Circular RNAs (circRNAs) exhibit a wide range of physiological and pathological activities. To uncover their role in hepatic steatosis, we investigated the expression profile of circRNAs in HepG2-based hepatic steatosis induced by high-fat stimulation. Differentially expressed circRNAs were subjected to validation using QPCR and functional analyses using principal component analysis, hierarchical clustering, target prediction, gene ontology (GO), and pathway annotation, respectively. Bioinformatic integration established the circRNA-miRNA-mRNA regulatory network so as to identify the mechanisms underlying circRNAs' metabolic effect. Here we reported that hepatic steatosis was associated with a total of 357 circRNAs. Enrichment of transcription-related GOs, especially GO: 0006355, GO: 004589, GO: 0045944, GO: 0045892, and GO: 0000122, demonstrated their specific actions in transcriptional regulation. Lipin 1 (LPIN1) was recognized to mediate the transcriptional regulatory effect of circRNAs on metabolic pathways. circRNA-miRNA-mRNA network further identified the signaling cascade of circRNA_021412/miR-1972/LPIN1, which was characterized by decreased level of circRNA_021412 and miR-1972-based inhibition of LPIN1. LPIN1-induced downregulation of long chain acyl-CoA synthetases (ACSLs) expression finally resulted in the hepatosteatosis. These findings identify circRNAs to be important regulators of hepatic steatosis. Transcription-dependent modulation of metabolic pathways may underlie their effects, partially by the circRNA_021412/miR-1972/LPIN1 signaling.
Smith, Jason T; Harris, Justine C; Lopez, Oscar J; Valverde, Laura; Borchert, Glen M
The sequencing of whole genomes and the analysis of genetic information continues to fundamentally change biological and medical research. Unfortunately, the people best suited to interpret this data (biologically trained researchers) are commonly discouraged by their own perceived computational limitations. To address this, we developed a course to help alleviate this constraint. Remarkably, in addition to equipping our undergraduates with an informatic toolset, we found our course design helped prepare our students for collaborative research careers in unexpected ways. Instead of simply offering a traditional lecture- or laboratory-based course, we chose a guided inquiry method, where an instructor-selected research question is examined by students in a collaborative analysis with students contributing to experimental design, data collection, and manuscript reporting. While students learn the skills needed to conduct bioinformatic research throughout all sections of the course, importantly, students also gain experience in working as a team and develop important communication skills through working with their partner and the class as a whole, and by contributing to an original research article. Remarkably, in its first three semesters, this novel computational genetics course has generated 45 undergraduate authorships across three peer-reviewed articles. More importantly, the students that took this course acquired a positive research experience, newfound informatics technical proficiency, unprecedented familiarity with manuscript preparation, and an earned sense of achievement. Although this course deals with analyses of genetic systems, we suggest the basic concept of integrating actual research projects into a 16-week undergraduate course could be applied to numerous other research-active academic fields. © 2015 The International Union of Biochemistry and Molecular Biology.
Seibel, Philipp N; Krüger, Jan; Hartmeier, Sven; Schwarzer, Knut; Löwenthal, Kai; Mersch, Henning; Dandekar, Thomas; Giegerich, Robert
Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data--therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. Acknowledging the need for common formats, the Helmholtz Open BioInformatics Technology network (HOBIT) identified several basic data types used in bioinformatics and developed appropriate format descriptions, formally defined by XML schemas, and incorporated them in a Java library (BioDOM). These schemas currently cover sequence, sequence alignment, RNA secondary structure and RNA secondary structure alignment formats in a form that is independent of any specific program, thus enabling seamless interoperation of different tools. All XML formats are available at http://bioschemas.sourceforge.net, the BioDOM library can be obtained at http://biodom.sourceforge.net. The HOBIT XML schemas and the BioDOM library simplify adding XML support to newly created and existing bioinformatic tools, enabling these tools to interoperate seamlessly in workflow scenarios.
Balqis, Widodo, Lukiati, Betty; Amin, Mohamad
A way to improve the quality of learning in the course of Plant Metabolism in the Department of Biology, State University of Malang, is to develop teaching materials. This research evaluates the needs of bioinformatics-based teaching material in the course Plant Metabolism by the Analyze, Design, Develop, Implement, and Evaluate (ADDIE) development model. Data were collected through questionnaires distributed to the students in the Plant Metabolism course of the Department of Biology, University of Malang, and analysis of the plan of lectures semester (RPS). Learning gains of this course show that it is not yet integrated into the field of bioinformatics. All respondents stated that plant metabolism books do not include bioinformatics and fail to explain the metabolism of a chemical compound of a local plant in Indonesia. Respondents thought that bioinformatics can explain examples and metabolism of a secondary metabolite analysis techniques and discuss potential medicinal compounds from local plants. As many as 65% of the respondents said that the existing metabolism book could not be used to understand secondary metabolism in lectures of plant metabolism. Therefore, the development of teaching materials including plant metabolism-based bioinformatics is important to improve the understanding of the lecture material in plant metabolism.
Kovarik, Dina N; Patterson, Davis G; Cohen, Carolyn; Sanders, Elizabeth A; Peterson, Karen A; Porter, Sandra G; Chowning, Jeanne Ting
We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The program included best practices in adult education and diverse resources to empower teachers to integrate STEM career information into their classrooms. The introductory unit, Using Bioinformatics: Genetic Testing, uses bioinformatics to teach basic concepts in genetics and molecular biology, and the advanced unit, Using Bioinformatics: Genetic Research, utilizes bioinformatics to study evolution and support student research with DNA barcoding. Pre-post surveys demonstrated significant growth (n = 24) among teachers in their preparation to teach the curricula and infuse career awareness into their classes, and these gains were sustained through the end of the academic year. Introductory unit students (n = 289) showed significant gains in awareness, relevance, and self-efficacy. While these students did not show significant gains in engagement, advanced unit students (n = 41) showed gains in all four cognitive areas. Lessons learned during Bio-ITEST are explored in the context of recommendations for other programs that wish to increase student interest in STEM careers.
Seibel, Philipp N; Krüger, Jan; Hartmeier, Sven; Schwarzer, Knut; Löwenthal, Kai; Mersch, Henning; Dandekar, Thomas; Giegerich, Robert
Background Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data – therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. Results Acknowledging the need for common formats, the Helmholtz Open BioInformatics Technology network (HOBIT) identified several basic data types used in bioinformatics and developed appropriate format descriptions, formally defined by XML schemas, and incorporated them in a Java library (BioDOM). These schemas currently cover sequence, sequence alignment, RNA secondary structure and RNA secondary structure alignment formats in a form that is independent of any specific program, thus enabling seamless interoperation of different tools. All XML formats are available at , the BioDOM library can be obtained at . Conclusion The HOBIT XML schemas and the BioDOM library simplify adding XML support to newly created and existing bioinformatic tools, enabling these tools to interoperate seamlessly in workflow scenarios. PMID:17087823
Liu, Lin; Tang, Lin; Dong, Wen; Yao, Shaowen; Zhou, Wei
With the rapid accumulation of biological datasets, machine learning methods designed to automate data analysis are urgently needed. In recent years, so-called topic models that originated from the field of natural language processing have been receiving much attention in bioinformatics because of their interpretability. Our aim was to review the application and development of topic models for bioinformatics. This paper starts with the description of a topic model, with a focus on the understanding of topic modeling. A general outline is provided on how to build an application in a topic model and how to develop a topic model. Meanwhile, the literature on application of topic models to biological data was searched and analyzed in depth. According to the types of models and the analogy between the concept of document-topic-word and a biological object (as well as the tasks of a topic model), we categorized the related studies and provided an outlook on the use of topic models for the development of bioinformatics applications. Topic modeling is a useful method (in contrast to the traditional means of data reduction in bioinformatics) and enhances researchers' ability to interpret biological information. Nevertheless, due to the lack of topic models optimized for specific biological data, the studies on topic modeling in biological data still have a long and challenging road ahead. We believe that topic models are a promising method for various applications in bioinformatics research.
AWARD NUMBER: W81XWH-15-1-0342 TITLE: Toward Personalized Pressure Ulcer Care Planning: Development of a Bioinformatics System for Individualized...Planning: Development of a Bioinformatics System for Individualized Prioritization of Clinical Pratice Guideline 5a. CONTRACT NUMBER 5b. GRANT...recommendations of CPG has been identified by experts in the field. We will use bioinformatics to enable data extraction, storage, and analysis to support
Fiers, M.W.E.J.; Burgt, van der A.; Datema, E.; Groot, de J.C.W.; Ham, van R.C.H.J.
Background - Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses
Barbara J. May
Full Text Available Bioinformatics spans many fields of biological research and plays a vital role in mining and analyzing data. Therefore, there is an ever-increasing need for students to understand not only what can be learned from this data, but also how to use basic bioinformatics tools. This activity is designed to provide secondary and undergraduate biology students to a hands-on activity meant to explore and understand gene structure with the use of basic bioinformatic tools. Students are provided an “unknown” sequence from which they are asked to use a free online gene finder program to identify the gene. Students then predict the putative function of this gene with the use of additional online databases.
