Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah
This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate…
Biochemical information has been crucial for the development of evolutionary biology. On the one hand, the sequence information now appearing is producing a huge increase in the amount of data available for phylogenetic analysis; on the other hand, and perhaps more fundamentally, it allows understanding of the ...
This paper draws on the philosophy of Karl Popper to present a descriptive evolutionary epistemology that offers philosophical solutions to the following related problems: "What happens when learning takes place?" and "What happens in human learning?" It provides a detailed analysis of how learning takes place without any direct transfer of…
Ma, Zhanshan (Sam)
In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal -. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three
These discussions included, among others, the possible consequences of nonDNA-based inheritance—epigenetics and cultural evolution, niche construction, and developmental mechanisms on our understanding of the evolutionary process, speciation, complexity in biology, and constructing a formal evolutionary theory.
We are delighted to bring to the readers, a set of peer-reviewed papers on evolutionary biology, published as a special issue of the Journal of Genetics. These papers emanated from ruminations upon and discussions at the Foundations of. Evolutionary Theory: the Ongoing Synthesis meeting at Coorg, India, in February ...
Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah
This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate students in response to two different evolution instruments (the EGALT-F and EGALT-P) that contained prompts that differed in various surface features (such as species and traits). We tested human-SIDE scoring correspondence under a series of different training and testing conditions, using Kappa inter-rater agreement values of greater than 0.80 as a performance benchmark. In addition, we examined the effects of response length on scoring success; that is, whether SIDE scoring models functioned with comparable success on short and long responses. We found that SIDE performance was most effective when scoring models were built and tested at the individual item level and that performance degraded when suites of items or entire instruments were used to build and test scoring models. Overall, SIDE was found to be a powerful and cost-effective tool for assessing student knowledge and performance in a complex science domain.
Hindi and English. Port 1. Resonance, Vo1.7 ... they use. Of course, many evolutionary biologists do work with fossils or DNA, or both, but there are also large numbers of ... The first major division that I like to make is between studies focussed ...
Home; Journals; Resonance – Journal of Science Education; Volume 10; Issue 7. Polemics and Synthesis: Ernst Mayr and Evolutionary Biology. Renee M Borges. General Article Volume 10 Issue 7 July 2005 pp 21-33. Fulltext. Click here to view fulltext PDF. Permanent link:
Home; Journals; Resonance – Journal of Science Education; Volume 5; Issue 10. Evolutionary Biology Research in India. Information and Announcements Volume 5 Issue 10 October 2000 pp 102-104. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/005/10/0102-0104 ...
Nesse, Randolph M.; Bergstrom, Carl T.; Ellison, Peter T.; Flier, Jeffrey S.; Gluckman, Peter; Govindaraju, Diddahally R.; Niethammer, Dietrich; Omenn, Gilbert S.; Perlman, Robert L.; Schwartz, Mark D.; Thomas, Mark G.; Stearns, Stephen C.; Valle, David
New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease. PMID:19918069
Torday, J S
Nowhere are the shortcomings of conventional descriptive biology more evident than in the literature on Quantum Biology. In the on-going effort to apply Quantum Mechanics to evolutionary biology, merging Quantum Mechanics with the fundamentals of evolution as the First Principles of Physiology-namely negentropy, chemiosmosis and homeostasis-offers an authentic opportunity to understand how and why physics constitutes the basic principles of biology. Negentropy and chemiosmosis confer determinism on the unicell, whereas homeostasis constitutes Free Will because it offers a probabilistic range of physiologic set points. Similarly, on this basis several principles of Quantum Mechanics also apply directly to biology. The Pauli Exclusion Principle is both deterministic and probabilistic, whereas non-localization and the Heisenberg Uncertainty Principle are both probabilistic, providing the long-sought after ontologic and causal continuum from physics to biology and evolution as the holistic integration recognized as consciousness for the first time. Copyright © 2018 Elsevier Ltd. All rights reserved.
Aktipis, C Athena; Nesse, Randolph M
New applications of evolutionary biology are transforming our understanding of cancer. The articles in this special issue provide many specific examples, such as microorganisms inducing cancers, the significance of within-tumor heterogeneity, and the possibility that lower dose chemotherapy may sometimes promote longer survival. Underlying these specific advances is a large-scale transformation, as cancer research incorporates evolutionary methods into its toolkit, and asks new evolutionary questions about why we are vulnerable to cancer. Evolution explains why cancer exists at all, how neoplasms grow, why cancer is remarkably rare, and why it occurs despite powerful cancer suppression mechanisms. Cancer exists because of somatic selection; mutations in somatic cells result in some dividing faster than others, in some cases generating neoplasms. Neoplasms grow, or do not, in complex cellular ecosystems. Cancer is relatively rare because of natural selection; our genomes were derived disproportionally from individuals with effective mechanisms for suppressing cancer. Cancer occurs nonetheless for the same six evolutionary reasons that explain why we remain vulnerable to other diseases. These four principles-cancers evolve by somatic selection, neoplasms grow in complex ecosystems, natural selection has shaped powerful cancer defenses, and the limitations of those defenses have evolutionary explanations-provide a foundation for understanding, preventing, and treating cancer.
Whiteson, S.; Wiering, M.; van Otterlo, M.
Algorithms for evolutionary computation, which simulate the process of natural selection to solve optimization problems, are an effective tool for discovering high-performing reinforcement-learning policies. Because they can automatically find good representations, handle continuous action spaces,
Laland, Kevin N; Odling-Smee, John; Feldman, Marcus W; Kendal, Jeremy
In spite of its success, Neo-Darwinism is faced with major conceptual barriers to further progress, deriving directly from its metaphysical foundations. Most importantly, neo-Darwinism fails to recognize a fundamental cause of evolutionary change, "niche construction". This failure restricts the generality of evolutionary theory, and introduces inaccuracies. It also hinders the integration of evolutionary biology with neighbouring disciplines, including ecosystem ecology, developmental biology, and the human sciences. Ecology is forced to become a divided discipline, developmental biology is stubbornly difficult to reconcile with evolutionary theory, and the majority of biologists and social scientists are still unhappy with evolutionary accounts of human behaviour. The incorporation of niche construction as both a cause and a product of evolution removes these disciplinary boundaries while greatly generalizing the explanatory power of evolutionary theory.
Lynch, Michael; Field, Mark C; Goodson, Holly V; Malik, Harmit S; Pereira-Leal, José B; Roos, David S; Turkewitz, Aaron P; Sazer, Shelley
All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.
Brown, C. R.
Full Text Available The demographic processes that drive the spread of populations through environments and in turn determine the abundance of organisms are the same demographic processes that drive the spread of genes through populations and in turn determine gene frequencies and fitness. Conceptually, marked similarities exist in the dynamic processes underlying population ecology and those underlying evolutionary biology. Central to an understanding of both disciplines is life history and its component demographic rates, such as survival, fecundity, and age of first breeding, and biologists from both fields have a vested interest in good analytical machinery for the estimation and analysis of these demographic rates. In the EURING conferences, we have been striving since the mid 1980s to promote a quantitative understanding of demographic rates through interdisciplinary collaboration between ecologists and statisticians. From the ecological side, the principal impetus has come from population biology, and in particular from wildlife biology, but the importance of good quantitative insights into demographic processes has long been recognized by a number of evolutionary biologists (e.g., Nichols & Kendall, 1995; Clobert, 1995; Cooch et al., 2002. In organizing this session, we have aimed to create a forum for those committed to gaining the best possible understanding of evolutionary processes through the application of modern quantitative methods for the collection and interpretation of data on marked animal populations. Here we present a short overview of the material presented in the session on evolutionary biology and life histories. In a plenary talk, Brown & Brown (2004 explored how mark–recapture methods have allowed a better understanding of the evolution of group–living and alternative reproductive tactics in colonial cliff swallows (Petrochelidon pyrrhonota. By estimating the number of transient birds passing through colonies of different sizes, they
With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics and computer science are now known as systems biology. Here I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.
Carson, Hampton L.
Cites examples of the contribution of basic research in evolutionary biology to the solution of problems facing society (1) by dispelling myths about human origins, the nature of the individual, and the nature of race (2) by providing basic data concerning the effects of overpopulation, the production of improved sources of food, resistance of…
Nesse, Randolph M; Bergstrom, Carl T; Ellison, Peter T; Flier, Jeffrey S; Gluckman, Peter; Govindaraju, Diddahally R; Niethammer, Dietrich; Omenn, Gilbert S; Perlman, Robert L; Schwartz, Mark D; Thomas, Mark G; Stearns, Stephen C; Valle, David
New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease.
Edward B. Chuong
Full Text Available In all mammals including humans, development takes place within the protective environment of the maternal womb. Throughout gestation, nutrients and waste products are continuously exchanged between mother and fetus through the placenta. Despite the clear importance of the placenta to successful pregnancy and the health of both mother and offspring, relatively little is understood about the biology of the placenta and its role in pregnancy-related diseases. Given that pre- and peri-natal diseases involving the placenta affect millions of women and their newborns worldwide, there is an urgent need to understand placenta biology and development. Here, we suggest that the placenta is an organ under unique selective pressures that have driven its rapid diversification throughout mammalian evolution. The high divergence of the placenta complicates the use of non-human animal models and necessitates an evolutionary perspective when studying its biology and role in disease. We suggest that diversifying evolution of the placenta is primarily driven by intraspecies evolutionary conflict between mother and fetus, and that many pregnancy diseases are a consequence of this evolutionary force. Understanding how maternal–fetal conflict shapes both basic placental and reproductive biology – in all species – will provide key insights into diseases of pregnancy.
The exploitation of linkage learning is enhancing the performance of evolutionary algorithms. This monograph examines recent progress in linkage learning, with a series of focused technical chapters that cover developments and trends in the field.
Stoops, John L.
As is becoming increasingly clear, the human species evolvedin the East African savannah. Details of the precise evolutionary chainremain unresolved however it appears that the process lasted severalmillion years, culminating with the emergence of modern Homo sapiensroughly 200,000 years ago. Following that final evolutionary developmentmodern Homo sapiens relatively quickly populated the entire world.Clearly modern Homo sapiens is a successful, resourceful and adaptablespecies. In the developed societies, modern humans live an existence farremoved from our evolutionary ancestors. As we have learned over the lastcentury, this "new" lifestyle can often result in unintendedconsequences. Clearly, our modern access to food, shelter, transportationand healthcare has resulted in greatly expanded expected lifespan butthis new lifestyle can also result in the emergence of different kinds ofdiseases and health problems. The environment in modern buildings haslittle resemblance to the environment of the savannah. We strive tocreate environments with little temperature, air movement and lightvariation. Building occupants often express great dissatisfaction withthese modern created environments and a significant fraction even developsomething akin to allergies to specific buildings (sick buildingsyndrome). Are the indoor environments we are creating fundamentallyunhealthy -- when examined from an evolutionary perspective?
Fisher, D N; McAdam, A G
effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.
Carroll, Scott P.; Jørgensen, Peter Søgaard; Kinnison, Michael T.; Bergstrom, Carl T.; Denison, R. Ford; Gluckman, Peter; Smith, Thomas B.; Strauss, Sharon Y.; Tabashnik, Bruce E.
Two categories of evolutionary challenges result from escalating human impacts on the planet. The first arises from cancers, pathogens and pests that evolve too quickly, and the second from the inability of many valued species to adapt quickly enough. Applied evolutionary biology provides a suite of strategies to address these global challenges that threaten human health, food security, and biodiversity. This review highlights both progress and gaps in genetic, developmental and environmental manipulations across the life sciences that either target the rate and direction of evolution, or reduce the mismatch between organisms and human-altered environments. Increased development and application of these underused tools will be vital in meeting current and future targets for sustainable development. PMID:25213376
Darriba, Diego; Flouri, Tomáš; Stamatakis, Alexandros
With Next Generation Sequencing data being routinely used, evolutionary biology is transforming into a computational science. Thus, researchers have to rely on a growing number of increasingly complex software. All widely used core tools in the field have grown considerably, in terms of the number of features as well as lines of code and consequently, also with respect to software complexity. A topic that has received little attention is the software engineering quality of widely used core analysis tools. Software developers appear to rarely assess the quality of their code, and this can have potential negative consequences for end-users. To this end, we assessed the code quality of 16 highly cited and compute-intensive tools mainly written in C/C++ (e.g., MrBayes, MAFFT, SweepFinder, etc.) and JAVA (BEAST) from the broader area of evolutionary biology that are being routinely used in current data analysis pipelines. Because, the software engineering quality of the tools we analyzed is rather unsatisfying, we provide a list of best practices for improving the quality of existing tools and list techniques that can be deployed for developing reliable, high quality scientific software from scratch. Finally, we also discuss journal as well as science policy and, more importantly, funding issues that need to be addressed for improving software engineering quality as well as ensuring support for developing new and maintaining existing software. Our intention is to raise the awareness of the community regarding software engineering quality issues and to emphasize the substantial lack of funding for scientific software development.
... and Evolutionary Dynamics of Pathogens * 21 Keith A. Crandall and Marcos Pérez-Losada II. Evolutionary Genetics of Microbial Pathogens 4. Environmental and Social Influences on Infectious Disea...
Dunn, Robert Roberdeau; Beasley, DeAnna E.
The engagement of the public in the scientific process is an old practice. Yet with recent advances in technology, the role of the citizen scientist in studying evolutionary processes has increased. Insects provide ideal models for understanding these evolutionary processes at large scales. This ...
Masudul Alam Choudhury
Full Text Available The usual kinds of Fixed-Point Theorems formalized on the existence of competitive equilibrium that explain much of economic theory at the core of economics can operate only on bounded and closed sets with convex mappings. But these conditions are hardly true of the real world of economic and financial complexities and perturbations. The category of learning sets explained by continuous fields of interactive, integrative and evolutionary behaviour caused by dynamic preferences at the individual and institutional and social levels cannot maintain the assumption of closed, bounded and convex sets. Thus learning sets and multi-system inter-temporal relations explained by pervasive complementarities and participation between variables and entities, and evolution by learning, have evolutionary equilibriums. Such a study requires a new methodological approach. This paper formalizes such a methodology for evolutionary equilibriums in learning spaces. It briefly points out the universality of learning equilibriums in all mathematical structures. For a particular case though, the inter-systemic interdependence between sustainable development and ethics and economics in the specific understanding of learning domain is pointed out.
Full Text Available Human biology, in terms of organization of our brains and our evolutionary past, constrains and enables learning. Two examples where neurobiology and evolution influences learning are given and discussed in relation to education: mirror neurons and adaptive memory. Mirror neurons serves imitation and understanding of other peoples intentions. Adaptive memory implies that our memory is an adaptation influenced by our evolutionary past, enabling us to solve problems in the present and in the future. Additionally, the aim is to contribute to bridges between natural and social sciences in an attempt to achieve an improved understanding of learning. The relevance of perspectives on learning founded in biology are discussed, and the article argues for including biological perspectives in discussions of education and learning processes.
Van Sciver, Robert E; Lee, Michael P; Lee, Caroline Dasom; Lafever, Alex C; Svyatova, Elizaveta; Kanda, Kevin; Colliver, Amber L; Siewertsz van Reesema, Lauren L; Tang-Tan, Angela M; Zheleva, Vasilena; Bwayi, Monicah N; Bian, Minglei; Schmidt, Rebecca L; Matrisian, Lynn M; Petersen, Gloria M; Tang, Amy H
Oncogenic K-RAS mutations are found in virtually all pancreatic cancers, making K-RAS one of the most targeted oncoproteins for drug development in cancer therapies. Despite intense research efforts over the past three decades, oncogenic K-RAS has remained largely "undruggable". Rather than targeting an upstream component of the RAS signaling pathway (i.e., EGFR/HER2) and/or the midstream effector kinases (i.e., RAF/MEK/ERK/PI3K/mTOR), we propose an alternative strategy to control oncogenic K-RAS signal by targeting its most downstream signaling module, Seven-In-Absentia Homolog (SIAH). SIAH E3 ligase controls the signal output of oncogenic K-RAS hyperactivation that drives unchecked cell proliferation, uncontrolled tumor growth, and rapid cancer cell dissemination in human pancreatic cancer. Therefore, SIAH is an ideal therapeutic target as it is an extraordinarily conserved downstream signaling gatekeeper indispensable for proper RAS signaling. Guided by molecular insights and core principles obtained from developmental and evolutionary biology, we propose an anti-SIAH-centered anti-K-RAS strategy as a logical and alternative anticancer strategy to dampen uncontrolled K-RAS hyperactivation and halt tumor growth and metastasis in pancreatic cancer. The clinical utility of developing SIAH as both a tumor-specific and therapy-responsive biomarker, as well as a viable anti-K-RAS drug target, is logically simple and conceptually innovative. SIAH clearly constitutes a major tumor vulnerability and K-RAS signaling bottleneck in pancreatic ductal adenocarcinoma (PDAC). Given the high degree of evolutionary conservation in the K-RAS/SIAH signaling pathway, an anti-SIAH-based anti-PDAC therapy will synergize with covalent K-RAS inhibitors and direct K-RAS targeted initiatives to control and eradicate pancreatic cancer in the future.
The study of evolutionary patterns of cognitive convergence would be greatly helped by a clear demarcation of cognition. Cognition is often used as an equivalent of mind, making it difficult to pin down empirically or to apply it confidently beyond the human condition. Recent developments in
This second essay continues the reflection on this problem through an exploration of the extra-biological factors and how they effect human moral development—a facet which is only too obvious, but which the evolutionary approach sidelines in its desperate effort to put up purely biological accounts of morality and ethics.
Full Text Available We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or "rewire", at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of "commonplace" networks such as family trees, co-authorships and linux-kernel function dependencies.
Van Hezewijk, René
Published as a chapter in Van Hezewijk, R. (2003). Psychology and evolutionary biology; Causal analysis, evidence, and nomothetic laws. In N. Stephenson, L. Radtke, R. Jorna & H. J. Stam (Eds.), Theoretical psychology; Critical contributions (pp. 405-415). Concord, Ontario: Captus Press.
S. D. Johnson
Full Text Available In the two decades after publication of the Origin of Species, Charles Darwin facilitated the publication of numerous scientific papers by settler naturalists in South Africa. This helped to establish the strong tradition of natural history which has characterised evolutionary research in South African museums, herbaria and universities. Significant developments in the early 20th century included the hominid fossil discoveries of Raymond Dart, Robert Broom, and others, but there was otherwise very little South African involvement in the evolutionary synthesis of the 1930s and 1940s. Evolutionary biology developed into a distinct discipline in South Africa during the 1970s and 1980s when it was dominated by mammalian palaeontology and a vigorous debate around species concepts. In the post-apartheid era, the main focus of evolutionary biology has been the construction of phylogenies for African plants and animals using molecular data, and the use of these phylogenies to answer questions about taxonomic classification and trait evolution. South African biologists have also recently contributed important evidence for some of Darwin’s ideas about plant–animal coevolution, sexual selection, and the role of natural selection in speciation. A bibliographic analysis shows that South African authors produce 2–3% of the world’s publications in the field of evolutionary biology, which is much higher than the value of about 0.5% for publications in all sciences. With its extraordinary biodiversity and well-developed research infrastructure, South Africa is an ideal laboratory from which to advance evolutionary research.
The thesis is concerned with learning distributions in the two settings of Evolutionary Strategies (ESs) and Restricted Boltzmann Machines (RBMs). In both cases, the distributions are learned from samples, albeit with different goals. Evolutionary Strategies are concerned with finding an optimum ...
The historical approach to the sciences has undergone a sea change during recent decades. Maybe the major contribution of Hans-Jörg Rheinberger to this movement was his demonstration of the importance of experimental systems, and of their transformations, in the development of the sciences. To describe these transformations, Hans-Jörg borrows metaphors from evolutionary biology. I want to argue that evolutionary biologists can find in these recent historical studies plenty of models and concepts to address unresolved issues in their discipline. At a time when transdisciplinarity is highly praised, it is useful to provide a precise description of the obstacles that have so far prevented this exchange.
The aim of this brief review article is to help to reconcile medicine with evolutionary biology, a subject that should be taught in medical school. Evolutionary medicine takes the view that contemporary ills are related to an incompatibility between the environment in which humans currently live and their genomes, which have been shaped by diferent environmental conditions during biological evolution. Human activity has recently induced acute environmental modifications that have profoundly changed the medical landscape. Evolutionary biology is an irreversible, ongoing and discontinuous process characterized by periods of stasis followed by accelerations. Evolutionary biology is determined by genetic mutations, which are selected either by Darwinian selective pressure or randomly by genetic drift. Most medical events result from a genome/environment conflict. Some may be purely genetic, as in monogenic diseases, and others purely environmental, such as traffic accidents. Nevertheless, in most common diseases the clinical landscape is determined by the conflict between these two factors, the genetic elements of which are gradually being unraveled Three examples are examined in depth:--The medical consequences of the greenhouse effect. The absence of excess mortality during recent heat waves suggests that the main determinant of mortality in the 2003 heatwave was heatstroke and old age. The projected long-term effects of global warming call for research on thermolysis, a forgotten branch of physiology.--The hygiene hypothesis postulates that the exponential rise in autoimmune and allergic diseases is linked to lesser exposure to infectious agents, possibly involving counter-regulatory factors such as IL-10.--The recent rise in the incidence of obesity and type 2 diabetes in rich countries can be considered to result from a conflict between a calorie-rich environment and gene variants that control appetite. These variants are currently being identified by genome
Han, Mira V; Zmasek, Christian M
Evolutionary trees are central to a wide range of biological studies. In many of these studies, tree nodes and branches need to be associated (or annotated) with various attributes. For example, in studies concerned with organismal relationships, tree nodes are associated with taxonomic names, whereas tree branches have lengths and oftentimes support values. Gene trees used in comparative genomics or phylogenomics are usually annotated with taxonomic information, genome-related data, such as gene names and functional annotations, as well as events such as gene duplications, speciations, or exon shufflings, combined with information related to the evolutionary tree itself. The data standards currently used for evolutionary trees have limited capacities to incorporate such annotations of different data types. We developed a XML language, named phyloXML, for describing evolutionary trees, as well as various associated data items. PhyloXML provides elements for commonly used items, such as branch lengths, support values, taxonomic names, and gene names and identifiers. By using "property" elements, phyloXML can be adapted to novel and unforeseen use cases. We also developed various software tools for reading, writing, conversion, and visualization of phyloXML formatted data. PhyloXML is an XML language defined by a complete schema in XSD that allows storing and exchanging the structures of evolutionary trees as well as associated data. More information about phyloXML itself, the XSD schema, as well as tools implementing and supporting phyloXML, is available at http://www.phyloxml.org.
Islas Morales, Parsifal
Evolutionary cell biology (ECB) has raised increasing attention in the last decades. Is this a new discipline and an historical opportunity to combine functional and evolutionary biology towards the insight that cell
The effort to relate mental and biological functioning has fluctuated between two doctrines: 1) an attempt to explain mental functioning as a collective property of the brain and 2) as one relatied to other mental processes associated with specific regions of the brain. The article reviews the main theories developed over the last 200 years: phrenology, the psuedo study of the brain, mass action, cellular connectionism and distributed processing among others. In addition, approaches have emerged in recent years that allows for an understanding of the biological determinants and individual differences in complex mental processes through what is called cognitive neuroscience. Knowing the definition of neuroscience, the learning of memory, the ways in which learning occurs, the principles of the neural basis of memory and learning and its effects on brain function, among other things, allows us the basic understanding of the processes of memory and learning and is an important requirement to address the best manner to commit to the of training future specialists in Psychiatry. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.
Information is a key concept in evolutionary biology. Information stored in a biological organism's genome is used to generate the organism and to maintain and control it. Information is also that which evolves. When a population adapts to a local environment, information about this environment is fixed in a representative genome. However, when an environment changes, information can be lost. At the same time, information is processed by animal brains to survive in complex environments, and the capacity for information processing also evolves. Here, I review applications of information theory to the evolution of proteins and to the evolution of information processing in simulated agents that adapt to perform a complex task. © 2012 New York Academy of Sciences.
Karmon, Amit; Pilpel, Yitzhak
Correlation does not imply causation. If two variables, say A and B, are correlated, it could be because A causes B, or that B causes A, or because a third factor affects them both. We suggest that in many cases in biology, the causal link might be bi-directional: A causes B through a fast-acting physiological process, while B causes A through a slowly accumulating evolutionary process. Furthermore, many trained biologists tend to consistently focus at first on the fast-acting direction, and overlook the slower process in the opposite direction. We analyse several examples from modern biology that demonstrate this bias (codon usage optimality and gene expression, gene duplication and genetic dispensability, stem cell division and cancer risk, and the microbiome and host metabolism) and also discuss an example from linguistics. These examples demonstrate mutual effects between the fast physiological processes and the slow evolutionary ones. We believe that building awareness of inference biases among biologists who tend to prefer one causal direction over another could improve scientific reasoning.
Tavares, Gustavo Medina; Bobrowski, Vera Lucia
The integrative role that Evolutionary theory plays within Biology is recognised by most scientific authors, as well as in governmental education policies, including Brazilian policies. However, teaching and learning evolution seems problematic in many countries, and Brazil is among those. Many factors may affect teachers' and students'…
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.
Kumar, Amrendra; Suryadevara, Naveenchandra; Hill, Timothy M.; Bezbradica, Jelena S.; Van Kaer, Luc; Joyce, Sebastian
Type I natural killer T (NKT) cells are innate-like T lymphocytes that recognize glycolipid antigens presented by the MHC class I-like protein CD1d. Agonistic activation of NKT cells leads to rapid pro-inflammatory and immune modulatory cytokine and chemokine responses. This property of NKT cells, in conjunction with their interactions with antigen-presenting cells, controls downstream innate and adaptive immune responses against cancers and infectious diseases, as well as in several inflammatory disorders. NKT cell properties are acquired during development in the thymus and by interactions with the host microbial consortium in the gut, the nature of which can be influenced by NKT cells. This latter property, together with the role of the host microbiota in cancer therapy, necessitates a new perspective. Hence, this review provides an initial approach to understanding NKT cells from an ecological evolutionary developmental biology (eco-evo-devo) perspective. PMID:29312339
Kumar, Amrendra; Suryadevara, Naveenchandra; Hill, Timothy M; Bezbradica, Jelena S; Van Kaer, Luc; Joyce, Sebastian
Type I natural killer T (NKT) cells are innate-like T lymphocytes that recognize glycolipid antigens presented by the MHC class I-like protein CD1d. Agonistic activation of NKT cells leads to rapid pro-inflammatory and immune modulatory cytokine and chemokine responses. This property of NKT cells, in conjunction with their interactions with antigen-presenting cells, controls downstream innate and adaptive immune responses against cancers and infectious diseases, as well as in several inflammatory disorders. NKT cell properties are acquired during development in the thymus and by interactions with the host microbial consortium in the gut, the nature of which can be influenced by NKT cells. This latter property, together with the role of the host microbiota in cancer therapy, necessitates a new perspective. Hence, this review provides an initial approach to understanding NKT cells from an ecological evolutionary developmental biology (eco-evo-devo) perspective.
The 'Modern Synthesis' (Neo-Darwinism) is a mid-20th century gene-centric view of evolution, based on random mutations accumulating to produce gradual change through natural selection. Any role of physiological function in influencing genetic inheritance was excluded. The organism became a mere carrier of the real objects of selection, its genes. We now know that genetic change is far from random and often not gradual. Molecular genetics and genome sequencing have deconstructed this unnecessarily restrictive view of evolution in a way that reintroduces physiological function and interactions with the environment as factors influencing the speed and nature of inherited change. Acquired characteristics can be inherited, and in a few but growing number of cases that inheritance has now been shown to be robust for many generations. The 21st century can look forward to a new synthesis that will reintegrate physiology with evolutionary biology.
Full Text Available Type I natural killer T (NKT cells are innate-like T lymphocytes that recognize glycolipid antigens presented by the MHC class I-like protein CD1d. Agonistic activation of NKT cells leads to rapid pro-inflammatory and immune modulatory cytokine and chemokine responses. This property of NKT cells, in conjunction with their interactions with antigen-presenting cells, controls downstream innate and adaptive immune responses against cancers and infectious diseases, as well as in several inflammatory disorders. NKT cell properties are acquired during development in the thymus and by interactions with the host microbial consortium in the gut, the nature of which can be influenced by NKT cells. This latter property, together with the role of the host microbiota in cancer therapy, necessitates a new perspective. Hence, this review provides an initial approach to understanding NKT cells from an ecological evolutionary developmental biology (eco-evo-devo perspective.
Haigh, Carol A
This paper presents a discussion of the role of altruism in development of the discipline of nursing and an exploration of how nursing altruism compares with current thinking in biological evolutionary theory. There is an assumption that the role of the nurse has its foundations in altruistic behaviours; however, the source of this altruism is never analysed or debated. A search of the biological altruism, altruism and health-related literature encompassing the years 1975-2007 was performed using Google Scholar. The first element of the study is a brief overview of nursing altruism as a way of establishing the conceptual boundaries. Additionally, the major tenets of biological evolution are explored to clarify the theoretical underpinnings of the hypotheses presented. A key premise of this study is that nursing altruism is not solely a manifestation of disinterested sacrifice for the benefit of others, but is more concerned with ensuring the survival of a clearly defined social group. A re-evaluation of altruism as a motivating factor in nursing and as an element of the therapeutic relationship is long overdue. It is time that the nursing profession examined professional driving forces using more than traditional philosophical frameworks. Nursing altruism is programmed to ensure the survival of the meme rather than to act in the best interest of patients. Certainly patients reap the benefits of this selfish altruism, but that can be argued to be a side effect rather than a result.
White, Roderick E.; Thornhill, Stewart; Hampson, Elizabeth
Biological evolutionary processes select for heritable behaviors providing a survival and reproductive advantage. Accordingly, how we behave is, at least in part, affected by the evolutionary history of our species. This research uses evolutionary psychology as the theoretical perspective for exploring the relationship between a heritable…
Islas Morales, Parsifal
lessons learned from ECB and attempts to find a homologue structure of the eukaryotic nucleolus within the Archaea. We found nanometric structures in S. solfactarius that either are positive to specific nucleolar techniques such as Nucleolar organizer regions NOR silver staining. These is structures are novel and its significance should be revised on the evolutionary cell biology perspective.
Hommes, Cars H.
We briefly review some work on expectations and learning in complex markets, using the familiar demand-supply cobweb model. We discuss and combine two different approaches on learning. According to the adaptive learning approach, agents behave as econometricians using time series observations to form expectations, and update the parameters as more observations become available. This approach has become popular in macro. The second approach has an evolutionary flavor and is sometimes referred to as reinforcement learning. Agents employ different forecasting strategies and evaluate these strategies based upon a fitness measure, e.g. past realized profits. In this framework, boundedly rational agents switch between different, but fixed behavioral rules. This approach has become popular in finance. We combine evolutionary and adaptive learning to model complex markets and discuss whether this theory can match empirical facts and forecasting behavior in laboratory experiments with human subjects.