Full Text Available Allergies and/or food intolerances are a growing problem of the modern world. Diffi culties associated with the correct diagnosis of food allergies result in the need to classify the factors causing allergies and allergens themselves. Therefore, internet databases and other bioinformatic tools play a special role in deepening knowledge of biologically-important compounds. Internet repositories, as a source of information on different chemical compounds, including those related to allergy and intolerance, are increasingly being used by scientists. Bioinformatic methods play a signifi cant role in biological and medical sciences, and their importance in food science is increasing. This study aimed at presenting selected databases and tools of bioinformatic analysis useful in research on food allergies, allergens (11 databases, epitopes (7 databases, and haptens (2 databases. It also presents examples of the application of computer methods in studies related to allergies.
Taylor, Ronald C.
Bioinformatics researchers are increasingly confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date.
Morales, Hernán F; Giovambattista, Guillermo
We have developed BioSmalltalk, a new environment system for pure object-oriented bioinformatics programming. Adaptive end-user programming systems tend to become more important for discovering biological knowledge, as is demonstrated by the emergence of open-source programming toolkits for bioinformatics in the past years. Our software is intended to bridge the gap between bioscientists and rapid software prototyping while preserving the possibility of scaling to whole-system biology applications. BioSmalltalk performs better in terms of execution time and memory usage than Biopython and BioPerl for some classical situations. BioSmalltalk is cross-platform and freely available (MIT license) through the Google Project Hosting at http://code.google.com/p/biosmalltalk firstname.lastname@example.org Supplementary data are available at Bioinformatics online.
Liu, Hongyun; Qin, Jiajia; Fan, Hui; Cheng, Jinjin; Li, Lin; Liu, Zheng
As a member of the GRAS gene family, SCARECROW - LIKE ( SCL ) genes encode transcriptional regulators that are involved in plant information transmission and signal transduction. In this study, 44 SCL genes including two SCARECROW genes in millet were identified to be distributed on eight chromosomes, except chromosome 6. All the millet genes contain motifs 6-8, indicating that these motifs are conserved during the evolution. SCL genes of millet were divided into eight groups based on the phylogenetic relationship and classification of Arabidopsis SCL genes. Several putative millet orthologous genes in Arabidopsis , maize and rice were identified. High throughput RNA sequencing revealed that the expressions of millet SCL genes in root, stem, leaf, spica, and along leaf gradient varied greatly. Analyses combining the gene expression patterns, gene structures, motif compositions, promoter cis -elements identification, alternative splicing of transcripts and phylogenetic relationship of SCL genes indicate that the these genes may play diverse functions. Functionally characterized SCL genes in maize, rice and Arabidopsis would provide us some clues for future characterization of their homologues in millet. To the best of our knowledge, this is the first study of millet SCL genes at the genome wide level. Our work provides a useful platform for functional analysis of SCL genes in millet, a model crop for C 4 photosynthesis and bioenergy studies.
Full Text Available Computer-based resources are central to much, if not most, biological and medical research. However, while there is an ever expanding choice of bioinformatics resources to use, described within the biomedical literature, little work to date has provided an evaluation of the full range of availability or levels of usage of database and software resources. Here we use text mining to process the PubMed Central full-text corpus, identifying mentions of databases or software within the scientific literature. We provide an audit of the resources contained within the biomedical literature, and a comparison of their relative usage, both over time and between the sub-disciplines of bioinformatics, biology and medicine. We find that trends in resource usage differs between these domains. The bioinformatics literature emphasises novel resource development, while database and software usage within biology and medicine is more stable and conservative. Many resources are only mentioned in the bioinformatics literature, with a relatively small number making it out into general biology, and fewer still into the medical literature. In addition, many resources are seeing a steady decline in their usage (e.g., BLAST, SWISS-PROT, though some are instead seeing rapid growth (e.g., the GO, R. We find a striking imbalance in resource usage with the top 5% of resource names (133 names accounting for 47% of total usage, and over 70% of resources extracted being only mentioned once each. While these results highlight the dynamic and creative nature of bioinformatics research they raise questions about software reuse, choice and the sharing of bioinformatics practice. Is it acceptable that so many resources are apparently never reused? Finally, our work is a step towards automated extraction of scientific method from text. We make the dataset generated by our study available under the CC0 license here: http://dx.doi.org/10.6084/m9.figshare.1281371.
Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev
Welner, Simon; Nielsen, Morten; Lund, Ole
an effective CTL response against PRRSV, we have taken a bioinformatics approach to identify common PRRSV epitopes predicted to react broadly with predominant swine MHC (SLA) alleles. First, the genomic integrity and sequencing method was examined for 334 available complete PRRSV type 2 genomes leaving 104...... by the PopCover algorithm, providing a final list of 54 epitopes prioritized according to maximum coverage of PRRSV strains and SLA alleles. This bioinformatics approach provides a rational strategy for selecting peptides for a CTL-activating vaccine with broad coverage of both virus and swine diversity...
This book contains 18 contributions from different authors. Its subtitle 'Econophysics, Bioinformatics, and Pattern Recognition' says more precisely what it is about: not so much about central problems of conventional statistical physics like equilibrium phase transitions and critical phenomena, but about its interdisciplinary applications. After a long period of specialization, physicists have, over the last few decades, found more and more satisfaction in breaking out of the limitations set by the traditional classification of sciences. Indeed, this classification had never been strict, and physicists in particular had always ventured into other fields. Helmholtz, in the middle of the 19th century, had considered himself a physicist when working on physiology, stressing that the physics of animate nature is as much a legitimate field of activity as the physics of inanimate nature. Later, Max Delbrueck and Francis Crick did for experimental biology what Schroedinger did for its theoretical foundation. And many of the experimental techniques used in chemistry, biology, and medicine were developed by a steady stream of talented physicists who left their proper discipline to venture out into the wider world of science. The development we have witnessed over the last thirty years or so is different. It started with neural networks where methods could be applied which had been developed for spin glasses, but todays list includes vehicular traffic (driven lattice gases), geology (self-organized criticality), economy (fractal stochastic processes and large scale simulations), engineering (dynamical chaos), and many others. By staying in the physics departments, these activities have transformed the physics curriculum and the view physicists have of themselves. In many departments there are now courses on econophysics or on biological physics, and some universities offer degrees in the physics of traffic or in econophysics. In order to document this change of attitude
Full Text Available Yubin Kou,1,2* Suya Zhang,3* Xiaoping Chen,2 Sanyuan Hu1 1Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People’s Republic of China; 2Department of General Surgery, 3Department of Neurology, Shuguang Hospital Baoshan Branch, Shanghai, People’s Republic of China *These authors contributed equally to this work Abstract: This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t-test. The Gene Ontology (GO functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID software followed by the construction of a protein–protein interaction (PPI network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS, FN1, PPP1CC, and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B in the upregulated PPI network and three modules (d-A, d-B, and d-C in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE Molecular Complex Detection (MCODE score ≥4 and nodes ≥6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative
Brown, James A. L.
A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion,…
Jothi, G. Edward Gnana; Majilla, G. Sahaya Jose; Subhashini, D.; Deivasigamani, B.
In spite of the medical advances in recent years, the world is in need of different sources to encounter certain health issues.Ribosome Inactivating Proteins (RIPs) were found to be one among them. In order to get easy access about RIPs, there is a need to analyse RIPs towards constructing a database on RIPs. Also, multiple sequence alignment was done towards screening for homologues of significant RIPs from rare sources against RIPs from easily available sources in terms of similarity. Protein sequences were retrieved from SWISS-PROT and are further analysed using pair wise and multiple sequence alignment.Analysis shows that, 151 RIPs have been characterized to date. Amongst them, there are 87 type I, 37 type II, 1 type III and 25 unknown RIPs. The sequence length information of various RIPs about the availability of full or partial sequence was also found. The multiple sequence alignment of 37 type I RIP using the online server Multalin, indicates the presence of 20 conserved residues. Pairwise alignment and multiple sequence alignment of certain selected RIPs in two groups namely Group I and Group II were carried out and the consensus level was found to be 98%, 98% and 90% respectively.
Post, L.J.G.; Roos, M.; Marshall, M.S.; van Driel, R.; Breit, T.M.
The numerous public data resources make integrative bioinformatics experimentation increasingly important in life sciences research. However, it is severely hampered by the way the data and information are made available. The semantic web approach enhances data exchange and integration by providing
Manyam, Ganiraju; Payton, Michelle A; Roth, Jack A; Abruzzo, Lynne V; Coombes, Kevin R
With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. Copyright © 2012 Elsevier Inc. All rights reserved.
Manyam, Ganiraju; Payton, Michelle A.; Roth, Jack A.; Abruzzo, Lynne V.; Coombes, Kevin R.