Morgan, T J H; Rendell, L E; Ehn, M; Hoppitt, W; Laland, K N
Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.
Eiben, A.; Horvath, Mark; Kowalczyk, Wojtek; Schut, Martijn
The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). We are running an RL procedure and the EA simultaneously and the RL is changing the EA parameters on-the-fly. We
Klymkowsky, Michael W; Rentsch, Jeremy D; Begovic, Emina; Cooper, Melanie M
Many introductory biology courses amount to superficial surveys of disconnected topics. Often, foundational observations and the concepts derived from them and students' ability to use these ideas appropriately are overlooked, leading to unrealistic expectations and unrecognized learning obstacles. The result can be a focus on memorization at the expense of the development of a meaningful framework within which to consider biological phenomena. About a decade ago, we began a reconsideration of what an introductory course should present to students and the skills they need to master. The original Web-based course's design presaged many of the recommendations of the Vision and Change report; in particular, a focus on social evolutionary mechanisms, stochastic (evolutionary and molecular) processes, and core ideas (cellular continuity, evolutionary homology, molecular interactions, coupled chemical reactions, and molecular machines). Inspired by insights from the Chemistry, Life, the Universe & Everything general chemistry project, we transformed the original Web version into a (freely available) book with a more unified narrative flow and a set of formative assessments delivered through the beSocratic system. We outline how student responses to course materials are guiding future course modifications, in particular a more concerted effort at helping students to construct logical, empirically based arguments, explanations, and models. © 2016 M. W. Klymkowsky et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Tavares, Gustavo Medina; Bobrowski, Vera Lucia
The integrative role that Evolutionary theory plays within Biology is recognised by most scientific authors, as well as in governmental education policies, including Brazilian policies. However, teaching and learning evolution seems problematic in many countries, and Brazil is among those. Many factors may affect teachers' and students' perceptions towards evolution, and studies can help to reveal those factors. We used a conceptual questionnaire, the Measure of Acceptance of the Theory of Evolution (MATE) instrument, and a Knowledge test to assess (1) the level of acceptance and understanding of 23 undergraduate Biology students nearing the end of their course, (2) other factors that could affect these levels, including course structure, and (3) the most difficult topics regarding evolutionary biology. The results of this study showed that the students, on average, had a 'Very High Acceptance' (89.91) and a 'Very Low Knowledge' (59.42%) of Evolutionary theory, and also indicated a moderate positive correlation between the two (r = 0.66, p = .001). The most difficult topics were related to the definition of evolution and dating techniques. We believe that the present study provides evidence for policymakers to reformulate current school and university curricula in order to improve the teachers' acceptance and understanding of evolution and other biological concepts, consequently, helping students reduce their misconceptions related to evolutionary biology.
Oliver Y. Martin
Full Text Available It is now generally acknowledged that climate change has wide-ranging biological consequences, potentially leading to impacts on biodiversity. Environmental factors can have diverse and often strong effects on reproduction, with obvious ramifications for population fitness. Nevertheless, reproductive traits are often neglected in conservation considerations. Focusing on animals, recent progress in sexual selection and sexual conflict research suggests that reproductive costs may pose an underestimated hurdle during rapid climate change, potentially lowering adaptive potential and increasing extinction risk of certain populations. Nevertheless, regime shifts may have both negative and positive effects on reproduction, so it is important to acquire detailed experimental data. We hence present an overview of the literature reporting short-term reproductive consequences of exposure to different environmental factors. From the enormous diversity of findings, we conclude that climate change research could benefit greatly from more coordinated efforts incorporating evolutionary approaches in order to obtain cross-comparable data on how individual and population reproductive fitness respond in the long term. Therefore, we propose ideas and methods concerning future efforts dealing with reproductive consequences of climate change, in particular by highlighting the advantages of multi-generational experimental evolution experiments.
Grossman, G. D.
Full Text Available I discuss current issues in reviewing and editorial practices in ecology and evolutionary biology and suggest possible solutions for current problems. The reviewing crisis is unlikely to change unless steps are taken by journals to provide greater inclusiveness and incentives to reviewers. In addition, both journals and institutions should reduce their emphasis on publication numbers (least publishable units and impact factors and focus instead on article synthesis and quality which will require longer publications. Academic and research institutions should consider reviewing manuscripts and editorial positions an important part of a researcher’s professional activities and reward them accordingly. Rewarding reviewers either monetarily or via other incentives such as free journal subscriptions may encourage participation in the reviewing process for both profit and non–profit journals. Reviewer performance will likely be improved by measures that increase inclusiveness, such as sending reviews and decision letters to reviewers. Journals may be able to evaluate the efficacy of their reviewing process by comparing citations of rejected but subsequently published papers with those published within the journal at similar times. Finally, constructive reviews: 1 identify important shortcomings and suggest solutions when possible, 2 distinguish trivial from non–trivial problems, and 3 include editor’s evaluations of the reviews including identification of trivial versus substantive comments (i.e., those that must be addressed.
Full Text Available Nitrogenase, which catalyzes the ATP-dependent reduction of dinitrogen (N2 to ammonia (NH3, accounts for roughly half of the bioavailable nitrogen supporting extant life. The fundamental requirement for fixed forms of nitrogen for life on Earth, both at present and in the past, has led to broad and significant interest in the origin and evolution of this fundamental biological process. One key question is whether the limited availability of fixed nitrogen was a factor in life’s origin or whether there were ample sources of fixed nitrogen produced by abiotic processes or delivered through the weathering of bolide impact materials to support this early life. If the latter, the key questions become what were the characteristics of the environment that precipitated the evolution of this oxygen sensitive process, when did this occur, and how was its subsequent evolutionary history impacted by the advent of oxygenic photosynthesis and the rise of oxygen in the Earth’s biosphere. Since the availability of fixed sources of nitrogen capable of supporting early life is difficult to glean from the geologic record, there are limited means to get direct insights into these questions. Indirect insights, however, can be gained by deep phylogenetic studies of nitrogenase structural gene products and additional gene products involved in the biosynthesis of the complex metal-containing prosthetic groups associated with this enzyme complex. Insights gained from such studies, as reviewed herein, challenge traditional models for the evolution of biological nitrogen fixation and provide the basis for the development of new conceptual models that explain the stepwise evolution of this highly complex and life sustaining process.
Vecchi, Davide; Baravalle, Lorenzo
This paper will critically assess Popper's evolutionary philosophy. There exists a rich literature on the topic with which we have many reservations. We believe that Popper's evolutionary philosophy should be assessed in light of the intriguing theoretical insights offered, during the last 10 years or so, by the philosophy of biology, evolutionary biology and molecular biology. We will argue that, when analysed in this manner, Popper's ideas concerning the nature of selection, Lamarckism and the theoretical limits of neo-Darwinism can be appreciated in their full biological and philosophical value.
Team, Galaxy; Goecks, Jeremy; Taylor, James
Abstract Research in population genetics and evolutionary biology has always provided a computational backbone for life sciences as a whole. Today evolutionary and population biology reasoning are essential for interpretation of large complex datasets that are characteristic of all domains of today’s life sciences ranging from cancer biology to microbial ecology. This situation makes algorithms and software tools developed by our community more important than ever before. This means that we, developers of software tool for molecular evolutionary analyses, now have a shared responsibility to make these tools accessible using modern technological developments as well as provide adequate documentation and training. PMID:29688462
Izzo, Dario; Sprague, Christopher; Tailor, Dharmesh
After providing a brief historical overview on the synergies between artificial intelligence research, in the areas of evolutionary computations and machine learning, and the optimal design of interplanetary trajectories, we propose and study the use of deep artificial neural networks to represent, on-board, the optimal guidance profile of an interplanetary mission. The results, limited to the chosen test case of an Earth-Mars orbital transfer, extend the findings made previously for landing ...
Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll
This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...
Perlman, Robert L
Evolutionary biology was a poorly developed discipline at the time of the Flexner Report and was not included in Flexner's recommendations for premedical or medical education. Since that time, however, the value of an evolutionary approach to medicine has become increasingly recognized. There are several ways in which an evolutionary perspective can enrich medical education and improve medical practice. Evolutionary considerations rationalize our continued susceptibility or vulnerability to disease; they call attention to the idea that the signs and symptoms of disease may be adaptations that prevent or limit the severity of disease; they help us understand the ways in which our interventions may affect the evolution of microbial pathogens and of cancer cells; and they provide a framework for thinking about population variation and risk factors for disease. Evolutionary biology should become a foundational science for the medical education of the future.
Chen, Bor-Sen; Yeh, Chin-Hsun
We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.
A hundred years is but an instant in evolutionary time; however during his life that spanned a century, Ernst Mayr (1904-2005) made outstanding contributions to our understanding of the pat- tern and process of evolution. An ornithologist and systematist by training, Mayr embraced Darwinism and championed the cause of.
Cao, Xuanyu; Liu, K. J. Ray
In this work, we study the social learning problem, in which agents of a networked system collaborate to detect the state of the nature based on their private signals. A novel distributed graphical evolutionary game theoretic learning method is proposed. In the proposed game-theoretic method, agents only need to communicate their binary decisions rather than the real-valued beliefs with their neighbors, which endows the method with low communication complexity. Under mean field approximations, we theoretically analyze the steady state equilibria of the game and show that the evolutionarily stable states (ESSs) coincide with the decisions of the benchmark centralized detector. Numerical experiments are implemented to confirm the effectiveness of the proposed game-theoretic learning method.
Echaubard, Pierre; Sripa, Banchob; Mallory, Frank F; Wilcox, Bruce A
Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. Copyright © 2016 Elsevier B.V. All rights reserved.
This study investigated the effects of different styles of social interaction on the learning of advanced biological knowledge. Recent research has increasingly acknowledged the importance of social interaction for promoting learning and cognitive development. However, there has been a controversy about the optimal style of interaction. Some studies have showed the beneficial effects of symmetrical interactions such as an argument between peers, whereas other studies have found the superiority of asymmetrical interactions in which a novice learn with the guidance of an expert. The reason for the contradictory results may be that different styles of interaction enhance different kinds of learning. The present study focused on the three styles of interaction; (1) Conflicting style, in which two novice students with scientifically wrong but conflicting views argue with one another, (2) Guiding style, in which a novice student is led by a more expert student to an understanding of scientifically appropriate knowledge, (3) Mutual Constructive style, in which an expert student and a novice student jointly solve a scientific problem on an equal footing. Sixty college students with non-biology-majors and 30 students with a biology major participated in this experiment to discuss an evolutionary problem in these three styles of interaction, with the former serving as novices and the latter as experts. Analyses of the Pre- and the Posttest performance and discussion processes in the Interaction session revealed the following. First, the Guiding style and the Mutual Constructive style enhanced the acquisition of the scientific evolutionary conceptual framework more effectively than the Conflicting style. However, some students in the Conflicting style also grasped the scientific evolutionary framework, and many students reconstructed their theories of evolution through discussion, even if the frameworks remained scientifically inappropriate. Second, the students who discussed
Friedman, William E; Diggle, Pamela K
Much has been written of the early history of comparative embryology and its influence on the emergence of an evolutionary developmental perspective. However, this literature, which dates back nearly a century, has been focused on metazoans, without acknowledgment of the contributions of comparative plant morphologists to the creation of a developmental view of biodiversity. We trace the origin of comparative plant developmental morphology from its inception in the eighteenth century works of Wolff and Goethe, through the mid nineteenth century discoveries of the general principles of leaf and floral organ morphogenesis. Much like the stimulus that von Baer provided as a nonevolutionary comparative embryologist to the creation of an evolutionary developmental view of animals, the comparative developmental studies of plant morphologists were the basis for the first articulation of the concept that plant (namely floral) evolution results from successive modifications of ontogeny. Perhaps most surprisingly, we show that the first person to carefully read and internalize the remarkable advances in the understanding of plant morphogenesis in the 1840s and 1850s is none other than Charles Darwin, whose notebooks, correspondence, and (then) unpublished manuscripts clearly demonstrate that he had discovered the developmental basis for the evolutionary transformation of plant form.
Maria R Servedio
Full Text Available Progress in science often begins with verbal hypotheses meant to explain why certain biological phenomena exist. An important purpose of mathematical models in evolutionary research, as in many other fields, is to act as “proof-of-concept” tests of the logic in verbal explanations, paralleling the way in which empirical data are used to test hypotheses. Because not all subfields of biology use mathematics for this purpose, misunderstandings of the function of proof-of-concept modeling are common. In the hope of facilitating communication, we discuss the role of proof-of-concept modeling in evolutionary biology.
da Silva, Paloma Rodrigues; de Andrade, Mariana A. Bologna Soares; de Andrade Caldeira, Ana Maria
Biology is a science that involves study of the diversity of living organisms. This diversity has always generated questions and has motivated cultures to seek plausible explanations for the differences and similarities between types of organisms. In biology teaching, these issues are addressed by adopting an evolutionary approach. The aim of this…
Sheng-Zhi Du; Zeng-Qiang Chen; Zhu-Zhi Yuan
This paper analyzes the sensitivity to noise in BAM (Bidirectional Associative Memory), and then proves the noise immunity of BAM relates not only to the minimum absolute value of net inputs (MAV) but also to the variance of weights associated with synapse connections. In fact, it is a positive monotonically increasing function of the quotient of MAV divided by the variance of weights. Besides, the performance of pseudo-relaxation method depends on learning parameters (λ and ζ), but the relation of them is not linear. So it is hard to find a best combination of λ and ζ which leads to the best BAM performance. And it is obvious that pseudo-relaxation is a kind of local optimization method, so it cannot guarantee to get the global optimal solution. In this paper, a novel learning algorithm EPRBAM (evolutionary psendo-relaxation learning algorithm for bidirectional association memory) employing genetic algorithm and pseudo-relaxation method is proposed to get feasible solution of BAM weight matrix. This algorithm uses the quotient as the fitness of each individual and employs pseudo-relaxation method to adjust individual solution when it does not satisfy constraining condition any more after genetic operation. Experimental results show this algorithm improves noise immunity of BAM greatly. At the same time, EPRBAM does not depend on learning parameters and can get global optimal solution.
Badyaev, Alexander V
In complex organisms, neutral evolution of genomic architecture, associated compensatory interactions in protein networks and emergent developmental processes can delineate the directions of evolutionary change, including the opportunity for natural selection. These effects are reflected in the evolution of developmental programmes that link genomic architecture with a corresponding functioning phenotype. Two recent findings call for closer examination of the rules by which these links are constructed. First is the realization that high dimensionality of genotypes and emergent properties of autonomous developmental processes (such as capacity for self-organization) result in the vast areas of fitness neutrality at both the phenotypic and genetic levels. Second is the ubiquity of context- and taxa-specific regulation of deeply conserved gene networks, such that exceptional phenotypic diversification coexists with remarkably conserved generative processes. Establishing the causal reciprocal links between ongoing neutral expansion of genomic architecture, emergent features of organisms' functionality, and often precisely adaptive phenotypic diversification therefore becomes an important goal of evolutionary biology and is the latest reincarnation of the search for a framework that links development, functioning and evolution of phenotypes. Here I examine, in the light of recent empirical advances, two evolutionary concepts that are central to this framework-natural selection and inheritance-the general rules by which they become associated with emergent developmental and homeostatic processes and the role that they play in descent with modification.