With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. PMID:22609849
Reece, P.; Bremer, M.G.E.G.; Stones, R.; Danks, C.; Baumgartner, S.; Tomkies, V.; Hemetsberger, C.; Smits, N.G.E.; Lubbe, W.
A bioinformatics approach to developing antibodies to specific proteins has been evaluated for the production of antibodies to heat-processed specified risk tissues from ruminants (brain and eye tissue). The approach involved the identification of proteins specific to ruminant tissues by
Mello, Luciane V; Tregilgas, Luke; Cowley, Gwen; Gupta, Anshul; Makki, Fatima; Jhutty, Anjeet; Shanmugasundram, Achchuthan
Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student-staff partnership and peer-learning. It was centred on the experiences of peer-facilitators, students who had previously taken a postgraduate bioinformatics module, and had applied knowledge and skills gained from it to their own research. It aimed to demonstrate to peer-receivers, current students, how bioinformatics could be used in their own research while developing peer-facilitators' teaching and mentoring skills. This student-centred approach was well received by the peer-receivers, who claimed to have gained improved understanding of bioinformatics and its relevance to research. Equally, peer-facilitators also developed a better understanding of the subject and appreciated that the activity was a rare and invaluable opportunity to develop their teaching and mentoring skills, enhancing their employability.
Full Text Available After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.
Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.
Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150
Martin-Sanchez, F.; Iakovidis, I.; Norager, S.; Maojo, V.; de Groen, P.; Van der Lei, J.; Jones, T.; Abraham-Fuchs, K.; Apweiler, R.; Babic, A.; Baud, R.; Breton, V.; Cinquin, P.; Doupi, P.; Dugas, M.; Eils, R.; Engelbrecht, R.; Ghazal, P.; Jehenson, P.; Kulikowski, C.; Lampe, K.; De Moor, G.; Orphanoudakis, S.; Rossing, N.; Sarachan, B.; Sousa, A.; Spekowius, G.; Thireos, G.; Zahlmann, G.; Zvárová, Jana; Hermosilla, I.; Vicente, F. J.
Roč. 37, - (2004), s. 30-42 ISSN 1532-0464 Institutional research plan: CEZ:AV0Z1030915 Keywords : bioinformatics * medical informatics * genomics * genomic medicine * biomedical informatics Subject RIV: BD - Theory of Information Impact factor: 1.013, year: 2004
Kovarik, Dina N.; Patterson, Davis G.; Cohen, Carolyn; Sanders, Elizabeth A.; Peterson, Karen A.; Porter, Sandra G.; Chowning, Jeanne Ting
We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The…
Kesmir, Can; van Noort, V.; de Boer, R.J.
not yet been quantified how different the specificity of two forms of the proteasome are. The main question, which still lacks direct evidence, is whether the immunoproteasome generates more MHC ligands. Here we use bioinformatics tools to quantify these differences and show that the immunoproteasome...
Among posttranslational modifications, there are some conceptual similarities between Lys-N'-acetylation and Ser/Thr/Tyr O-phosphorylation. Herein we present a bioinformatics-based overview of reversible protein Lys-acetylation, including some comparisons with reversible protein phosphorylation. T...
Campbell, Chad E.; Nehm, Ross H.
The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students' knowledge, attitudes, or skills. Although assessments are…
Elwess, Nancy L.; Duprey, Stephen L.; Harney, Lindesay A.; Langman, Jessie E.; Marino, Tara C.; Martinez, Carolina; McKeon, Lauren L.; Moss, Chantel I. E.; Myrie, Sasha S.; Taylor, Luke Ryan
"Alu"-insertion polymorphisms were used by an undergraduate Bioinformatics class to study how these insertion sites could be the basis for an investigation in human population genetics. Based on the students' investigation, both allele and genotype "Alu" frequencies were determined for African-American and Japanese populations as well as a…
Adachi, Jun; Kumar, Chanchal; Zhang, Yanling
, mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized...
Boomsma, Wouter Krogh; Nielsen, Sofie Vincents; Lindorff-Larsen, Kresten
conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology...
Medin, Carey L.; Nolin, Katie L.
Molecular biologists commonly use bioinformatics to map and analyze DNA and protein sequences and to align different DNA and protein sequences for comparison. Additionally, biologists can create and view 3D models of protein structures to further understand intramolecular interactions. The primary goal of this 10-week laboratory was to introduce…
Nan, Jie; Brostromer, Erik; Liu, Xiang-Yu
. From the interlinking structural and bioinformatics studies, we have concluded that SMU.440 could be involved in polyketide-like antibiotic resistance, providing a better understanding of this hypothetical protein. Besides, the combination of multiple methods in this study can be used as a general...
Eisenhaber, Frank; Sherman, Westley Arthur
The Journal of Bioinformatics and Computational Biology (JBCB) started publishing scientific articles in 2003. It has established itself as home for solid research articles in the field (~ 60 per year) that are surprisingly well cited. JBCB has an important function as alternative publishing channel in addition to other, bigger journals.
Alyuruk, Hakan; Cavas, Levent
Genomics and proteomics projects have produced a huge amount of raw biological data including DNA and protein sequences. Although these data have been stored in data banks, their evaluation is strictly dependent on bioinformatics tools. These tools have been developed by multidisciplinary experts for fast and robust analysis of biological data.…
Nogaj, Luiza A.
A nine-week laboratory project designed for a sophomore level molecular biology course is described. Small groups of students (3-4 per group) choose a tumor suppressor gene (TSG) or an oncogene for this project. Each group researches the role of their TSG/oncogene from primary literature articles and uses bioinformatics engines to find the gene…
Shapiro, Casey; Ayon, Carlos; Moberg-Parker, Jordan; Levis-Fitzgerald, Marc; Sanders, Erin R.
This study used a mixed methods approach to evaluate hybrid peer-assisted learning approaches incorporated into a bioinformatics tutorial for a genome annotation research project. Quantitative and qualitative data were collected from undergraduates who enrolled in a research-based laboratory course during two different academic terms at UCLA.…
Wulff, Tune; Silva, T.; Nielsen, Michael Engelbrecht
and magnitude of the cellular response, in the context of a regenerative process. Using a bioinformatics approach, the main biological function of these proteins were assigned, showing the regulation of proteins involved in processes like apoptosis, iron homeostasis and regulation of muscular structure...
Greene, Kathleen; Donovan, Sam
In the process of designing and field-testing bioinformatics curriculum materials, we have adopted a three-stage, progressive model that emphasizes collaborative scientific inquiry. The elements of the model include: (1) context setting, (2) introduction to concepts, processes, and tools, and (3) development of competent use of technologically…
Katayama, T.; Arakawa, K.; Nakao, M.; Prins, J.C.P.
Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However,
We used bioinformatics methods to study phylogenetic relations and differentiation patterns of the archaeal chaperonin 60 kDa heat-shock protein (HSP60) genes in support of the study of differential expression patterns of the three chaperonin genes encoded in Sulfolobus shibatae.
Attwood, Teresa K; Blackford, Sarah; Brazas, Michelle D; Davies, Angela; Schneider, Maria Victoria
Bioinformatics is now intrinsic to life science research, but the past decade has witnessed a continuing deficiency in this essential expertise. Basic data stewardship is still taught relatively rarely in life science education programmes, creating a chasm between theory and practice, and fuelling demand for bioinformatics training across all educational levels and career roles. Concerned by this, surveys have been conducted in recent years to monitor bioinformatics and computational training needs worldwide. This article briefly reviews the principal findings of a number of these studies. We see that there is still a strong appetite for short courses to improve expertise and confidence in data analysis and interpretation; strikingly, however, the most urgent appeal is for bioinformatics to be woven into the fabric of life science degree programmes. Satisfying the relentless training needs of current and future generations of life scientists will require a concerted response from stakeholders across the globe, who need to deliver sustainable solutions capable of both transforming education curricula and cultivating a new cadre of trainer scientists. © The Author 2017. Published by Oxford University Press.
Wilson, Justin; Dai, Manhong; Jakupovic, Elvis; Watson, Stanley; Meng, Fan
Modern video cards and game consoles typically have much better performance to price ratios than that of general purpose CPUs. The parallel processing capabilities of game hardware are well-suited for high throughput biomedical data analysis. Our initial results suggest that game hardware is a cost-effective platform for some computationally demanding bioinformatics problems.
Banasik, Karina; Justesen, Johanne M.; Hornbak, Malene
Objective: Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes. Research Design and Methods: By integrating public database text mining, trans-organism protein...
Hemerich, Daiane; van Setten, Jessica; Tragante, Vinicius; Asselbergs, Folkert W
High blood pressure or hypertension is an established risk factor for a myriad of cardiovascular diseases. Genome-wide association studies have successfully found over nine hundred loci that contribute to blood pressure. However, the mechanisms through which these loci contribute to disease are still relatively undetermined as less than 10% of hypertension-associated variants are located in coding regions. Phenotypic cell-type specificity analyses and expression quantitative trait loci show predominant vascular and cardiac tissue involvement for blood pressure-associated variants. Maps of chromosomal conformation and expression quantitative trait loci (eQTL) in critical tissues identified 2,424 genes interacting with blood pressure-associated loci, of which 517 are druggable. Integrating genome, regulome and transcriptome information in relevant cell-types could help to functionally annotate blood pressure associated loci and identify drug targets.
Liu, Yanhan; Ma, Tengfei; Liu, Jianzhu; Zhao, Xiaona; Cheng, Ziqiang; Guo, Huijun; Wang, Shujing; Xu, Ruixue
Poliomyelitis, a disease which can manifest as muscle paralysis, is caused by the poliovirus, which is a human enterovirus and member of the family Picornaviridae that usually transmits by the faecal-oral route. The viruses of the OPV (oral poliovirus attenuated-live vaccine) strains can mutate in the human intestine during replication and some of these mutations can lead to the recovery of serious neurovirulence. Informatics research of the poliovirus genome can be used to explain further the characteristics of this virus. In this study, sequences from 100 poliovirus isolates were acquired from GenBank. To determine the evolutionary relationship between the strains, we compared and analysed the sequences of the complete poliovirus genome and the VP1 region. The reconstructed phylogenetic trees for the complete sequences and the VP1 sequences were both divided into two branches, indicating that the genetic relationships of the whole poliovirus genome and the VP1 sequences are very similar. This branching indicates that the virulence and pathogenicity of poliomyelitis may be associated with the VP1 region. Sequence alignment of the VP1 region revealed numerous mutation sites in which mutation rates of >30 % were detected. In a group of strains recorded in the USA, mutation sites and mutation types were the same and this may be associated with their distribution in the evolutionary tree and their genetic relationship. In conclusion, the genetic evolutionary relationships of poliovirus isolate sequences are determined to a great extent by the VP1 protein, and poliovirus strains located on the same branch of the phylogenetic tree contain the same mutation spots and mutation types. Hence, the genetic characteristics of the VP1 region in the poliovirus genome should be analysed to identify the transmission route of poliovirus and provide the basis of viral immunity development. © 2014 The Authors.
Full Text Available Computational biology and bioinformatics have been part and parcel of biomedical research for few decades now. However, the institutionalization of bioinformatics research took place with the establishment of Distributed Information Centres (DISCs in the research institutions of repute in various disciplines by the Department of Biotechnology, Government of India. Though, at initial stages, this endeavor was mainly focused on providing infrastructure for using information technology and internet based communication and tools for carrying out computational biology and in-silico assisted research in varied arena of research starting from disease biology to agricultural crops, spices, veterinary science and many more, the natural outcome of establishment of such facilities resulted into new experiments with bioinformatics tools. Thus, Biotechnology Information Systems (BTIS grew into a solid movement and a large number of publications started coming out of these centres. In the end of last century, bioinformatics started developing like a full-fledged research subject. In the last decade, a need was felt to actually make a factual estimation of the result of this endeavor of DBT which had, by then, established about two hundred centres in almost all disciplines of biomedical research. In a bid to evaluate the efforts and outcome of these centres, BTIS Centre at CSIR-CDRI, Lucknow was entrusted with collecting and collating the publications of these centres. However, when the full data was compiled, the DBT task force felt that the study must include Non-BTIS centres also so as to expand the report to have a glimpse of bioinformatics publications from the country.
Hernández-de-Diego, Rafael; de Villiers, Etienne P; Klingström, Tomas; Gourlé, Hadrien; Conesa, Ana; Bongcam-Rudloff, Erik
Bioinformatics skills have become essential for many research areas; however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.
Full Text Available Over the past 30 years, genomic and bioinformatic analysis of human adenoviruses has been achieved using a variety of DNA sequencing methods; initially with the use of restriction enzymes and more currently with the use of the GS FLX pyrosequencing technology. Following the conception of DNA sequencing in the 1970s, analysis of adenoviruses has evolved from 100 base pair mRNA fragments to entire genomes. Comparative genomics of adenoviruses made its debut in 1984 when nucleotides and amino acids of coding sequences within the hexon genes of two human adenoviruses (HAdV, HAdV–C2 and HAdV–C5, were compared and analyzed. It was determined that there were three different zones (1-393, 394-1410, 1411-2910 within the hexon gene, of which HAdV–C2 and HAdV–C5 shared zones 1 and 3 with 95% and 89.5% nucleotide identity, respectively. In 1992, HAdV-C5 became the first adenovirus genome to be fully sequenced using the Sanger method. Over the next seven years, whole genome analysis and characterization was completed using bioinformatic tools such as blastn, tblastx, ClustalV and FASTA, in order to determine key proteins in species HAdV-A through HAdV-F. The bioinformatic revolution was initiated with the introduction of a novel species, HAdV-G, that was typed and named by the use of whole genome sequencing and phylogenetics as opposed to traditional serology. HAdV bioinformatics will continue to advance as the latest sequencing technology enables scientists to add to and expand the resource databases. As a result of these advancements, how novel HAdVs are typed has changed. Bioinformatic analysis has become the revolutionary tool that has significantly accelerated the in-depth study of HAdV microevolution through comparative genomics.
Full Text Available Abstract Background Computational methods for problem solving need to interleave information access and algorithm execution in a problem-specific workflow. The structures of these workflows are defined by a scaffold of syntactic, semantic and algebraic objects capable of representing them. Despite the proliferation of GUIs (Graphic User Interfaces in bioinformatics, only some of them provide workflow capabilities; surprisingly, no meta-analysis of workflow operators and components in bioinformatics has been reported. Results We present a set of syntactic components and algebraic operators capable of representing analytical workflows in bioinformatics. Iteration, recursion, the use of conditional statements, and management of suspend/resume tasks have traditionally been implemented on an ad hoc basis and hard-coded; by having these operators properly defined it is possible to use and parameterize them as generic re-usable components. To illustrate how these operations can be orchestrated, we present GPIPE, a prototype graphic pipeline generator for PISE that allows the definition of a pipeline, parameterization of its component methods, and storage of metadata in XML formats. This implementation goes beyond the macro capacities currently in PISE. As the entire analysis protocol is defined in XML, a complete bioinformatic experiment (linked sets of methods, parameters and results can be reproduced or shared among users. Availability: http://if-web1.imb.uq.edu.au/Pise/5.a/gpipe.html (interactive, ftp://ftp.pasteur.fr/pub/GenSoft/unix/misc/Pise/ (download. Conclusion From our meta-analysis we have identified syntactic structures and algebraic operators common to many workflows in bioinformatics. The workflow components and algebraic operators can be assimilated into re-usable software components. GPIPE, a prototype implementation of this framework, provides a GUI builder to facilitate the generation of workflows and integration of heterogeneous
Heo, Go Eun; Kang, Keun Young; Song, Min; Lee, Jeong-Hoon
Bioinformatics is an interdisciplinary field at the intersection of molecular biology and computing technology. To characterize the field as convergent domain, researchers have used bibliometrics, augmented with text-mining techniques for content analysis. In previous studies, Latent Dirichlet Allocation (LDA) was the most representative topic modeling technique for identifying topic structure of subject areas. However, as opposed to revealing the topic structure in relation to metadata such as authors, publication date, and journals, LDA only displays the simple topic structure. In this paper, we adopt the Tang et al.'s Author-Conference-Topic (ACT) model to study the field of bioinformatics from the perspective of keyphrases, authors, and journals. The ACT model is capable of incorporating the paper, author, and conference into the topic distribution simultaneously. To obtain more meaningful results, we use journals and keyphrases instead of conferences and bag-of-words.. For analysis, we use PubMed to collected forty-six bioinformatics journals from the MEDLINE database. We conducted time series topic analysis over four periods from 1996 to 2015 to further examine the interdisciplinary nature of bioinformatics. We analyze the ACT Model results in each period. Additionally, for further integrated analysis, we conduct a time series analysis among the top-ranked keyphrases, journals, and authors according to their frequency. We also examine the patterns in the top journals by simultaneously identifying the topical probability in each period, as well as the top authors and keyphrases. The results indicate that in recent years diversified topics have become more prevalent and convergent topics have become more clearly represented. The results of our analysis implies that overtime the field of bioinformatics becomes more interdisciplinary where there is a steady increase in peripheral fields such as conceptual, mathematical, and system biology. These results are
Shen, Yue; Liu, Mingzhe; Wang, Lili; Li, Zhuowei; Taylor, David C; Li, Zhixi; Zhang, Meng
Caleosins are a class of Ca(2+) binding proteins that appear to be ubiquitous in plants. Some of the main proteins embedded in the lipid monolayer of lipid droplets, caleosins, play critical roles in the degradation of storage lipids during germination and in lipid trafficking. Some of them have been shown to have histidine-dependent peroxygenase activity, which is believed to participate in stress responses in Arabidopsis. In the model plant Arabidopsis thaliana, caleosins have been examined extensively. However, little is known on a genome-wide scale about these proteins in other members of the Brassicaceae. In this study, 51 caleosins in Brassica plants and Arabidopsis lyrata were investigated and analyzed in silico. Among them, 31 caleosins, including 7 in A. lyrata, 11 in Brassica oleracea and 13 in Brassica napus, are herein identified for the first time. Segmental duplication was the main form of gene expansion. Alignment, motif and phylogenetic analyses showed that Brassica caleosins belong to either the H-family or the L-family with different motif structures and physicochemical properties. Our findings strongly suggest that L-caleosins are evolved from H-caleosins. Predicted phosphorylation sites were differentially conserved in H-caleosin and L-caleosins, respectively. 'RY-repeat' elements and phytohormone-related cis-elements were identified in different caleosins, which suggest diverse physiological functions. Gene structure analysis indicated that most caleosins (38 out of 44) contained six exons and five introns and their intron phases were highly conserved. Structurally integrated caleosins, such as BrCLO3-3 and BrCLO4-2, showed high expression levels and may have important roles. Some caleosins, such as BrCLO2 and BoCLO8-2, lost motifs of the calcium binding domain, proline knot, potential phosphorylation sites and haem-binding sites. Combined with their low expression, it is suggested that these caleosins may have lost function.