Richardson, Elisabeth; Zerr, Kelly; Tsaousis, Anastasios; Dorrell, Richard G; Dacks, Joel B
In animal and fungal model organisms, the complexities of cell biology have been analyzed in exquisite detail and much is known about how these organisms function at the cellular level. However, the model organisms cell biologists generally use include only a tiny fraction of the true diversity of eukaryotic cellular forms. The divergent cellular processes observed in these more distant lineages are still largely unknown in the general scientific community. Despite the relative obscurity of these organisms, comparative studies of them across eukaryotic diversity have had profound implications for our understanding of fundamental cell biology in all species and have revealed the evolution and origins of previously observed cellular processes. In this Perspective, we will discuss the complexity of cell biology found across the eukaryotic tree, and three specific examples of where studies of divergent cell biology have altered our understanding of key functional aspects of mitochondria, plastids, and membrane trafficking. © 2015 Richardson et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei
The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.
Crutzen, Rik; Peters, Gjalt-Jorn Ygram
We argue that the active ingredients of behaviour change interventions, often called behaviour change methods (BCMs) or techniques (BCTs), can usefully be placed on a dimension of psychological aggregation. We introduce evolutionary learning processes (ELPs) as fundamental building blocks that are on a lower level of psychological aggregation than BCMs/BCTs. A better understanding of ELPs is useful to select the appropriate BCMs/BCTs to target determinants of behaviour, or vice versa, to identify potential determinants targeted by a given BCM/BCT, and to optimally translate them into practical applications. Using these insights during intervention development may increase the likelihood of developing effective interventions - both in terms of behaviour change as well as maintenance of behaviour change.
Majaj, Najib; Pelli, Denis
Today most vision-science presentations mention machine learning. Many neuroscientists use machine learning to decode neural responses. Many perception scientists try to understand recognition by living organisms. To them, machine learning offers a reference of attainable performance based on learned stimuli. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions.
During evolution, the cell as a fine-tuned machine had to undergo permanent adjustments to match changes in its environment, while "closed for repair work" was not possible. Evolution from protists (protozoa and unicellular algae) to multicellular organisms may have occurred in basically two lineages, Unikonta and Bikonta, culminating in mammals and angiosperms (flowering plants), respectively. Unicellular models for unikont evolution are myxamoebae (Dictyostelium) and increasingly also choanoflagellates, whereas for bikonts, ciliates are preferred models. Information accumulating from combined molecular database search and experimental verification allows new insights into evolutionary diversification and maintenance of genes/proteins from protozoa on, eventually with orthologs in bacteria. However, proteins have rarely been followed up systematically for maintenance or change of function or intracellular localization, acquirement of new domains, partial deletion (e.g. of subunits), and refunctionalization, etc. These aspects are discussed in this review, envisaging "evolutionary cell biology." Protozoan heritage is found for most important cellular structures and functions up to humans and flowering plants. Examples discussed include refunctionalization of voltage-dependent Ca 2+ channels in cilia and replacement by other types during evolution. Altogether components serving Ca 2+ signaling are very flexible throughout evolution, calmodulin being a most conservative example, in contrast to calcineurin whose catalytic subunit is lost in plants, whereas both subunits are maintained up to mammals for complex functions (immune defense and learning). Domain structure of R-type SNAREs differs in mono- and bikonta, as do Ca 2+ -dependent protein kinases. Unprecedented selective expansion of the subunit a which connects multimeric base piece and head parts (V0, V1) of H + -ATPase/pump may well reflect the intriguing vesicle trafficking system in ciliates, specifically in
Reti, Irene H.; Burney, Le Boeuf J; Jarrell, Randall
Burney Le Boeuf was born in southern Louisiana. He attended UC Berkeley, earning his PhD in experimental psychology in 1966. While at Berkeley, he also studied zoology and experimental biology. He arrived at UCSC in 1967 as a member of the psychology board and of Crown College. He already had a strong interest in evolutionary biology and participated in the biology board’s meetings as an outside member. He also began working with biology professor Richard Peterson on seal and sea lion researc...
Eugene V. Koonin
Full Text Available When Charles Darwin formulated the central principles of evolutionary biology in the Origin of Species in 1859 and the architects of the Modern Synthesis integrated these principles with population genetics almost a century later, the principal if not the sole objects of evolutionary biology were multicellular eukaryotes, primarily animals and plants. Before the advent of efficient gene sequencing, all attempts to extend evolutionary studies to bacteria have been futile. Sequencing of the rRNA genes in thousands of microbes allowed the construction of the three- domain ‘ribosomal Tree of Life’ that was widely thought to have resolved the evolutionary relationships between the cellular life forms. However, subsequent massive sequencing of numerous, complete microbial genomes revealed novel evolutionary phenomena, the most fundamental of these being: i pervasive horizontal gene transfer (HGT, in large part mediated by viruses and plasmids, that shapes the genomes of archaea and bacteria and call for a radical revision (if not abandonment of the Tree of Life concept, ii Lamarckian-type inheritance that appears to be critical for antivirus defense and other forms of adaptation in prokaryotes, and iii evolution of evolvability, i.e. dedicated mechanisms for evolution such as vehicles for HGT and stress-induced mutagenesis systems. In the non-cellular part of the microbial world, phylogenomics and metagenomics of viruses and related selfish genetic elements revealed enormous genetic and molecular diversity and extremely high abundance of viruses that come across as the dominant biological entities on earth. Furthermore, the perennial arms race between viruses and their hosts is one of the defining factors of evolution. Thus, microbial phylogenomics adds new dimensions to the fundamental picture of evolution even as the principle of descent with modification discovered by Darwin and the laws of population genetics remain at the core of evolutionary
Yaroslavsky, Leonid P.
We show that one can treat pseudo-random generators, evolutionary models of texture images, iterative local adaptive filters for image restoration and enhancement and growth models in biology and material sciences in a unified way as special cases of dynamic systems with a nonlinear feedback.
Laudel, Grit; Benninghoff, Martin; Lettkemann, Eric; Håkansson, Elias; Whitley, Richard; Gläser, Jochen
Evolutionary developmental biology is a highly variable scientific innovation because researchers can adapt their involvement in the innovation to the opportunities provided by their environment. On the basis of comparative case studies in four countries, we link epistemic properties of research
Passmore, Cynthia; Stewart, James
Recent education reform documents emphasize the need for students to develop a rich understanding of evolution's power to integrate knowledge of the natural world. This paper describes a nine-week high school course designed to help students understand evolutionary biology by engaging them in developing, elaborating, and using Charles Darwin's…
Ramirez, Aaron Robert
The unique nature of island ecosystems have fascinated generations of naturalists, ecologists, and evolutionary biologists. Studying island systems led to the development of keystone biological theories including: Darwin and Wallace's theories of natural selection, Carlquist's insights into the biology of adaptive radiations, MacArthur and Wilson's theory of island biogeography, and many others. Utilizing islands as natural laboratories allows us to discover the underlying fabric of ecology a...
Silva, Fernando; Correia, Luís; Christensen, Anders Lyhne
Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm.
Caceres, M.O.; Caceres-Saez, I.
We present a perturbative formalism to deal with linear random matrix difference equations. We generalize the concept of the population growth rate when a Leslie matrix has random elements (i.e., characterizing the disorder in the vital parameters). The dominant eigenvalue of which defines the asymptotic dynamics of the mean value population vector state, is presented as the effective growth rate of a random Leslie model. This eigenvalue is calculated from the largest positive root of a secular polynomial. Analytical (exact and perturbative calculations) results are presented for several models of disorder. A 3 x 3 numerical example is applied to study the effective growth rate characterizing the long-time dynamics of a population biological case: the Tursiops sp. (author)
Michael D Barton
Full Text Available Every protein has a biosynthetic cost to the cell based on the synthesis of its constituent amino acids. In order to optimise growth and reproduction, natural selection is expected, where possible, to favour the use of proteins whose constituents are cheaper to produce, as reduced biosynthetic cost may confer a fitness advantage to the organism. Quantifying the cost of amino acid biosynthesis presents challenges, since energetic requirements may change across different cellular and environmental conditions. We developed a systems biology approach to estimate the cost of amino acid synthesis based on genome-scale metabolic models and investigated the effects of the cost of amino acid synthesis on Saccharomyces cerevisiae gene expression and protein evolution. First, we used our two new and six previously reported measures of amino acid cost in conjunction with codon usage bias, tRNA gene number and atomic composition to identify which of these factors best predict transcript and protein levels. Second, we compared amino acid cost with rates of amino acid substitution across four species in the genus Saccharomyces. Regardless of which cost measure is used, amino acid biosynthetic cost is weakly associated with transcript and protein levels. In contrast, we find that biosynthetic cost and amino acid substitution rates show a negative correlation, but for only a subset of cost measures. In the economy of the yeast cell, we find that the cost of amino acid synthesis plays a limited role in shaping transcript and protein expression levels compared to that of translational optimisation. Biosynthetic cost does, however, appear to affect rates of amino acid evolution in Saccharomyces, suggesting that expensive amino acids may only be used when they have specific structural or functional roles in protein sequences. However, as there appears to be no single currency to compute the cost of amino acid synthesis across all cellular and environmental
Chen, Bor-Sen; Lin, Ying-Po
In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563
Machado, Marcelo Dornellas; Schirru, Roberto
Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for combinatorial problems optimization. In this work, a new learning mode, to be used by the population-based incremental learning algorithm, has the aim to build a new evolutionary algorithm to be used in optimization of numerical problems and combinatorial problems. This new learning mode uses a variable learning rate during the optimization process, constituting a process known as proportional reward. The development of this new algorithm aims its application in the optimization of reload problem of PWR nuclear reactors, in order to increase the useful life of the nuclear fuel. For the test, two classes of problems are used: numerical problems and combinatorial problems. Due to the fact that the reload problem is a combinatorial problem, the major interest relies on the last class. The results achieved with the tests indicate the applicability of the new learning mode, showing its potential as a developing tool in the solution of reload problem. (author)
O'Malley, Maureen A
Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.
Evolution as an idea has a lengthy history, even though the idea of evolution is generally associated with Darwin today. Rebecca Stott provides an engaging and thoughtful overview of this history of evolutionary thinking in her 2013 book, Darwin's Ghosts: The Secret History of Evolution. Since Darwin, the debate over evolution—both how it takes place and, in a long war of words with religiously-oriented thinkers, whether it takes place—has been sustained and heated. A growing share of this debate is now devoted to examining how evolutionary thinking affects areas outside of biology. How do our lives change when we recognize that all is in flux? What can we learn about life more generally if we study change instead of stasis? Carter Phipps’ book, Evolutionaries: Unlocking the Spiritual and Cultural Potential of Science's Greatest Idea, delves deep into this relatively new development. Phipps generally takes as a given the validity of the Modern Synthesis of evolutionary biology. His story takes us into, as the subtitle suggests, the spiritual and cultural implications of evolutionary thinking. Can religion and evolution be reconciled? Can evolutionary thinking lead to a new type of spirituality? Is our culture already being changed in ways that we don't realize by evolutionary thinking? These are all important questions and Phipps book is a great introduction to this discussion. Phipps is an author, journalist, and contributor to the emerging “integral” or “evolutionary” cultural movement that combines the insights of Integral Philosophy, evolutionary science, developmental psychology, and the social sciences. He has served as the Executive Editor of EnlightenNext magazine (no longer published) and more recently is the co-founder of the Institute for Cultural Evolution, a public policy think tank addressing the cultural roots of America's political challenges. What follows is an email interview with Phipps. PMID:26478766
Carroll, Juliet E.
This monograph contains 10 plant pathology experiments that were written to correspond to portions of a biology curriculum. Each experiment is suitable to a biology topic and designed to encourage exploration of those biological concepts being taught. Experiments include: (1) The Symptoms and Signs of Disease; (2) Koch's Postulates; (3)…
.... A Perception-based reasoning approach based on co-evolutionary reinforcement learning was developed for jointly addressing sensor allocation on each individual UAV and allocation of a team of UAVs...
Skene, Keith R.
This paper addresses a key issue confronting ecological and evolutionary biology, namely the challenge of a cohesive approach to these fields given significant differences in the concepts and foundations of their study. Yet these two areas of scientific research are paramount in terms addressing the spatial and temporal dynamics and distribution of diversity, an understanding of which is needed if we are to resolve the current crisis facing the biosphere. The importance of understanding how nature responds to change is now of essential rather than of metaphysical interest as our planet struggles with increasing anthropogenic damage. Ecology and evolutionary biology can no longer remain disjointed. While some progress has been made in terms of synthetic thinking across these areas, this has often been in terms of bridge building, where thinking in one aspect is extended over to the other side. We review these bridges and the success or otherwise of such efforts. This paper then suggests that in order to move from a descriptive to a mechanistic understanding of the biosphere, we may need to re-evaluate our approach to the studies of ecology and evolutionary biology, finding a common denominator that will enable us to address the critical issues facing us, particularly in terms of understanding what drives change, what determines tempo and how communities function. Common ground, we argue, is essential if we are to comprehend how resilience operates in the natural world and how diversification can counter increasing extinction rates. This paper suggests that thermodynamics may provide a bridge between ecology and evolutionary biology, and that this will enable us to move forward with otherwise intractable problems.
Malik, Aamina H.; Ziermann, Janine M.; Diogo, Rui
Textbooks on the history of biology and evolutionary thought do not mention the evolutionary ideas of Muslim scholars before Darwin's time. This is part of a trend in the West to minimise the contributions of non-Western scientists to biology, human anatomy and evolutionary biology. Therefore, this paper focuses on the contributions of…
In this paper we present ELeaRNT an evolutionary strategy which evolves rich neural network topologies in order to find an optimal domain specific non linear function approximator with a good generalization performance...
Kandel, Eric R.; Hawkins, Robert D.
Describes the biological basis of learning and individuality. Presents an overview of recent discoveries that suggest learning engages a simple set of rules that modify the strength of connection between neurons in the brain. The changes are cited as playing an important role in making each individual unique. (MCO)
Bonier, Frances; Martin, Paul R
An evolutionary perspective can enrich almost any endeavour in biology, providing a deeper understanding of the variation we see in nature. To this end, evolutionary endocrinologists seek to describe the fitness consequences of variation in endocrine traits. Much of the recent work in our field, however, follows a flawed approach to the study of how selection shapes endocrine traits. Briefly, this approach relies on among-individual correlations between endocrine phenotypes (often circulating hormone levels) and fitness metrics to estimate selection on those endocrine traits. Adaptive plasticity in both endocrine and fitness-related traits can drive these correlations, generating patterns that do not accurately reflect natural selection. We illustrate why this approach to studying selection on endocrine traits is problematic, referring to work from evolutionary biologists who, decades ago, described this problem as it relates to a variety of other plastic traits. We extend these arguments to evolutionary endocrinology, where the likelihood that this flaw generates bias in estimates of selection is unusually high due to the exceptional responsiveness of hormones to environmental conditions, and their function to induce adaptive life-history responses to environmental variation. We end with a review of productive approaches for investigating the fitness consequences of variation in endocrine traits that we expect will generate exciting advances in our understanding of endocrine system evolution. © 2016 The Author(s).
Kong, Yi; Anderson, Trevor; Pelaez, Nancy
Evolutionary trees are key tools for modern biology and are commonly portrayed in textbooks to promote learning about biological evolution. However, many people have difficulty in understanding what evolutionary trees are meant to portray. In fact, some ideas that current professional biologists depict with evolutionary trees are neither clearly…
Full Text Available Abstract Background Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni’s proteome evolution and to improve its functional annotation. Results Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org. Conclusions In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into
Full Text Available The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.
Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V
The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.
Kamath, Uday Krishna
Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…
Fiete, Ila Rani
How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and
Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung
The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and…
After the inaugural Pan-American-Evo-Devo meeting (2015, Berkeley), I showed how major concerns about evo-devo (Evolutionary Developmental Biology) research were demonstrated by a simple, non-biased quantitative analysis of the titles/abstracts of that meeting's talks. Here, I apply the same methodology to the titles/abstracts of the recent Pan-American-Evo-Devo meeting (2017, Calgary). The aim is to evaluate if the concerns raised by me in that paper and by other authors have been addressed and/or if there are other types of differences between the two meetings that may reflect trends within the field of evo-devo. This analysis shows that the proportion of presentations referring to "morphology", "organism", "selection", "adaptive", "phylogeny", and their derivatives was higher in the 2017 meeting, which therefore had a more "organismal" feel. However, there was a decrease in the use of "evolution"/its derivatives and of macroevolutionary terms related to the tempo and mode of evolution in the 2017 meeting. Moreover, the disproportionately high use of genetic/genomic terms clearly shows that evo-devo continues to be mainly focused on devo, and particularly on "Geno", that is, on molecular/genetic studies. Furthermore, the vast majority of animal evo-devo studies are focused only on hard tissues, which are just a small fraction of the whole organism-for example, only 15% of the tissue mass of the human body. The lack of an integrative approach is also evidenced by the lack of studies addressing conceptual/long-standing broader questions, including the links between ecology and particularly behavior and developmental/evolutionary variability and between evo-devo and evolutionary medicine. © 2018 Wiley Periodicals, Inc.
Full Text Available Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that several studies have been tried to achieve. In recent years, probability-based evolutionary algorithms have been proposed as a new efficient approach to learn Bayesian networks. In this paper, we target on one of the probability-based evolutionary algorithms called PBIL (Probability-Based Incremental Learning, and propose a new mutation operator. Through performance evaluation, we found that the proposed mutation operator has a good performance in learning Bayesian networks
Wong, Ka Chun
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
Chitpin, Jeremy Sebastian; Chitpin, Stephanie
Purpose: Through a series of critical discussions on Karl Popper's evolutionary analysis of learning and the non-authoritarian values it promotes, the purpose of this paper is to advocate a Popperian approach for building medical student knowledge. Specifically, it challenges positivist assumptions that permeate the design and management of many…
Whiteson, S.; Taylor, M.E.; Stone, P.
Temporal difference and evolutionary methods are two of the most common approaches to solving reinforcement learning problems. However, there is little consensus on their relative merits and there have been few empirical studies that directly compare their performance. This article aims to address
Murray, Darrel L.
This article reviews recent research studies and experiences relating the learning theories of Ausubel to biology instruction. Also some suggestions are made for future research on the learning of biology. (MR)
Liao, David; Tlsty, Thea D
Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.
We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/ f2 fluctuations are found for the model without demographic noise. © 2010 The American Physical Society.
Murase, Yohsuke; Shimada, Takashi; Ito, Nobuyasu; Rikvold, Per Arne
We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/ f2 fluctuations are found for the model without demographic noise. © 2010 The American Physical Society.
Martin, George M
What might now be referred to as the "classical" evolutionary biological theory of why we age has had a number of serious challenges in recent years. While the theory might therefore have to be modified under certain circumstances, in the author's opinion, it still provides the soundest theoretical basis for thinking about how we age. Nine modalities of gene action that have the potential to modulate processes of aging are reviewed, including the two most widely reviewed and accepted concepts ("antagonistic pleiotropy" and "mutation accumulation"). While several of these nine mechanisms can be regarded as derivatives of the antagonistic pleiotropic concept, they frame more specific questions for future research. Such research should pursue what appears to be the dominant factor in the determination of intraspecific variations in longevity-stochastic mechanisms, most likely based upon epigenetics. This contrasts with the dominant factor in the determination of interspecific variations in longevity-the constitutional genome, most likely based upon variations in regulatory loci.
Wensink, Maarten; Westendorp, Rudi G J; Baudisch, Annette
A general concept for thinking about causality facilitates swift comprehension of results, and the vocabulary that belongs to the concept is instrumental in cross-disciplinary communication. The causal pie model has fulfilled this role in epidemiology and could be of similar value in evolutionary biology and ecology. In the causal pie model, outcomes result from sufficient causes. Each sufficient cause is made up of a "causal pie" of "component causes". Several different causal pies may exist for the same outcome. If and only if all component causes of a sufficient cause are present, that is, a causal pie is complete, does the outcome occur. The effect of a component cause hence depends on the presence of the other component causes that constitute some causal pie. Because all component causes are equally and fully causative for the outcome, the sum of causes for some outcome exceeds 100%. The causal pie model provides a way of thinking that maps into a number of recurrent themes in evolutionary biology and ecology: It charts when component causes have an effect and are subject to natural selection, and how component causes affect selection on other component causes; which partitions of outcomes with respect to causes are feasible and useful; and how to view the composition of a(n apparently homogeneous) population. The diversity of specific results that is directly understood from the causal pie model is a test for both the validity and the applicability of the model. The causal pie model provides a common language in which results across disciplines can be communicated and serves as a template along which future causal analyses can be made.
Machado, Marcelo Dornellas
Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for function optimization. In this work, a new learning mode, to be used by the Population-Based Incremental Learning (PBIL) algorithm, who combines mechanisms of standard genetic algorithm with simple competitive learning, has the aim to build a new evolutionary algorithm to be used in optimization of numerical problems and combinatorial problems. This new learning mode uses a variable learning rate during the optimization process, constituting a process know as proportional reward. The development of this new algorithm aims its application in the optimization of reload problem of PWR nuclear reactors. This problem can be interpreted as search of a load pattern to be used in the nucleus of the reactor in order to increase the useful life of the nuclear fuel. For the test, two classes of problems are used: numerical problems and combinatorial problem, the major interest relies on the last class. The results achieved with the tests indicate the applicability of the new learning mode, showing its potential as a developing tool in the solution of reload problem. (author)
Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung
The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and large, it was found that the students reflected "mixed" motives in biology learning, while those who had more sophisticated epistemic beliefs tended to employ deep strategies. In addition, the results of paired t tests revealed that the female students were more likely to possess beliefs about biological knowledge residing in external authorities, to believe in a right answer, and to utilize rote learning as a learning strategy. Moreover, compared to juniors and seniors, freshmen and sophomores tended to hold less mature views on all factors of epistemic beliefs regarding biology. Another comparison indicated that theoretical biology students (e.g. students majoring in the Department of Biology) tended to have more mature beliefs in learning biology and more advanced strategies for biology learning than those students studying applied biology (e.g. in the Department of Biotechnology). Stepwise regression analysis, in general, indicated that students who valued the role of experiments and justify epistemic assumptions and knowledge claims based on evidence were more oriented towards having mixed motives and utilizing deep strategies to learn biology. In contrast, students who believed in the certainty of biological knowledge were more likely to adopt rote learning strategies and to aim to qualify in biology.
. Consequently, research has increasingly focused on the underlying causes of disease, shaped by human evolution. Evolutionary medicine is a relatively new field, specifically bridging the gap between conventional medicine and evolutionary biology: Instead of asking how we get sick, we can apply evolutionary...... explanations for this phenomenon. This thesis demonstrates how taking an evolutionary perspective can help us to better understand important aspects of health and medicine that remain opaque, using the specific example of pregnancy-related conditions.......Medicine has made a giant leap forward over the last century when it comes to the treatment of human disease, but even the most cutting edge 21st century medicine cannot prevent new diseases arising, nor those thought to be extinct developing resistance to pharmaceuticals and returning...
of biological and cultural evolution. Demographic variation within and among human populations is influenced by our biology, and therefore by natural selection and our evolutionary background. Demographic methods are necessary for studying populations of other species, and for quantifying evolutionary fitness......Demography is the quantitative study of population processes, while evolution is a population process that influences all aspects of biological organisms, including their demography. Demographic traits common to all human populations are the products of biological evolution or the interaction...
Full Text Available Abstract Background Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge. Results We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC devoted to BN structure learning. Conclusion We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.
Jamali, D.; Khoury, G.; Sahyoun, H.
Purpose: To track changes in management paradigms from the bureaucratic to the post-bureaucratic to the learning organization model, highlighting core differentiating features of each paradigm as well as necessary ingredients for successful evolution. Design/methodology/approach: The article takes the form of a literature review and critical…
Full Text Available Within the mind, there are a myriad of ideas that make sense within the bounds of everyday experience, but are not reflective of how the world actually exists; this is particularly true in the domain of science. Classroom learning with teacher explanation are a bridge through which these naive understandings can be brought in line with scientific reality. The purpose of this paper is to examine how the application of a Multiobjective Evolutionary Algorithm (MOEA can work in concert with an existing computational-model to effectively model critical-thinking in the science classroom. An evolutionary algorithm is an algorithm that iteratively optimizes machine learning based computational models. The research question is, does the application of an evolutionary algorithm provide a means to optimize the Student Task and Cognition Model (STAC-M and does the optimized model sufficiently represent and predict teaching and learning outcomes in the science classroom? Within this computational study, the authors outline and simulate the effect of teaching on the ability of a “virtual” student to solve a Piagetian task. Using the Student Task and Cognition Model (STAC-M a computational model of student cognitive processing in science class developed in 2013, the authors complete a computational experiment which examines the role of cognitive retraining on student learning. Comparison of the STAC-M and the STAC-M with inclusion of the Multiobjective Evolutionary Algorithm shows greater success in solving the Piagetian science-tasks post cognitive retraining with the Multiobjective Evolutionary Algorithm. This illustrates the potential uses of cognitive and neuropsychological computational modeling in educational research. The authors also outline the limitations and assumptions of computational modeling.
Alexander Mackenzie Rivero
Full Text Available The use of machine learning allows the creation of a predictive data model, as a result of the analysis in a data set with 286 instances and nine attributes belonging to the Institute of Oncology of the University Medical Center. Ljubljana. Based on this situation, the data are preprocessed by applying intelligent data analysis techniques to eliminate missing values as well as the evaluation of each attribute that allows the optimization of results. We used several classification algorithms including J48 trees, random forest, bayes net, naive bayes, decision table, in order to obtain one that given the characteristics of the data, would allow the best classification percentage and therefore a better matrix of confusion, Using 66 % of the data for learning and 33 % for validating the model. Using this model, a predictor with a 71,134 % e effectiveness is obtained to estimate or not the recurrence of breast cancer.
Lindström, Björn; Selbing, Ida; Olsson, Andreas
Danger is a fundamental aspect of the lives of most animals. Adaptive behavior therefore requires avoiding actions, objects, and environments associated with danger. Previous research has shown that humans and non-human animals can avoid such dangers through two types of behavioral adaptions, (i) genetic preparedness to avoid certain stimuli or actions, and (ii) social learning. These adaptive mechanisms reduce the fitness costs associated with danger but still allow flexible behavior. Despite the empirical prevalence and importance of both these mechanisms, it is unclear when they evolve and how they interact. We used evolutionary agent-based simulations, incorporating empirically based learning mechanisms, to clarify if preparedness and social learning typically both evolve in dangerous environments, and if these mechanisms generally interact synergistically or antagonistically. Our simulations showed that preparedness and social learning often co-evolve because they provide complimentary benefits: genetic preparedness reduced foraging efficiency, but resulted in a higher rate of survival in dangerous environments, while social learning generally came to dominate the population, especially when the environment was stochastic. However, even in this case, genetic preparedness reliably evolved. Broadly, our results indicate that the relationship between preparedness and social learning is important as it can result in trade-offs between behavioral flexibility and safety, which can lead to seemingly suboptimal behavior if the evolutionary environment of the organism is not taken into account.
Peter J Thomas
Full Text Available In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control of a soccer playing micro-robot from any configuration belonging to a grid of initial configurations to hit the ball along the ball to goal line of sight. The knowledge base uses relative co-ordinate system including left and right wheel velocities of the robot. Final path positions allow forward and reverse facing robot to ball and include its physical dimensions.
Levin, Betty Wolder; Browner, C H
In 1946, the newly formed World Health Organization boldly sought to conceptualize "health" as wellbeing in the positive sense, "not merely the absence of disease or infirmity." Yet nearly six decades later, researchers are still principally concerned with pathology and its characteristics and consequences. This special issue is the result of an effort to broaden the focus. Anthropologists working from evolutionary, biological and sociocultural perspectives and in diverse geographic regions were asked to examine meanings associated with health and/or to identify social conditions and practices that have contributed to positive physiological and psychological states in particular cultures, times, or across time. Most notable, perhaps, was discovering how difficult it is for Western social scientists to move beyond pathology-based thinking; most authors represented here regard health primarily as the absence of disease. Still, these papers articulate and address questions key to understanding health in and of itself, including: How is health conceptualized? What kinds of social conditions lead to health? And, how do social inequalities affect health? This introduction critically discusses previous work on the subject to contextualize the original research papers offered here.
Schulz, Armin W
I argue for differences in the cognitive efficiency of different psychologies underlying helping behavior, and present an account of the adaptive pressures that result from these differences. Specifically, I argue that organisms often face pressure to move away from only being egoistically motivated to help: non-egoistic organisms are often able to determine how to help other organisms more quickly and with less recourse to costly cognitive resources like concentration and attention. Furthermore, I also argue that, while these pressures away from pure egoism can lead to the evolution of altruists, they can also lead to the evolution of reciprocation-focused behaviorist helpers or even of reflex-driven helpers (who are neither altruists nor egoists). In this way, I seek to broaden the set of considerations typically taken into account when assessing the evolution of the psychology of helping behavior-which tend to be restricted to matters of reliability-and also try to make clearer the role of evolutionary biological considerations in the discussion of this apparently straightforwardly psychological phenomenon. Copyright © 2015 Elsevier Ltd. All rights reserved.
Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.
Bohlin, Gustav; Höst, Gunnar E.
The present study explores the extent and precision of evolutionary explanations for antibiotic resistance in communication directed toward the Swedish public. Bacterial resistance develops through evolutionary mechanisms and knowledge of these helps to explain causes underlying the growing prevalence of resistant strains, as well as important…
Moore, Michael Edward
Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is…
Grunspan, Daniel Z; Nesse, Randolph M; Barnes, M Elizabeth; Brownell, Sara E
Abstract Background and objectives Evolutionary medicine is a rapidly growing field that uses the principles of evolutionary biology to better understand, prevent and treat disease, and that uses studies of disease to advance basic knowledge in evolutionary biology. Over-arching principles of evolutionary medicine have been described in publications, but our study is the first to systematically elicit core principles from a diverse panel of experts in evolutionary medicine. These principles should be useful to advance recent recommendations made by The Association of American Medical Colleges and the Howard Hughes Medical Institute to make evolutionary thinking a core competency for pre-medical education. Methodology The Delphi method was used to elicit and validate a list of core principles for evolutionary medicine. The study included four surveys administered in sequence to 56 expert panelists. The initial open-ended survey created a list of possible core principles; the three subsequent surveys winnowed the list and assessed the accuracy and importance of each principle. Results Fourteen core principles elicited at least 80% of the panelists to agree or strongly agree that they were important core principles for evolutionary medicine. These principles over-lapped with concepts discussed in other articles discussing key concepts in evolutionary medicine. Conclusions and implications This set of core principles will be helpful for researchers and instructors in evolutionary medicine. We recommend that evolutionary medicine instructors use the list of core principles to construct learning goals. Evolutionary medicine is a young field, so this list of core principles will likely change as the field develops further. PMID:29493660
Chevalier, Robert L
Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as "maladaptive." In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic) adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ~40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons), evolutionary selection for APOL1 mutations (that provide resistance to trypanosome infection, a tradeoff), and modern life experience (Western diet mismatch leading to diabetes and hypertension). Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo), developmental programming and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.
Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both
Mahmud, Mufti; Kaiser, Mohammed Shamim; Hussain, Amir; Vassanelli, Stefano
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence. The growth in computational power accompanied by faster and increased data storage, and declining computing costs have already allowed scientists in various fields to apply these techniques on data sets that were previously intractable owing to their size and complexity. This paper provides a comprehensive survey on the application of DL, RL, and deep RL techniques in mining biological data. In addition, we compare the performances of DL techniques when applied to different data sets across various application domains. Finally, we outline open issues in this challenging research area and discuss future development perspectives.
Yu, Xiang-Tian; Wang, Lu; Zeng, Tao
Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.
List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric
For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to
Felzien, Lisa; Salem, Laura
Service learning involves providing service to the community while requiring students to meet learning goals in a specific course. A service learning project was implemented in a general biology course at Rockhurst University to involve students in promoting scientific education in conjunction with community partner educators. Students were…
Full Text Available A primary goal of university instruction is the students’ demonstration of improved, highly developed critical thinking (CT skills. However, how do faculty encourage CT and its potential concomitant increase in student workload without negatively impacting student perceptions of the course? In this investigation, an advanced biology course is evaluated after structural changes (implemented in 2010 met with a poor student evaluation of the course and the instructor. This analysis first examines the steps used to transform a course to encourage CT and then explains how it can be assessed. To accomplish these goals, the instructor collaborated with an educational developer to redesign the course using a philosophy informed by SoTL. This approach, as we see it, represents a set of principles that demand transparency in the development and application of strategies whose aim is to encourage student learning. However, the SoTL approach would be insufficient to simply promote a set of strategies without some mechanism for evaluating its efficacy. Therefore, we designed a “Graded Response” (GR multiple-choice test to measure CT development and hence to properly evaluate whether the strategies embedded in our SoTL-informed course redesign have adequately met our goals.
Bergh, van den Jeroen C.J.M.; Gowdy, John M.
We consider the microfoundations controversy from the perspective ofeconomic evolution and show that the debate can benefit from lessons learned in evolutionary biology. Although the analogy between biology and economics has been noted before, it has rarely focused on clarifying the micro-macro
Novak, Joseph D.
The material presented in this article is intended to help students learn how to learn. The seven key concepts of David Ausubel's assimilation theory for cognitive learning are discussed with reference to the classroom. Concept mapping is suggested as a tool for demonstrating how the seven key concepts function. (SA)
An, Ji-Yong; Zhang, Lei; Zhou, Yong; Zhao, Yu-Jun; Wang, Da-Fu
Self-interactions Proteins (SIPs) is important for their biological activity owing to the inherent interaction amongst their secondary structures or domains. However, due to the limitations of experimental Self-interactions detection, one major challenge in the study of prediction SIPs is how to exploit computational approaches for SIPs detection based on evolutionary information contained protein sequence. In the work, we presented a novel computational approach named WELM-LAG, which combined the Weighed-Extreme Learning Machine (WELM) classifier with Local Average Group (LAG) to predict SIPs based on protein sequence. The major improvement of our method lies in presenting an effective feature extraction method used to represent candidate Self-interactions proteins by exploring the evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix (PSSM); and then employing a reliable and robust WELM classifier to carry out classification. In addition, the Principal Component Analysis (PCA) approach is used to reduce the impact of noise. The WELM-LAG method gave very high average accuracies of 92.94 and 96.74% on yeast and human datasets, respectively. Meanwhile, we compared it with the state-of-the-art support vector machine (SVM) classifier and other existing methods on human and yeast datasets, respectively. Comparative results indicated that our approach is very promising and may provide a cost-effective alternative for predicting SIPs. In addition, we developed a freely available web server called WELM-LAG-SIPs to predict SIPs. The web server is available at http://184.108.40.206:8888/WELMLAG/ .
Samuel Agus Triyanto
Biologi abad 21 merupakan integrasi dan mengintegrasikan kembali sub disiplin ilmu biologi, serta integrasi biologi dengan disiplin ilmu lain untuk mengatasi permasalahan sosial. Penelitian ini bertujuan untuk mengetahui penerapan Blended-Problem Based Learning, aktivitas belajar, dan respon siswa dalam pembelajaran biologi. Penelitian ini merupakan penelitian survei dengan pendekatan deskriptif kualitatif. Data hasil penelitian menunjukkan bahwa aktivitas positif siswa dalam pembelajaran memuaskan, sedangkan respon siswa baik terhadap pembelajaran. Berdasarkan hasil penelitian, disimpulkan bahwa Blended-Problem Based Learning dapat diterapkan dan diterima sebagai model dalam pembelajaran.
Full Text Available INTRODUCTION: Evolution has been recognized as a key concept for biologists. In order to motivate biology undergraduates for contents of central energetic metabolism, we addressed the Krebs cycle structure and functions to an evolutionary view. To this end, we created a study guide which contextualizes the emergence of the cyclic pathway, in light of the prokaryotic influence since early Earth anaerobic condition to oxygen rise in atmosphere. OBJECTIVES: The main goal is to highlight the educational potential of the material whose subject is scarcely covered in biochemistry textbooks. MATERIALS AND METHODS: The study guide is composed by three interrelated sections, the problem (Section 1, designed to arouse curiosity, inform and motivate students; an introductory text (Section 2 about life evolution, including early micro-organisms and Krebs cycle emergence, and questions (Section 3 for debate. The activity consisted on a peer discussion session, with instructors tutoring. The questions were designed to foster exchange of ideas in an ever-increasing level of complexity, and cover subjects from early atmospheric conditions to organization of the metabolism along the subsequent geological ages. RESULTS AND DISCUSSION: We noticed that students were engaged and motivated by the task, especially during group discussion. Based on students’ feedbacks and class observations, we learned that the material raised curiosity and stimulated discussion among peers. It brought a historical and purposeful way of dealing with difficult biochemical concepts. CONCLUSIONS: The whole experience suggests that the study guide was a stimulus for broadening comprehension of the Krebs cycle, reinforcing the evolutionary stance as an important theme for biology and biochemistry understanding. On the other hand, we do not underestimate the fact that approaching Krebs cycle from an evolutionary standpoint is a quite complex discussion for the majority of students
Konstantinidis, Konstantinos T; Serres, Margrethe H; Romine, Margaret F; Rodrigues, Jorge L M; Auchtung, Jennifer; McCue, Lee-Ann; Lipton, Mary S; Obraztsova, Anna; Giometti, Carol S; Nealson, Kenneth H; Fredrickson, James K; Tiedje, James M
To what extent genotypic differences translate to phenotypic variation remains a poorly understood issue of paramount importance for several cornerstone concepts of microbiology including the species definition. Here, we take advantage of the completed genomic sequences, expressed proteomic profiles, and physiological studies of 10 closely related Shewanella strains and species to provide quantitative insights into this issue. Our analyses revealed that, despite extensive horizontal gene transfer within these genomes, the genotypic and phenotypic similarities among the organisms were generally predictable from their evolutionary relatedness. The power of the predictions depended on the degree of ecological specialization of the organisms evaluated. Using the gradient of evolutionary relatedness formed by these genomes, we were able to partly isolate the effect of ecology from that of evolutionary divergence and to rank the different cellular functions in terms of their rates of evolution. Our ranking also revealed that whole-cell protein expression differences among these organisms, when the organisms were grown under identical conditions, were relatively larger than differences at the genome level, suggesting that similarity in gene regulation and expression should constitute another important parameter for (new) species description. Collectively, our results provide important new information toward beginning a systems-level understanding of bacterial species and genera.
Parker, William; Ollerton, Jeff
Industrialized society currently faces a wide range of non-infectious, immune-related pandemics. These pandemics include a variety of autoimmune, inflammatory and allergic diseases that are often associated with common environmental triggers and with genetic predisposition, but that do not occur in developing societies. In this review, we briefly present the idea that these pandemics are due to a limited number of evolutionary mismatches, the most damaging being 'biome depletion'. This particular mismatch involves the loss of species from the ecosystem of the human body, the human biome, many of which have traditionally been classified as parasites, although some may actually be commensal or even mutualistic. This view, evolved from the 'hygiene hypothesis', encompasses a broad ecological and evolutionary perspective that considers host-symbiont relations as plastic, changing through ecological space and evolutionary time. Fortunately, this perspective provides a blueprint, termed 'biome reconstitution', for disease treatment and especially for disease prevention. Biome reconstitution includes the controlled and population-wide reintroduction (i.e. domestication) of selected species that have been all but eradicated from the human biome in industrialized society and holds great promise for the elimination of pandemics of allergic, inflammatory and autoimmune diseases.
AlShahrani, Mona; Khan, Mohammed Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Nú ria; Hoehndorf, Robert
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph
Zaslansky, Paul; Currey, John D; Fleck, Claudia
The main mass of material found in teeth is dentine, a bone-like tissue, riddled with micron-sized tubules and devoid of living cells. It provides support to the outer wear-resistant layer of enamel, and exhibits toughening mechanisms which contribute to crack resistance. And yet unlike most bone tissues, dentine does not remodel and consequently any accumulated damage does not 'self repair'. Because damage containment followed by tissue replacement is a prime reason for the crack-arresting microstructures found in most bones, the occurrence of toughening mechanisms without the biological capability to repair is puzzling. Here we consider the notion that dentine might be overdesigned for strength, because it has to compensate for the lack of cell-mediated healing mechanisms. Based on our own and on literature-reported observations, including quasistatic and fatigue properties, dentine design principles are discussed in light of the functional conditions under which teeth evolved. We conclude that dentine is only slightly overdesigned for everyday cyclic loading because usual mastication stresses may come close to its endurance strength. The in-built toughening mechanisms constitute an evolutionary benefit because they prevent catastrophic failure during rare overload events, which was probably very advantageous in our hunter gatherer ancestor times. From a bio-inspired perspective, understanding the extent of evolutionary overdesign might be useful for optimising biomimetic structures used for load bearing.
Discusses how biologists use evolutionary theory and provides examples of how evolutionary biologists test hypotheses on specific modes of selection and evolution. Presents an example of the successful predictive power of one evolutionary hypothesis. Contains 38 references. (DDR)
Home; Journals; Resonance – Journal of Science Education; Volume 21; Issue 9. Evolutionary Stable Strategy: Application of Nash Equilibrium in Biology. General Article Volume 21 Issue 9 September 2016 pp 803- ... Keywords. Evolutionary game theory, evolutionary stable state, conflict, cooperation, biological games.
The biases of individual language learners act to determine the learnability and cultural stability of languages: learners come to the language learning task with biases which make certain linguistic systems easier to acquire than others. These biases are repeatedly applied during the process of language transmission, and consequently should effect the types of languages we see in human populations. Understanding the cultural evolutionary consequences of particular learning biases is therefore central to understanding the link between language learning in individuals and language universals, common structural properties shared by all the world’s languages. This paper reviews a range of models and experimental studies which show that weak biases in individual learners can have strong effects on the structure of socially learned systems such as language, suggesting that strong universal tendencies in language structure do not require us to postulate strong underlying biases or constraints on language learning. Furthermore, understanding the relationship between learner biases and language design has implications for theories of the evolution of those learning biases: models of gene-culture coevolution suggest that, in situations where a cultural dynamic mediates between properties of individual learners and properties of language in this way, biological evolution is unlikely to lead to the emergence of strong constraints on learning.
Robert L. Chevalier
Full Text Available Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as “maladaptive.” In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or from evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ∼40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons, evolutionary selection for APOL1 mutations (which provide resistance to trypanosome infection, a tradeoff, and modern life experience (Western diet mismatch leading to diabetes and hypertension. Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout the life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo, developmental programming, and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.
The purpose of this study was to analyze the relation between students' cognitive learning strategies and conceptions of learning biology. The two scales, "Cognitive Learning Strategies" and "Conceptions of Learning Biology", were revised and adapted to biology in order to measure the students' learning strategies and…
Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung
This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely "multiple-source," "uncertainty," "development," and "justification." COLB is further…
Full Text Available Timely learning of specialized science vocabulary is critical for building a solid knowledge base in any scientific discipline. To motivate students to dedicate time and effort mastering biology vocabulary, I have designed a vocabulary exercise utilizing the popular web encyclopedia Wikipedia. The exercise creates an opportunity for students to connect the challenge of vocabulary learning to a prior positive experience of self-guided learning using a content source they are familiar and comfortable with.
In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information
May, S. Randolph; Cook, David L.; May, Marilyn K.
Biology courses have thousands of words to learn in order to intelligently discuss the subject and take tests over the material. Biological fluency is an important goal for students, and practical methods based on constructivist pedagogies can be employed to promote it. We present a method in which pairs of students write dialogues from…
Full Text Available In two upper-level elective biology courses and one beginning-level general biology course, college students participated in Learning Partnerships with middle or high school classes to study some aspect of biology. The goals were to enhance learning by providing resources to middle and high school students and teachers and by encouraging college students to consider teaching as a learning tool and a possible career goal. The college students designed lessons, activities, and laboratories that were done at the schools and at Bates College. Feedback and data suggest that the partnerships have helped teachers enrich their curricula, enhanced student learning, encouraged additional high school students to consider applying to college, and encouraged college students to consider teaching science.
Kalmady, Sunil V; Venkatasubramanian, Ganesan; Arasappa, Rashmi; Rao, Naren P
MEF2C facilitates context-dependent fear conditioning (CFC) which is a salient aspect of hippocampus-dependent learning and memory. CFC might have played a crucial role in human evolution because of its advantageous influence on survival of species. In this study, we analyzed 23 orthologous mammalian gene sequences of MEF2C gene to examine the evidence for positive selection on this gene in Homo sapiens using Phylogenetic Analysis by Maximum Likelihood (PAML) and HyPhy software. Both PAML Bayes Empirical Bayes (BEB) and HyPhy Fixed Effects Likelihood (FEL) analyses supported significant positive selection on 4 codon sites in H. sapiens. Also, haplotter analysis revealed significant ongoing positive selection on this gene in Central European population. The study findings suggest that adaptive selective pressure on this gene might have influenced human evolution. Further research on this gene might unravel the potential role of this gene in learning and memory as well as its pathogenetic effect in certain hippocampal disorders with evolutionary basis like schizophrenia. Copyright © 2012 Elsevier B.V. All rights reserved.
Zhou, Ming-Sheng; Wang, Aimei; Yu, Hong
Insulin resistance and hypertension are considered as prototypical "diseases of civilization" that are manifested in the modern environment as plentiful food and sedentary life. The human propensity for insulin resistance and hypertension is a product, at least in part, of our evolutionary history. Adaptation to ancient lifestyle characterized by a low sodium, low-calorie food supply and physical stress to injury response has driven our evolution to shape and preserve a thrifty genotype, which is favorite with energy-saving and sodium conservation. As our civilization evolved, a sedentary lifestyle and sodium- and energy-rich diet, the thrifty genotype is no longer advantageous, and may be maladaptive to disease phenotype, such as hypertension, obesity and insulin resistance syndrome. This article reviews human evolution and the impact of the modern environment on hypertension and insulin resistance.