Rodriguez-del Valle Nuri
Full Text Available Abstract Background Sporothrix schenckii is a pathogenic, dimorphic fungus, the etiological agent of sporotrichosis, a subcutaneous lymphatic mycosis. Dimorphism in S. schenckii responds to second messengers such as cAMP and calcium, suggesting the possible involvement of a calcium/calmodulin kinase in its regulation. In this study we describe a novel calcium/calmodulin-dependent protein kinase gene in S. schenckii, sscmk1, and the effects of inhibitors of calmodulin and calcium/calmodulin kinases on the yeast to mycelium transition and the yeast cell cycle. Results Using the PCR homology approach a new member of the calcium/calmodulin kinase family, SSCMK1, was identified in this fungus. The cDNA sequence of sscmk1 revealed an open reading frame of 1,221 nucleotides encoding a 407 amino acid protein with a predicted molecular weight of 45.6 kDa. The genomic sequence of sscmk1 revealed the same ORF interrupted by five introns. Bioinformatic analyses of SSCMK1 showed that this protein had the distinctive features that characterize a calcium/calmodulin protein kinase: a serine/threonine protein kinase domain and a calmodulin-binding domain. When compared to homologues from seven species of filamentous fungi, SSCMK1 showed substantial similarities, except for a large and highly variable region that encompasses positions 330 – 380 of the multiple sequence alignment. Inhibition studies using calmodulin inhibitor W-7, and calcium/calmodulin kinase inhibitors, KN-62 and lavendustin C, were found to inhibit budding by cells induced to re-enter the yeast cell cycle and to favor the yeast to mycelium transition. Conclusion This study constitutes the first evidence of the presence of a calcium/calmodulin kinase-encoding gene in S. schenckii and its possible involvement as an effector of dimorphism in this fungus. These results suggest that a calcium/calmodulin dependent signaling pathway could be involved in the regulation of dimorphism in this fungus
Full Text Available Chao-Jin Chen,* De-Zhao Liu,* Wei-Feng Yao, Yu Gu, Fei Huang, Zi-Qing Hei, Xiang Li Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of China *These authors contributed equally to this work Purpose: Neuropathic pain is a complex chronic condition occurring post-nervous system damage. The transcriptional reprogramming of injured dorsal root ganglia (DRGs drives neuropathic pain. However, few comparative analyses using high-throughput platforms have investigated uninjured DRG in neuropathic pain, and potential interactions among differentially expressed genes (DEGs and pathways were not taken into consideration. The aim of this study was to identify changes in genes and pathways associated with neuropathic pain in uninjured L4 DRG after L5 spinal nerve ligation (SNL by using bioinformatic analysis.Materials and methods: The microarray profile GSE24982 was downloaded from the Gene Expression Omnibus database to identify DEGs between DRGs in SNL and sham rats. The prioritization for these DEGs was performed using the Toppgene database followed by gene ontology and pathway enrichment analyses. The relationships among DEGs from the protein interactive perspective were analyzed using protein–protein interaction (PPI network and module analysis. Real-time polymerase chain reaction (PCR and Western blotting were used to confirm the expression of DEGs in the rodent neuropathic pain model.Results: A total of 206 DEGs that might play a role in neuropathic pain were identified in L4 DRG, of which 75 were upregulated and 131 were downregulated. The upregulated DEGs were enriched in biological processes related to transcription regulation and molecular functions such as DNA binding, cell cycle, and the FoxO signaling pathway. Ctnnb1 protein had the highest connectivity degrees in the PPI network. The in vivo studies also validated that mRNA and protein levels of Ctnnb1 were
Mulder, Nicola J.; Adebiyi, Ezekiel; Alami, Raouf; Benkahla, Alia; Brandful, James; Doumbia, Seydou; Everett, Dean; Fadlelmola, Faisal M.; Gaboun, Fatima; Gaseitsiwe, Simani; Ghazal, Hassan; Hazelhurst, Scott; Hide, Winston; Ibrahimi, Azeddine; Jaufeerally Fakim, Yasmina; Jongeneel, C. Victor; Joubert, Fourie; Kassim, Samar; Kayondo, Jonathan; Kumuthini, Judit; Lyantagaye, Sylvester; Makani, Julie; Mansour Alzohairy, Ahmed; Masiga, Daniel; Moussa, Ahmed; Nash, Oyekanmi; Ouwe Missi Oukem-Boyer, Odile; Owusu-Dabo, Ellis; Panji, Sumir; Patterton, Hugh; Radouani, Fouzia; Sadki, Khalid; Seghrouchni, Fouad; Tastan Bishop, Özlem; Tiffin, Nicki; Ulenga, Nzovu
The application of genomics technologies to medicine and biomedical research is increasing in popularity, made possible by new high-throughput genotyping and sequencing technologies and improved data analysis capabilities. Some of the greatest genetic diversity among humans, animals, plants, and microbiota occurs in Africa, yet genomic research outputs from the continent are limited. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive the development of genomic research for human health in Africa, and through recognition of the critical role of bioinformatics in this process, spurred the establishment of H3ABioNet, a pan-African bioinformatics network for H3Africa. The limitations in bioinformatics capacity on the continent have been a major contributory factor to the lack of notable outputs in high-throughput biology research. Although pockets of high-quality bioinformatics teams have existed previously, the majority of research institutions lack experienced faculty who can train and supervise bioinformatics students. H3ABioNet aims to address this dire need, specifically in the area of human genetics and genomics, but knock-on effects are ensuring this extends to other areas of bioinformatics. Here, we describe the emergence of genomics research and the development of bioinformatics in Africa through H3ABioNet. PMID:26627985
Grafström, Roland C; Nymark, Penny; Hongisto, Vesa; Spjuth, Ola; Ceder, Rebecca; Willighagen, Egon; Hardy, Barry; Kaski, Samuel; Kohonen, Pekka
This paper outlines the work for which Roland Grafström and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafström laboratory have, for many years, covered cancer biology studies, as well as the development and application of toxicity-predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art cancer biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in toxicity testing with alternative methods, such as bioinformatics-driven analyses of data obtained from human cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose toxicity testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of toxicity pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to human health and environmental safety. 2015 FRAME.
EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.
Luscombe, Nicholas; Fdez-Riverola, Florentino; Rodríguez, Juan; Practical Applications of Computational Biology & Bioinformatics
The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable.. The analysis of the datasets of Next Generation Sequencing needs new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Also Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. This book presents the results of the 6th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, 28-30th March, 2012 which brought together interdisciplinary scientists that have a strong background in the biological and computational sciences.
Wang, Pengfei; Wang, Yingfang; Duan, Guangcai; Xue, Zerun; Wang, Linlin; Guo, Xiangjiao; Yang, Haiyan; Xi, Yuanlin
This study was aimed to explore the features of clustered regularly interspaced short palindromic repeats (CRISPR) structures in Shigella by using bioinformatics. We used bioinformatics methods, including BLAST, alignment and RNA structure prediction, to analyze the CRISPR structures of Shigella genomes. The results showed that the CRISPRs existed in the four groups of Shigella, and the flanking sequences of upstream CRISPRs could be classified into the same group with those of the downstream. We also found some relatively conserved palindromic motifs in the leader sequences. Repeat sequences had the same group with corresponding flanking sequences, and could be classified into two different types by their RNA secondary structures, which contain "stem" and "ring". Some spacers were found to homologize with part sequences of plasmids or phages. The study indicated that there were correlations between repeat sequences and flanking sequences, and the repeats might act as a kind of recognition mechanism to mediate the interaction between foreign genetic elements and Cas proteins.