Evolutionary medicine allows new insights into long standing medical problems. Are we "really stoneagers on the fast lane"? This insight might have enormous consequences and will allow new answers that could never been provided by traditional anthropology. Only now this is made possible using data from molecular medicine and systems biology. Thereby evolutionary medicine takes a leap from a merely theoretical discipline to practical fields - reproductive, nutritional and preventive medicine, as well as microbiology, immunology and psychiatry. Evolutionary medicine is not another "just so story" but a serious candidate for the medical curriculum providing a universal understanding of health and disease based on our biological origin. © Georg Thieme Verlag KG Stuttgart · New York.
Moore, Michael Edward
Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is why active learning is such an effective instructional tool and the limits of this instructional method’s ability to influence performance. This dissertation builds a case in three steps for why active learning is an effective instructional tool. In step one, I assessed the influence of different types of active learning (clickers, group activities, and whole class discussions) on student engagement behavior in one semester of two different introductory biology courses and found that active learning positively influenced student engagement behavior significantly more than lecture. For step two, I examined over four semesters whether student engagement behavior was a predictor of performance and found participation (engagement behavior) in the online (video watching) and in-class course activities (clicker participation) that I measure were significant predictors of performance. In the third, I assessed whether certain active learning satisfied the psychological needs that lead to students’ intrinsic motivation to participate in those activities when compared over two semesters and across two different institutions of higher learning. Findings from this last step show us that student’s perceptions of autonomy, competency, and relatedness in doing various types of active learning are significantly higher than lecture and consistent across two institutions of higher learning. Lastly, I tie everything together, discuss implications of the research, and address future directions for research on biology student motivation and behavior.
Petersen, Morten Rask; Dohn, Niels Bonderup
for learning (e.g. Krapp, 2002). Here we turn the interplay and see learning as a facilitator for interest development. This interplay was studied in upper secondary biology education. Student’s conducted an exercise on modelling natural selection with LEGO® bricks (Christensen-Dalsgaard & Kanneworf, 2009...... support our initial hypothesis that learning can be a facilitator for interest development. This is an argument for focusing more on didactical approaches and learning environments if the goal is to have interested students. As stated by Dewey: “If we can discover a child’s urgent needs and powers...
Wu, Zujian; Pang, Wei; Coghill, George M
Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.
The medaka Oryzias latipes is a small egg-laying freshwater teleost, and has become an excellent model system for developmental genetics and evolutionary biology. The medaka genome is relatively small in size, approximately 800 Mb, and the genome sequencing project was recently completed by Japanese research groups, providing a high-quality draft genome sequence of the inbred Hd-rR strain of medaka. In this review, I present an overview of the medaka genome project including genome resources, followed by specific findings obtained with the medaka draft genome. In particular, I focus on the analysis that was done by taking advantage of the medaka system, such as the sex chromosome differentiation and the regional history of medaka species using single nucleotide polymorphisms as genomic markers.
LaBare, Kelly M.; Broyles, Steven B.; Klotz, R. Lawrence
Discusses the importance of studying nectar biology. Describes how to extract nectar from various flowers, measure nectar volume, determine sugar concentration, and determine caloric value per nectar sample. These data are then related to hummingbird energetics to determine how many flowers are required to supply the pollinator with its caloric…
Bauch, Chris T; Bhattacharyya, Samit
Immunization programs have often been impeded by vaccine scares, as evidenced by the measles-mumps-rubella (MMR) autism vaccine scare in Britain. A "free rider" effect may be partly responsible: vaccine-generated herd immunity can reduce disease incidence to such low levels that real or imagined vaccine risks appear large in comparison, causing individuals to cease vaccinating. This implies a feedback loop between disease prevalence and strategic individual vaccinating behavior. Here, we analyze a model based on evolutionary game theory that captures this feedback in the context of vaccine scares, and that also includes social learning. Vaccine risk perception evolves over time according to an exogenously imposed curve. We test the model against vaccine coverage data and disease incidence data from two vaccine scares in England & Wales: the whole cell pertussis vaccine scare and the MMR vaccine scare. The model fits vaccine coverage data from both vaccine scares relatively well. Moreover, the model can explain the vaccine coverage data more parsimoniously than most competing models without social learning and/or feedback (hence, adding social learning and feedback to a vaccine scare model improves model fit with little or no parsimony penalty). Under some circumstances, the model can predict future vaccine coverage and disease incidence--up to 10 years in advance in the case of pertussis--including specific qualitative features of the dynamics, such as future incidence peaks and undulations in vaccine coverage due to the population's response to changing disease incidence. Vaccine scares could become more common as eradication goals are approached for more vaccine-preventable diseases. Such models could help us predict how vaccine scares might unfold and assist mitigation efforts.
Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.
Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373
Grunspan, Daniel Z; Nesse, Randolph M; Barnes, M Elizabeth; Brownell, Sara E
Evolutionary medicine is a rapidly growing field that uses the principles of evolutionary biology to better understand, prevent and treat disease, and that uses studies of disease to advance basic knowledge in evolutionary biology. Over-arching principles of evolutionary medicine have been described in publications, but our study is the first to systematically elicit core principles from a diverse panel of experts in evolutionary medicine. These principles should be useful to advance recent recommendations made by The Association of American Medical Colleges and the Howard Hughes Medical Institute to make evolutionary thinking a core competency for pre-medical education. The Delphi method was used to elicit and validate a list of core principles for evolutionary medicine. The study included four surveys administered in sequence to 56 expert panelists. The initial open-ended survey created a list of possible core principles; the three subsequent surveys winnowed the list and assessed the accuracy and importance of each principle. Fourteen core principles elicited at least 80% of the panelists to agree or strongly agree that they were important core principles for evolutionary medicine. These principles over-lapped with concepts discussed in other articles discussing key concepts in evolutionary medicine. This set of core principles will be helpful for researchers and instructors in evolutionary medicine. We recommend that evolutionary medicine instructors use the list of core principles to construct learning goals. Evolutionary medicine is a young field, so this list of core principles will likely change as the field develops further.
Levit, Georgy S; Hossfeld, Uwe; Olsson, Lennart
Ivan I. Schmalhausen was one of the central figures in the Russian development of the "Modern Synthesis" in evolutionary biology. He is widely cited internationally even today. Schmalhausen developed the main principles of his theory facing the danger of death in the totalitarian Soviet Union. His great services to evolutionary and theoretical biology are indisputable. However, the received view of Schmalhausen's contributions to evolutionary biology makes an unbiased reading of his texts difficult. Here we show that taking all of his works into consideration (including those only available in Russian) paints a much more dynamic and exciting picture of what he tried to achieve. Schmalhausen pioneered the integration of a developmental perspective into evolutionary thinking. A main tool for achieving this was his approach to living objects as complex multi-level self-regulating systems. Schmalhausen put enormous effort into bringing this idea into fruition during the final stages of his career by combining evolutionary theory with cybernetics. His results and ideas remain thought-provoking, and his texts are of more than just historical interest. Copyright 2006 Wiley-Liss, Inc.
I reflect on my fifty-year history as a philosopher of biology, showing how it has taken me from rather narrow analytic studies, through the history of ideas, and now on to issues to do with science and religion. I argue that moral concerns were and still are a major motivation behind what I do and write. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.
Full Text Available Much of the philosophical attention directed to Kant’s intervention into biology has been directed toward Kant’s idea of a transcendental limit upon what can be understood constitutively. Kant’s own wider philosophical practice, however, was principally oriented toward solving problems and the scientific benefits of his methodology of teleology have been largely underappreciated, at least in the English language literature. This paper suggests that all basic biology has had, and continues to have, a need for some form of heuristic “bracketing” and that a renewal of some form of, albeit flexible, teleological methodological bracketing can better complement the productive assimilation into developmental biology of continuing advances in our understanding of the mesoscale physics and chemistry of soft, excitable condensed matter, than what has been the prevailing and de facto use of a form of bracketing shaped by the neoDarwinian Modern Synthesis. Further we offer a concept of biogeneric processes and a framework of physico-genetic “dynamical patterning modules”, that can begin to account for the appearance of new Kantian “stocks of Keime und Anlagen”, capable of potentiating some range of possible organismal forms, and provide grounds for moving up the teleological “goalposts”, i.e., expanding the range of what can be accounted for on a constitutive basis.
Tsai, Kuan-Yao; Wang, Feng-Sheng
Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.
Fritzsch, B.; Beisel, K. W.; Bermingham, N. A.
This brief overview shows that a start has been made to molecularly dissect vertebrate ear development and its evolutionary conservation to the development of the insect hearing organ. However, neither the patterning process of the ear nor the patterning process of insect sensory organs is sufficiently known at the moment to provide more than a first glimpse. Moreover, hardly anything is known about otocyst development of the cephalopod molluscs, another triploblast lineage that evolved complex 'ears'. We hope that the apparent conserved functional and cellular components present in the ciliated sensory neurons/hair cells will also be found in the genes required for vertebrate ear and insect sensory organ morphogenesis (Fig. 3). Likewise, we expect that homologous pre-patterning genes will soon be identified for the non-sensory cell development, which is more than a blocking of neuronal development through the Delta/Notch signaling system. Generation of the apparently unique ear could thus represent a multiplication of non-sensory cells by asymmetric and symmetric divisions as well as modification of existing patterning process by implementing novel developmental modules. In the final analysis, the vertebrate ear may come about by increasing the level of gene interactions in an already existing and highly conserved interactive cascade of bHLH genes. Since this was apparently achieved in all three lineages of triploblasts independently (Fig. 3), we now need to understand how much of the morphogenetic cascades are equally conserved across phyla to generate complex ears. The existing mutations in humans and mice may be able to point the direction of future research to understand the development of specific cell types and morphologies in the formation of complex arthropod, cephalopod, and vertebrate 'ears'.
Christy Anna Hipsley
Full Text Available Molecular-based divergence dating methods, or molecular clocks, are the primary neontological tool for estimating the temporal origins of clades. While the appropriate use of vertebrate fossils as external clock calibrations has stimulated heated discussions in the paleontological community, less attention has been given to the quality and implementation of other calibration types. In lieu of appropriate fossils, many studies rely on alternative sources of age constraints based on geological events, substitution rates and heterochronous sampling, as well as dates secondarily derived from previous analyses. To illustrate the breadth and frequency of calibration types currently employed, we conducted a literature survey of over 600 articles published from 2007 to 2013. Over half of all analyses implemented one or more fossil dates as constraints, followed by geological events and secondary calibrations (15% each. Vertebrate taxa were subjects of nearly half of all studies, while invertebrates and plants together accounted for 43%, followed by viruses, protists and fungi (3% each. Current patterns in calibration practices were disproportionate to the number of discussions on their proper use, particularly regarding plants and secondarily derived dates, which are both relatively neglected. Based on our survey, we provide a comprehensive overview of the latest approaches in clock calibration, and outline strengths and weaknesses associated with each. This critique should serve as a call to action for researchers across multiple communities, particularly those working on clades for which fossil records are poor, to develop their own guidelines regarding selection and implementation of alternative calibration types. This issue is particularly relevant now, as time-calibrated phylogenies are used for more than dating evolutionary origins, but often serve as the backbone of investigations into biogeography, diversity dynamics and rates of phenotypic
Novick, Laura R; Catley, Kefyn M
The ability to interpret and reason from Tree of Life (ToL) diagrams has become a vital component of science literacy in the 21st century. This article reports on the effectiveness of a research-based curriculum, including an instructional booklet, laboratory, and lectures, to teach the fundamentals of such tree thinking in an introductory biology class for science majors. We present the results of a study involving 117 undergraduates who received either our new research-based tree-thinking curriculum or business-as-usual instruction. We found greater gains in tree-thinking abilities for the experimental instruction group than for the business-as-usual group, as measured by performance on our novel assessment instrument. This was a medium size effect. These gains were observed on an unannounced test that was administered ∼5-6 weeks after the primary instruction in tree thinking. The nature of students' postinstruction difficulties with tree thinking suggests that the critical underlying concept for acquiring expert-level competence in this area is understanding that any specific phylogenetic tree is a subset of the complete, unimaginably large ToL. © 2016 L. R. Novick and K. M. Catley. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Lehmann, Torsten; Woodburn, Robin
Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the `biologically-inspired' approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks. We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...
RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp.
Smith, James J.; Cheruvelil, Kendra Spence; Auvenshine, Stacie
Phylogenetic trees provide visual representations of ancestor-descendant relationships, a core concept of evolutionary theory. We introduced "tree thinking" into our introductory organismal biology course (freshman/sophomore majors) to help teach organismal diversity within an evolutionary framework. Our instructional strategy consisted…
Nash, Ulrik William
, they are correlated among people who share environments because these individuals satisfice within their cognitive bounds by using cues in order of validity, as opposed to using cues arbitrarily. Any difference in expectations thereby arise from differences in cognitive ability, because two individuals with identical...... cognitive bounds will perceive business opportunities identically. In addition, because cues provide information about latent causal structures of the environment, changes in causality must be accompanied by changes in cognitive representations if adaptation is to be maintained. The concept of evolutionary......The concept of evolutionary expectations descends from cue learning psychology, synthesizing ideas on rational expectations with ideas on bounded rationality, to provide support for these ideas simultaneously. Evolutionary expectations are rational, but within cognitive bounds. Moreover...
Gardner, Joel; Belland, Brian R.
Introductory biology courses form a cornerstone of undergraduate instruction. However, the predominantly used lecture approach fails to produce higher-order biology learning. Research shows that active learning strategies can increase student learning, yet few biology instructors use all identified active learning strategies. In this paper, we…
The purpose of this study was to compare between learning sexually transmitted infections in Biology by observation and traditional classroom lecture method ... The study found that observational method was more effective and preferred by students as compared to traditional lecture method ... AJOL African Journals Online.
Chung, Ain; Barot, Sabiha K.; Kim, Jeansok J.; Bernstein, Ilene L.
Modern views on learning and memory accept the notion of biological constraints--that the formation of association is not uniform across all stimuli. Yet cellular evidence of the encoding of selective associations is lacking. Here, conditioned stimuli (CSs) and unconditioned stimuli (USs) commonly employed in two basic associative learning…
Kragten, M.; Admiraal, W.; Rijlaarsdam, G.
Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students’ learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems—patient classification, fundamental biological processes and treatment of patients—and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine. PMID:29618526
Ching, Travers; Himmelstein, Daniel S; Beaulieu-Jones, Brett K; Kalinin, Alexandr A; Do, Brian T; Way, Gregory P; Ferrero, Enrico; Agapow, Paul-Michael; Zietz, Michael; Hoffman, Michael M; Xie, Wei; Rosen, Gail L; Lengerich, Benjamin J; Israeli, Johnny; Lanchantin, Jack; Woloszynek, Stephen; Carpenter, Anne E; Shrikumar, Avanti; Xu, Jinbo; Cofer, Evan M; Lavender, Christopher A; Turaga, Srinivas C; Alexandari, Amr M; Lu, Zhiyong; Harris, David J; DeCaprio, Dave; Qi, Yanjun; Kundaje, Anshul; Peng, Yifan; Wiley, Laura K; Segler, Marwin H S; Boca, Simina M; Swamidass, S Joshua; Huang, Austin; Gitter, Anthony; Greene, Casey S
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine. © 2018 The Authors.