Full Text Available Performing Bioinformatic´s experiments involve an intensive access to distributed services and information resources through Internet. Although existing tools facilitate the implementation of workflow-oriented applications, they lack of capabilities to integrate services beyond low-scale applications, particularly integrating services with heterogeneous interaction patterns and in a larger scale. This is particularly required to enable a large-scale distributed processing of biological data generated by massive sequencing technologies. On the other hand, such integration mechanisms are provided by middleware products like Enterprise Service Buses (ESB, which enable to integrate distributed systems following a Service Oriented Architecture. This paper proposes an integration platform, based on enterprise middleware, to integrate Bioinformatics services. It presents a multi-level reference architecture and focuses on ESB-based mechanisms to provide asynchronous communications, event-based interactions and data transformation capabilities. The paper presents a formal specification of the platform using the Event-B model.
Bhunia, Gouri Sankar; Dikhit, Manas Ranjan; Kesari, Shreekant; Sahoo, Ganesh Chandra; Das, Pradeep
Visceral leishmaniasis or kala-azar is a potent parasitic infection causing death of thousands of people each year. Medicinal compounds currently available for the treatment of kala-azar have serious side effects and decreased efficacy owing to the emergence of resistant strains. The type of immune reaction is also to be considered in patients infected with Leishmania donovani (L. donovani). For complete eradication of this disease, a high level modern research is currently being applied both at the molecular level as well as at the field level. The computational approaches like remote sensing, geographical information system (GIS) and bioinformatics are the key resources for the detection and distribution of vectors, patterns, ecological and environmental factors and genomic and proteomic analysis. Novel approaches like GIS and bioinformatics have been more appropriately utilized in determining the cause of visearal leishmaniasis and in designing strategies for preventing the disease from spreading from one region to another.
Full Text Available Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.
Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T; van Oven, Mannis; Wallace, Douglas C; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J; Gai, Xiaowu
MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources. © 2016 WILEY PERIODICALS, INC.
Alexandre A. Lussier
Full Text Available We previously identified gene expression changes in the prefrontal cortex and hippocampus of rats prenatally exposed to alcohol under both steady-state and challenge conditions (Lussier et al., 2015, Alcohol.: Clin. Exp. Res., 39, 251–261. In this study, adult female rats from three prenatal treatment groups (ad libitum-fed control, pair-fed, and ethanol-fed were injected with physiological saline solution or complete Freund׳s adjuvant (CFA to induce arthritis (adjuvant-induced arthritis, AA. The prefrontal cortex and hippocampus were collected 16 days (peak of arthritis or 39 days (during recovery following injection, and whole genome gene expression was assayed using Illumina׳s RatRef-12 expression microarray. Here, we provide additional metadata, detailed explanations of data pre-processing steps and quality control, as well as a basic framework for the bioinformatic analyses performed. The datasets from this study are publicly available on the GEO repository (accession number GSE63561.
Filiz, Ertugrul; Vatansever, Recep; Ozyigit, Ibrahim Ilker
Urease (EC 184.108.40.206) is a nickel-dependent metalloenzyme catalyzing the hydrolysis of urea into ammonia and carbon dioxide. It is present in many bacteria, fungi, yeasts and plants. Most species, with few exceptions, use nickel metalloenzyme urease to hydrolyze urea, which is one of the commonly used nitrogen fertilizer in plant growth thus its enzymatic hydrolysis possesses vital importance in agricultural practices. Considering the essentiality and importance of urea and urease activity in most plants, this study aimed to comparatively investigate the ureases of two important legume species such as Glycine max (soybean) and Medicago truncatula (barrel medic) from Fabaceae family. With additional plant species, primary and secondary structures of 37 plant ureases were comparatively analyzed using various bioinformatics tools. A structure based phylogeny was constructed using predicted 3D models of G. max and M. truncatula, whose crystallographic structures are not available, along with three additional solved urease structures from Canavalia ensiformis (PDB: 4GY7), Bacillus pasteurii (PDB: 4UBP) and Klebsiella aerogenes (PDB: 1FWJ). In addition, urease structures of these species were docked with urea to analyze the binding affinities, interacting amino acids and atom distances in urease-urea complexes. Furthermore, mutable amino acids which could potentially affect the protein active site, stability and flexibility as well as overall protein stability were analyzed in urease structures of G. max and M. truncatula. Plant ureases demonstrated similar physico-chemical properties with 833-878 amino acid residues and 89.39-90.91 kDa molecular weight with mainly acidic (5.15-6.10 pI) nature. Four protein domain structures such as urease gamma, urease beta, urease alpha and amidohydro 1 characterized the plant ureases. Secondary structure of plant ureases also demonstrated conserved protein architecture, with predominantly α-helix and random coil structures. In
Chang, Victor; Walters, Robert John; Wills, Gary
This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) ...
Tsai, Pei-Lun; Chen, Sung-Fang
The purpose of this review is to provide updated information regarding bioinformatic software for the use in the characterization of glycosylated structures since 2013. A comprehensive review by Woodin et al. Analyst 138: 2793?2803, 2013 (ref. 1) described two main approaches that are introduced for starting researchers in this area; analysis of released glycans and the identification of glycopeptide in enzymatic digests, respectively. Complementary to that report, this review focuses on m...
Kanterakis, Alexandros; Kuiper, Joël; Potamias, George; Swertz, Morris A
Today researchers can choose from many bioinformatics protocols for all types of life sciences research, computational environments and coding languages. Although the majority of these are open source, few of them possess all virtues to maximize reuse and promote reproducible science. Wikipedia has proven a great tool to disseminate information and enhance collaboration between users with varying expertise and background to author qualitative content via crowdsourcing. However, it remains an open question whether the wiki paradigm can be applied to bioinformatics protocols. We piloted PyPedia, a wiki where each article is both implementation and documentation of a bioinformatics computational protocol in the python language. Hyperlinks within the wiki can be used to compose complex workflows and induce reuse. A RESTful API enables code execution outside the wiki. Initial content of PyPedia contains articles for population statistics, bioinformatics format conversions and genotype imputation. Use of the easy to learn wiki syntax effectively lowers the barriers to bring expert programmers and less computer savvy researchers on the same page. PyPedia demonstrates how wiki can provide a collaborative development, sharing and even execution environment for biologists and bioinformaticians that complement existing resources, useful for local and multi-center research teams. PyPedia is available online at: http://www.pypedia.com. The source code and installation instructions are available at: https://github.com/kantale/PyPedia_server. The PyPedia python library is available at: https://github.com/kantale/pypedia. PyPedia is open-source, available under the BSD 2-Clause License.
Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T
SUMMARY: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments......, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. AVAILABILITY: Biopython is freely available, with documentation and source code at (www...
Marci D. Brandenburg, MS, MSI
Conclusions: This collaboration furthered the U-M bioinformationist’s role in the field as an expert in Cytoscape instruction, while also establishing the CWML as a leader in providing support for analyzing and visualizing molecular data at Yale University. The authors found this collaboration to be a successful way for librarians to fill end-user training gaps in rapidly changing fields such as bioinformatics.
Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong
Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open
Full Text Available Abstract Background To a greater or lesser extent, eukaryotic nuclear genomes contain fragments of their mitochondrial genome counterpart, deriving from the random insertion of damaged mtDNA fragments. NumtS (Nuclear mt Sequences are not equally abundant in all species, and are redundant and polymorphic in terms of copy number. In population and clinical genetics, it is important to have a complete overview of NumtS quantity and location. Searching PubMed for NumtS or Mitochondrial pseudo-genes yields hundreds of papers reporting Human NumtS compilations produced by in silico or wet-lab approaches. A comparison of published compilations clearly shows significant discrepancies among data, due both to unwise application of Bioinformatics methods and to a not yet correctly assembled nuclear genome. To optimize quantification and location of NumtS, we produced a consensus compilation of Human NumtS by applying various bioinformatics approaches. Results Location and quantification of NumtS may be achieved by applying database similarity searching methods: we have applied various methods such as Blastn, MegaBlast and BLAT, changing both parameters and database; the results were compared, further analysed and checked against the already published compilations, thus producing the Reference Human Numt Sequences (RHNumtS compilation. The resulting NumtS total 190. Conclusion The RHNumtS compilation represents a highly reliable reference basis, which may allow designing a lab protocol to test the actual existence of each NumtS. Here we report preliminary results based on PCR amplification and sequencing on 41 NumtS selected from RHNumtS among those with lower score. In parallel, we are currently designing the RHNumtS database structure for implementation in the HmtDB resource. In the future, the same database will host NumtS compilations from other organisms, but these will be generated only when the nuclear genome of a specific organism has reached a high
Ison, Jon; Kalaš, Matúš; Jonassen, Inge; Bolser, Dan; Uludag, Mahmut; McWilliam, Hamish; Malone, James; Lopez, Rodrigo; Pettifer, Steve; Rice, Peter
Motivation: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required. Results: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations. Availability: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl. Contact: email@example.com PMID:23479348
Izak, Dariusz; Klim, Joanna; Kaczanowski, Szymon
Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.
Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H
Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.
Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.
Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832
Joanna R. Klein
Full Text Available Bioinformatics, the use of computer resources to understand biological information, is an important tool in research, and can be easily integrated into the curriculum of undergraduate courses. Such an example is provided in this series of four activities that introduces students to the field of bioinformatics as they design PCR based tests for pathogenic E. coli strains. A variety of computer tools are used including BLAST searches at NCBI, bacterial genome searches at the Integrated Microbial Genomes (IMG database, protein analysis at Pfam and literature research at PubMed. In the process, students also learn about virulence factors, enzyme function and horizontal gene transfer. Some or all of the four activities can be incorporated into microbiology or general biology courses taken by students at a variety of levels, ranging from high school through college. The activities build on one another as they teach and reinforce knowledge and skills, promote critical thinking, and provide for student collaboration and presentation. The computer-based activities can be done either in class or outside of class, thus are appropriate for inclusion in online or blended learning formats. Assessment data showed that students learned general microbiology concepts related to pathogenesis and enzyme function, gained skills in using tools of bioinformatics and molecular biology, and successfully developed and tested a scientific hypothesis.
Santos, Eliane Macedo Sobrinho; Santos, Hércules Otacílio; Dos Santos Dias, Ivoneth; Santos, Sérgio Henrique; Batista de Paula, Alfredo Maurício; Feltenberger, John David; Sena Guimarães, André Luiz; Farias, Lucyana Conceição
Pathogenesis of odontogenic tumors is not well known. It is important to identify genetic deregulations and molecular alterations. This study aimed to investigate, through bioinformatic analysis, the possible genes involved in the pathogenesis of ameloblastoma (AM) and keratocystic odontogenic tumor (KCOT). Genes involved in the pathogenesis of AM and KCOT were identified in GeneCards. Gene list was expanded, and the gene interactions network was mapped using the STRING software. "Weighted number of links" (WNL) was calculated to identify "leader genes" (highest WNL). Genes were ranked by K-means method and Kruskal-Wallis test was used (Preview data was used to corroborate the bioinformatics data. CDK1 was identified as leader gene for AM. In KCOT group, results show PCNA and TP53 . Both tumors exhibit a power law behavior. Our topological analysis suggested leader genes possibly important in the pathogenesis of AM and KCOT, by clustering coefficient calculated for both odontogenic tumors (0.028 for AM, zero for KCOT). The results obtained in the scatter diagram suggest an important relationship of these genes with the molecular processes involved in AM and KCOT. Ontological analysis for both AM and KCOT demonstrated different mechanisms. Bioinformatics analyzes were confirmed through literature review. These results may suggest the involvement of promising genes for a better understanding of the pathogenesis of AM and KCOT.
Suh, K. Stephen; Sarojini, Sreeja; Youssif, Maher; Nalley, Kip; Milinovikj, Natasha; Elloumi, Fathi; Russell, Steven; Pecora, Andrew; Schecter, Elyssa; Goy, Andre
Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs by focusing on genetics and “-omics” data obtained from patient biospecimens and records to guide therapy choices that generate good clinical outcomes. The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations of tissue banking, bioinformatics, and electronic medical records (EMRs). The analytical power of bioinformatic platforms combined with patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient biospecimens stored in tissue banks. For cancer, high-quality biospecimens collected at diagnosis, first relapse, and various treatment stages provide crucial resources for study designs. To enlarge biospecimen collections, patient education regarding the value of specimen donation is vital. One approach for increasing consent is to offer publically available illustrations and game-like engagements demonstrating how wider sample availability facilitates development of novel therapies. The critical value of tissue bank samples, bioinformatics, and EMR in the early stages of the biomarker discovery process for personalized medicine is often overlooked. The data obtained also require cross-disciplinary collaborations to translate experimental results into clinical practice and diagnostic and prognostic use in personalized medicine. PMID:23818899
Full Text Available Abstract Background Gene expression measurements from breast cancer (BrCa tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays. Results We gathered expression data from 9 published microarray studies examining estrogen receptor positive (ER+ and estrogen receptor negative (ER- BrCa tumor cases from the Oncomine database. We performed a meta-analysis and identified genes that were universally up or down regulated with respect to ER+ versus ER- tumor status. We surveyed both the proximal promoter and 3' untranslated regions (3'UTR of our top-ranking genes in each expression group to test whether common sequence elements may contribute to the observed expression patterns. Utilizing a combination of known transcription factor binding sites (TFBS, evolutionarily conserved mammalian promoter and 3'UTR motifs, and microRNA (miRNA seed sequences, we identified numerous motifs that were disproportionately represented between the two gene classes suggesting a common regulatory network for the observed gene expression patterns. Conclusion Some of the genes we identified distinguish key transcripts previously seen in array studies, while others are newly defined. Many of the genes identified as overexpressed in ER- tumors were previously identified as expression markers for neoplastic transformation in multiple human cancers. Moreover, our motif analysis identified a collection of specific cis-acting target sites which may collectively play a role in the differential gene expression patterns observed in ER+ versus ER- breast cancer tumors. Importantly, the gene sets and associated DNA motifs provide a starting point with which to explore the mechanistic basis for the observed expression patterns in breast tumors.
L. Shen (Lishuang); M.A. Diroma (Maria Angela); M. Gonzalez (Michael); D. Navarro-Gomez (Daniel); J. Leipzig (Jeremy); M.T. Lott (Marie T.); M. van Oven (Mannis); D.C. Wallace; C.C. Muraresku (Colleen Clarke); Z. Zolkipli-Cunningham (Zarazuela); P.F. Chinnery (Patrick); M. Attimonelli (Marcella); S. Zuchner (Stephan); M.J. Falk (Marni J.); X. Gai (Xiaowu)
textabstractMSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes,
Kouskoumvekaki, Irene; Shublaq, Nour; Brunak, Søren
As both the amount of generated biological data and the processing compute power increase, computational experimentation is no longer the exclusivity of bioinformaticians, but it is moving across all biomedical domains. For bioinformatics to realize its translational potential, domain experts need...... access to user-friendly solutions to navigate, integrate and extract information out of biological databases, as well as to combine tools and data resources in bioinformatics workflows. In this review, we present services that assist biomedical scientists in incorporating bioinformatics tools...... into their research.We review recent applications of Cytoscape, BioGPS and DAVID for data visualization, integration and functional enrichment. Moreover, we illustrate the use of Taverna, Kepler, GenePattern, and Galaxy as open-access workbenches for bioinformatics workflows. Finally, we mention services...
Oluwagbemi, Olugbenga O; Adewumi, Adewole; Esuruoso, Abimbola
Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context. MACBenAbim is available from the authors for non-commercial purposes.
Martin, G.; Baurens, F.C.; Droc, G.; Rouard, M.; Cenci, A.; Kilian, A.; Hastie, A.; Doležel, Jaroslav; Aury, J. M.; Alberti, A.; Carreel, F.; D'Hont, A.
Roč. 17, MAR 16 (2016), s. 243 ISSN 1471-2164 Institutional support: RVO:61389030 Keywords : Musa acuminata * Genome assembly * Bioinformatics tool Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.729, year: 2016
Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang
We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365
El-Kalioby, Mohamed; Abouelhoda, Mohamed; Krüger, Jan; Giegerich, Robert; Sczyrba, Alexander; Wall, Dennis P; Tonellato, Peter
Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org.
Full Text Available Linux container technologies, as represented by Docker, provide an alternative to complex and time-consuming installation processes needed for scientiﬁc software. The ease of deployment and the process isolation they enable, as well as the reproducibility they permit across environments and versions, are among the qualities that make them interesting candidates for the construction of bioinformatic infrastructures, at any scale from single workstations to high throughput computing architectures. The Docker Hub is a public registry which can be used to distribute bioinformatic software as Docker images. However, its lack of curation and its genericity make it difﬁcult for a bioinformatics user to ﬁnd the most appropriate images needed. BioShaDock is a bioinformatics-focused Docker registry, which provides a local and fully controlled environment to build and publish bioinformatic software as portable Docker images. It provides a number of improvements over the base Docker registry on authentication and permissions management, that enable its integration in existing bioinformatic infrastructures such as computing platforms. The metadata associated with the registered images are domain-centric, including for instance concepts deﬁned in the EDAM ontology, a shared and structured vocabulary of commonly used terms in bioinformatics. The registry also includes user deﬁned tags to facilitate its discovery, as well as a link to the tool description in the ELIXIR registry if it already exists. If it does not, the BioShaDock registry will synchronize with the registry to create a new description in the Elixir registry, based on the BioShaDock entry metadata. This link will help users get more information on the tool such as its EDAM operations, input and output types. This allows integration with the ELIXIR Tools and Data Services Registry, thus providing the appropriate visibility of such images to the bioinformatics community.
Deshmukh, Atul S; Cox, Juergen; Jensen, Lars Juhl
, in principle, allows an unbiased and comprehensive analysis of cellular secretomes; however, the distinction of bona fide secreted proteins from proteins released upon lysis of a small fraction of dying cells remains challenging. Here we applied highly sensitive MS and streamlined bioinformatics to analyze......-resistant conditions. Our study demonstrates an efficient combined experimental and bioinformatics workflow to identify putative secreted proteins from insulin-resistant skeletal muscle cells, which could easily be adapted to other cellular models....
Full Text Available The frequency of cardiovascular disorders is increasing in HIV-infected individuals despite a significant reduction in the viral load by antiretroviral therapies (ART. Since the CD4+ T-cells are responsible for the viral load as well as immunological responses, we hypothesized that chronic HIV-infection of T-cells produces novel proteins/enzymes that cause cardiac dysfunctions. To identify specific factors that might cause cardiac disorders without the influence of numerous cofactors produced by other pathogenic microorganisms that co-inhabit most HIV-infected individuals, we analyzed genome-wide proteomes of a CD4+ T-cell line at different stages of HIV replication and cell growth over >6 months. Subtractive analyses of several hundred differentially regulated proteins from HIV-infected and uninfected counterpart cells and comparisons with proteins expressed from the same cells after treating with the antiviral drug Zidovudine/AZT and inhibiting virus replication, identified a well-coordinated network of 12 soluble/diffusible proteins in HIV-infected cells. Functional categorization, bioinformatics and statistical analyses of each protein predicted that the expression of cardiac-specific Ca2+ kinase together with multiple Ca2+ release channels causes a sustained overload of Ca2+ in the heart which induces fetal/cardiac myosin heavy chains (MYH6 and MYH7 and a myosin light-chain kinase. Each of these proteins has been shown to cause cardiac stress, arrhythmia, hypertrophic signaling, cardiomyopathy and heart failure (p = 8 × 10−11. Translational studies using the newly discovered proteins produced by HIV infection alone would provide additional biomarkers that could be added to the conventional markers for an early diagnosis and/or development of specific therapeutic interventions for heart diseases in HIV-infected individuals.
Full Text Available Background & Objective: Single nucleotide polymorphisms are the cause of genetic variation to living organisms. Single nucleotide polymorphisms alter residues in the protein sequence. In this investigation, the relationship between prion protein gene polymorphisms and its relevance to pathogenicity was studied. Material & Method: Amino acid sequence of the main isoform from the human prion protein gene (PRNP was extracted from UniProt database and evaluated by FoldAmyloid and AmylPred servers. All non-synonymous single nucleotide polymorphisms (nsSNPs from SNP database (dbSNP were further analyzed by bioinformatics servers including SIFT, PolyPhen-2, I-Mutant-3.0, PANTHER, SNPs & GO, PHD-SNP, Meta-SNP, and MutPred to determine the most damaging nsSNPs. Results: The results of the first structure analyses by FoldAmyloid and AmylPerd servers implied that regions including 5-15, 174-178, 180-184, 211-217, and 240-252 were the most sensitive parts of the protein sequence to amyloidosis. Screening all nsSNPs of the main protein isoform using bioinformatic servers revealed that substitution of Aspartic acid with Valine at position 178 (ID code: rs11538766 was the most deleterious nsSNP in the protein structure. Conclusion: Substitution of the Aspartic acid with Valine at position 178 (D178V was the most pathogenic mutation in the human prion protein gene. Analyses from the MutPred server also showed that beta-sheets’ increment in the secondary structure was the main reason behind the molecular mechanism of the prion protein aggregation.
Full Text Available Background and objective It has been proven that ornithine aminotransferase (OAT might play an important role in the oncogenesis and progression of numerous malignant tumors. The aim of this study is to detect the mRNA and protein expression of OAT in non-small cell lung cancer (NSCLC, as well as to analyze the bioinformatic features and binary interactions. Methods OAT mRNA expression was detected in A549 and 16HBE cell lines by reverse transcription-polymerase chain reaction. OAT protein expression was determined in 55 cases of NSCLC and 17 cases of adjacent non-tumor lung tissues by immunohistochemical staining. The bioinformatic features and binary interactions of OAT were analyzed. Gene ontology annotation and signal pathway analysis were performed. Results OAT mRNA expression in A549 cells was 2.85-fold lower than that in 16HBE cells. OAT protein expression was significantly higher in NSCLC tissues than that in adjacent non-tumor lung tissues. A significant difference of OAT protein expression was existed between squamous cell lung cancer and adenocarcinoma (P<0.05, but was not correlated with the gender, age, lymph node metastasis, tumor size, and TNM stages. Bioinformatic analysis suggested that OAT was a highly homologous and stable protein located in the mitochondria. An aminotran-3 domain and several sites of phosphorylation, which may function in signal transduction, gene transcription, and molecular transit, were found. In the 54 selected binary interactions of OAT, TNF and TRAF6 play roles in the NF-κB pathway. Conclusion OAT may play an important role in the oncogenesis and progression of NSCLC. Thus, OAT may be a novel biomarker for the diagnosis of NSCLC or a new target for its treatment.
Pierre H H Schneeberger
Full Text Available Viruses belonging to the Flaviviridae and Bunyaviridae families show considerable genetic diversity. However, this diversity is not necessarily taken into account when developing diagnostic assays, which are often based on the pairwise alignment of a limited number of sequences. Our objective was to develop and evaluate a bioinformatics workflow addressing two recurrent issues of molecular assay design: (i the high intraspecies genetic diversity in viruses and (ii the potential for cross-reactivity with close relatives.The workflow developed herein was based on two consecutive BLASTn steps; the first was utilized to select highly conserved regions among the viral taxon of interest, and the second was employed to assess the degree of similarity of these highly-conserved regions to close relatives. Subsequently, the workflow was tested on a set of eight viral species, including various strains from the Flaviviridae and Bunyaviridae families.The genetic diversity ranges from as low as 0.45% variable sites over the complete genome of the Japanese encephalitis virus to more than 16% of variable sites on segment L of the Crimean-Congo hemorrhagic fever virus. Our proposed bioinformatics workflow allowed the selection-based on computing scores-of the best target for a diagnostic molecular assay for the eight viral species investigated.Our bioinformatics workflow allowed rapid selection of highly conserved and specific genomic fragments among the investigated viruses, while considering up to several hundred complete genomic sequences. The pertinence of this workflow will increase in parallel to the number of sequences made publicly available. We hypothesize that our workflow might be utilized to select diagnostic molecular markers for higher organisms with more complex genomes, provided the sequences are made available.
Roche-Lima, Abiel; Thulasiram, Ruppa K
Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.
Kalaš, Matúš; Puntervoll, Pæl; Joseph, Alexandre; Bartaševičiūtė, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge
Motivation: The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. Results: BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. Availability: The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community. Contact: firstname.lastname@example.org; email@example.com; firstname.lastname@example.org PMID:20823319
Bhuvaneshwar, Krithika; Belouali, Anas; Singh, Varun; Johnson, Robert M; Song, Lei; Alaoui, Adil; Harris, Michael A; Clarke, Robert; Weiner, Louis M; Gusev, Yuriy; Madhavan, Subha
G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available
Kalas, Matús; Puntervoll, Pål; Joseph, Alexandre; Bartaseviciūte, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge
The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community.
Indonesia has a huge amount of biodiversity, which may contain many biomaterials for pharmaceutical application. These resources potency should be explored to discover new drugs for human wealth. However, the bioactive screening using conventional methods is very expensive and time-consuming. Therefore, we developed a methodology for screening the potential of natural resources based on bioinformatics. The method is developed based on the fact that organisms in the same taxon will have similar genes, metabolism and secondary metabolites product. Then we employ bioinformatics to explore the potency of biomaterial from Indonesia biodiversity by comparing species with the well-known taxon containing the active compound through published paper or chemical database. Then we analyze drug-likeness, bioactivity and the target proteins of the active compound based on their molecular structure. The target protein was examined their interaction with other proteins in the cell to determine action mechanism of the active compounds in the cellular level, as well as to predict its side effects and toxicity. By using this method, we succeeded to screen anti-cancer, immunomodulators and anti-inflammation from Indonesia biodiversity. For example, we found anticancer from marine invertebrate by employing the method. The anti-cancer was explore based on the isolated compounds of marine invertebrate from published article and database, and then identified the protein target, followed by molecular pathway analysis. The data suggested that the active compound of the invertebrate able to kill cancer cell. Further, we collect and extract the active compound from the invertebrate, and then examined the activity on cancer cell (MCF7). The MTT result showed that the methanol extract of marine invertebrate was highly potent in killing MCF7 cells. Therefore, we concluded that bioinformatics is cheap and robust way to explore bioactive from Indonesia biodiversity for source of drug and another