Cortese-Krott, Miriam M; Koning, Anne; Kuhnle, Gunter G C; Nagy, Peter; Bianco, Christopher L; Pasch, Andreas; Wink, David A; Fukuto, Jon M; Jackson, Alan A; van Goor, Harry; Olson, Kenneth R; Feelisch, Martin
Oxidative stress is thought to account for aberrant redox homeostasis and contribute to aging and disease. However, more often than not, administration of antioxidants is ineffective, suggesting that our current understanding of the underlying regulatory processes is incomplete. Recent Advances: Similar to reactive oxygen species and reactive nitrogen species, reactive sulfur species are now emerging as important signaling molecules, targeting regulatory cysteine redox switches in proteins, affecting gene regulation, ion transport, intermediary metabolism, and mitochondrial function. To rationalize the complexity of chemical interactions of reactive species with themselves and their targets and help define their role in systemic metabolic control, we here introduce a novel integrative concept defined as the reactive species interactome (RSI). The RSI is a primeval multilevel redox regulatory system whose architecture, together with the physicochemical characteristics of its constituents, allows efficient sensing and rapid adaptation to environmental changes and various other stressors to enhance fitness and resilience at the local and whole-organism level. To better characterize the RSI-related processes that determine fluxes through specific pathways and enable integration, it is necessary to disentangle the chemical biology and activity of reactive species (including precursors and reaction products), their targets, communication systems, and effects on cellular, organ, and whole-organism bioenergetics using system-level/network analyses. Understanding the mechanisms through which the RSI operates will enable a better appreciation of the possibilities to modulate the entire biological system; moreover, unveiling molecular signatures that characterize specific environmental challenges or other forms of stress will provide new prevention/intervention opportunities for personalized medicine. Antioxid. Redox Signal. 00, 000-000.
Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. email@example.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge.We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of SemanticWeb based knowledge bases in biology to use in machine learning and data analytics.https://firstname.lastname@example.org.Supplementary data are available at Bioinformatics online.
Shcherbakov Victor P
Full Text Available Abstract Consistent holistic view of sexual species as the highest form of biological existence is presented. The Weismann's idea that sex and recombination provide the variation for the natural selection to act upon is dominated in most discussions of the biological meaning of the sexual reproduction. Here, the idea is substantiated that the main advantage of sex is the opposite: the ability to counteract not only extinction but further evolution as well. Living systems live long owing to their ability to reproduce themselves with a high fidelity. Simple organisms (like bacteria reach the continued existence due to the high fidelity of individual genome replication. In organisms with a large genome and complex development, the achievable fidelity of DNA replication is not enough for the precise reproduction of the genome. Such species must be capable of surviving and must remain unchanged in spite of the continuous changes of their genes. This problem has no solution in the frame of asexual ("homeogenomic" lineages. They would rapidly degrade and become extinct or blurred out in the course of the reckless evolution. The core outcome of the transition to sexual reproduction was the creation of multiorganismic entity - biological species. Individual organisms forfeited their ability to reproduce autonomously. It implies that individual organisms forfeited their ability to substantive evolution. They evolve as a part of the biological species. In case of obligatory sexuality, there is no such a thing as synchronic multi-level selection. Natural selection cannot select anything that is not a unit of reproduction. Hierarchy in biology implies the functional predestination of the parts for the sake of the whole. A crucial feature of the sexual reproduction is the formation of genomes of individual organisms by random picking them over from the continuously shuffled gene pool instead of the direct replication of the ancestor's genome. A clear anti-evolutionary
Tsaushu, Masha; Tal, Tali; Sagy, Ornit; Kali, Yael; Gepstein, Shimon; Zilberstein, Dan
This study offers an innovative and sustainable instructional model for an introductory undergraduate course. The model was gradually implemented during 3 yr in a research university in a large-lecture biology course that enrolled biology majors and nonmajors. It gives priority to sources not used enough to enhance active learning in higher…
Armstrong, Norris; Chang, Shu-Mei; Brickman, Marguerite
This study examined the impact of cooperative learning activities on student achievement and attitudes in large-enrollment (>250) introductory biology classes. We found that students taught using a cooperative learning approach showed greater improvement in their knowledge of course material compared with students taught using a traditional lecture format. In addition, students viewed cooperative learning activities highly favorably. These findings suggest that encouraging students to work in small groups and improving feedback between the instructor and the students can help to improve student outcomes even in very large classes. These results should be viewed cautiously, however, until this experiment can be replicated with additional faculty. Strategies for potentially improving the impact of cooperative learning on student achievement in large courses are discussed.
Millions of children visit zoos every year with parents or schools to encounter wildlife firsthand. Public conservation education is a requirement for membership in professional zoo associations. However, in recent years zoos have been criticized for failing to educate the public on conservation issues and related biological concepts, such as animal adaptation to habitats. I used matched pre- and postvisit mixed methods questionnaires to investigate the educational value of zoo visits for children aged 7-15 years. The questionnaires gathered qualitative data from these individuals, including zoo-related thoughts and an annotated drawing of a habitat. A content analysis of these qualitative data produced the quantitative data reported in this article. I evaluated the relative learning outcomes of educator-guided and unguided zoo visits at London Zoo, both in terms of learning about conservation biology (measured by annotated drawings) and changing attitudes toward wildlife conservation (measured using thought-listing data). Forty-one percent of educator-guided visits and 34% of unguided visits resulted in conservation biology-related learning. Negative changes in children's understanding of animals and their habitats were more prevalent in unguided zoo visits. Overall, my results show the potential educational value of visiting zoos for children. However, they also suggest that zoos' standard unguided interpretive materials are insufficient for achieving the best outcomes for visiting children. These results support a theoretical model of conservation biology learning that frames conservation educators as toolmakers who develop conceptual resources to enhance children's understanding of science. © 2014 Society for Conservation Biology.
The study of language knowledge guided by a purely biological perspective prioritizes the study of syntax. The essential process of syntax is recursion--the ability to generate an infinite array of expressions from a limited set of elements. Researchers working within the biological perspective argue that this ability is possible only because of an innately specified genetic makeup that is specific to human beings. Such a view of language knowledge may be fully justified in discussions on biolinguistics, and in evolutionary biology. However, it is grossly inadequate in understanding language-learning problems, particularly those experienced by children with neurodevelopmental disorders such as developmental dyslexia, Williams syndrome, specific language impairment and autism spectrum disorders. Specifically, syntax-centered definitions of language knowledge completely ignore certain crucial aspects of language learning and use, namely, that language is embedded in a social context; that the role of envrironmental triggering as a learning mechanism is grossly underestimated; that a considerable extent of visuo-spatial information accompanies speech in day-to-day communication; that the developmental process itself lies at the heart of knowledge acquisition; and that there is a tremendous variation in the orthographic systems associated with different languages. All these (socio-cultural) factors can influence the rate and quality of spoken and written language acquisition resulting in much variation in phenotypes associated with disorders known to have a genetic component. Delineation of such phenotypic variability requires inputs from varied disciplines such as neurobiology, neuropsychology, linguistics and communication disorders. In this paper, I discuss published research that questions cognitive modularity and emphasises the role of the environment for understanding linguistic capabilities of children with neuro-developmental disorders. The discussion pertains
Tsaushu, Masha; Tal, Tali; Sagy, Ornit; Kali, Yael; Gepstein, Shimon; Zilberstein, Dan
This study offers an innovative and sustainable instructional model for an introductory undergraduate course. The model was gradually implemented during 3 yr in a research university in a large-lecture biology course that enrolled biology majors and nonmajors. It gives priority to sources not used enough to enhance active learning in higher education: technology and the students themselves. Most of the lectures were replaced with continuous individual learning and 1-mo group learning of one topic, both supported by an interactive online tutorial. Assessment included open-ended complex questions requiring higher-order thinking skills that were added to the traditional multiple-choice (MC) exam. Analysis of students’ outcomes indicates no significant difference among the three intervention versions in the MC questions of the exam, while students who took part in active-learning groups at the advanced version of the model had significantly higher scores in the more demanding open-ended questions compared with their counterparts. We believe that social-constructivist learning of one topic during 1 mo has significantly contributed to student deep learning across topics. It developed a biological discourse, which is more typical to advanced stages of learning biology, and changed the image of instructors from “knowledge transmitters” to “role model scientists.” PMID:23222836
Tsaushu, Masha; Tal, Tali; Sagy, Ornit; Kali, Yael; Gepstein, Shimon; Zilberstein, Dan
This study offers an innovative and sustainable instructional model for an introductory undergraduate course. The model was gradually implemented during 3 yr in a research university in a large-lecture biology course that enrolled biology majors and nonmajors. It gives priority to sources not used enough to enhance active learning in higher education: technology and the students themselves. Most of the lectures were replaced with continuous individual learning and 1-mo group learning of one topic, both supported by an interactive online tutorial. Assessment included open-ended complex questions requiring higher-order thinking skills that were added to the traditional multiple-choice (MC) exam. Analysis of students' outcomes indicates no significant difference among the three intervention versions in the MC questions of the exam, while students who took part in active-learning groups at the advanced version of the model had significantly higher scores in the more demanding open-ended questions compared with their counterparts. We believe that social-constructivist learning of one topic during 1 mo has significantly contributed to student deep learning across topics. It developed a biological discourse, which is more typical to advanced stages of learning biology, and changed the image of instructors from "knowledge transmitters" to "role model scientists."
Nesse, Randolph M; Ganten, Detlev; Gregory, T Ryan; Omenn, Gilbert S
Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.
Kleshnina, Maria; Filar, Jerzy A; Ejov, Vladimir; McKerral, Jody C
The adaptation process of a species to a new environment is a significant area of study in biology. As part of natural selection, adaptation is a mutation process which improves survival skills and reproductive functions of species. Here, we investigate this process by combining the idea of incompetence with evolutionary game theory. In the sense of evolution, incompetence and training can be interpreted as a special learning process. With focus on the social side of the problem, we analyze the influence of incompetence on behavior of species. We introduce an incompetence parameter into a learning function in a single-population game and analyze its effect on the outcome of the replicator dynamics. Incompetence can change the outcome of the game and its dynamics, indicating its significance within what are inherently imperfect natural systems.
Full Text Available The study is aimed at finding an effective learning strategy that can increase metacognitive knowledge. Metacognitive knowledge is a standard that based on 2016-revised edition of 2013 curriculum needs to be achieved by every graduate in all level of education in Indonesia. The study is conducted in three different schools and engages 207 students, which then divided into six groups. The groups are students who study under mind mapping strategy, concept mapping, reciprocal teaching using summary notes, reciprocal teaching using mind mapping, problem-based learning, and investigation group. The results showed that those studying under problem-based learning strategy spent a significantly higher numbers in metacognitive knowledge in biology learning and followed by students who study under reciprocal teaching using mind mapping. According to the finding, it is expected that teachers of Biology will practice problem-based learning strategy in their classroom in order to increase the Metacognitive knowledge.
Full Text Available The study was to develop a Biology learning evaluation model in senior high schools that referred to the research and development model by Borg & Gall and the logic model. The evaluation model included the components of input, activities, output and outcomes. The developing procedures involved a preliminary study in the form of observation and theoretical review regarding the Biology learning evaluation in senior high schools. The product development was carried out by designing an evaluation model, designing an instrument, performing instrument experiment and performing implementation. The instrument experiment involved teachers and Students from Grade XII in senior high schools located in the City of Yogyakarta. For the data gathering technique and instrument, the researchers implemented observation sheet, questionnaire and test. The questionnaire was applied in order to attain information regarding teacher performance, learning performance, classroom atmosphere and scientific attitude; on the other hand, test was applied in order to attain information regarding Biology concept mastery. Then, for the analysis of instrument construct, the researchers performed confirmatory factor analysis by means of Lisrel 0.80 software and the results of this analysis showed that the evaluation instrument valid and reliable. The construct validity was between 0.43-0.79 while the reliability of measurement model was between 0.88-0.94. Last but not the least, the model feasibility test showed that the theoretical model had been supported by the empirical data.
Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang
Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.
Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia
Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human biological systems. Two hundred and forty-two children were given pretests at a Museum and posttests at home after playing either a treatment or control game. Also, 41 children were interviewed to explore deeper meanings behind the test results. Results show modest improvement in scientific attitudes, ability to identify human biological systems and in the children's ability to describe how those systems work together in real-world scenarios. Interviews reveal that children drew upon their prior school learning as they played the game. Also, on the surface they perceived the game as mainly entertainment but were easily able to discern learning outcomes when prompted. Implications for the design of casual games and how they can be used to enhance transfer of knowledge from the classroom to everyday life are discussed.
Wright, Robin; Boggs, James
To help students develop successful strategies for learning how to learn and communicate complex information in cell biology, we developed a quarter-long cell biology class based on team projects. Each team researches a particular human disease and presents information about the cellular structure or process affected by the disease, the cellular…
Shimansky, Yury P
Learning ability is a vitally important, distinctive property of biological systems, which provides dynamic stability in non-stationary environments. Although several different types of learning have been successfully modeled using a universal computer, in general, learning cannot be described by an algorithm. In other words, algorithmic approach to describing the functioning of biological systems is not sufficient for adequate grasping of what is life. Since biosystems are parts of the physical world, one might hope that adding some physical mechanisms and principles to the concept of algorithm could provide extra possibilities for describing learning in its full generality. However, a straightforward approach to that through the so-called physical hypercomputation so far has not been successful. Here an alternative approach is proposed. Biosystems are described as achieving enumeration of possible physical compositions though random incremental modifications inflicted on them by active operating resources (AORs) in the environment. Biosystems learn through algorithmic regulation of the intensity of the above modifications according to a specific optimality criterion. From the perspective of external observers, biosystems move in the space of different algorithms driven by random modifications imposed by the environmental AORs. A particular algorithm is only a snapshot of that motion, while the motion itself is essentially trans-algorithmic. In this conceptual framework, death of unfit members of a population, for example, is viewed as a trans-algorithmic modification made in the population as a biosystem by environmental AORs. Numerous examples of AOR utilization in biosystems of different complexity, from viruses to multicellular organisms, are provided.
Sear, Rebecca; Lawson, David W; Kaplan, Hillard; Shenk, Mary K
Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. © 2016 The Author(s).
P.A.N. Bosman (Peter); J.A. La Poutré (Han); D. Thierens (Dirk)
htmlabstractThe focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, the EA must not only be capable of tracking shifting optima, it must also take into account the future
The aims of the study were to investigate (a) the relationship between the attitudes toward biology and perceptions of the biology learning environment among grade 11 students in Tulkarm District, Palestine and (b) the effect of gender and residence of these students on their attitudes toward biology and on their perceptions of the biology…
Schrein, Caitlin M.
In the United States, there is a national agenda to increase the number of qualified science, technology, engineering, and maths (STEM) professionals and a movement to promote science literacy among the general public. This project explores the association between formal human evolutionary biology education (HEB) and high school science class enrollment, academic achievement, interest in a STEM degree program, motivation to pursue a STEM career, and socioscientific decision-making for a sample of students enrolled full-time at Arizona State University. Given a lack of a priori knowledge of these relationships, the Grounded Theory Method was used and was the foundation for a mixed-methods analysis involving qualitative and quantitative data from one-on-one interviews, focus groups, questionnaires, and an online survey. Theory development and hypothesis generation were based on data from 44 students. The survey instrument, developed to test the hypotheses, was completed by 486 undergraduates, age 18--22, who graduated from U.S. public high schools. The results showed that higher exposure to HEB was correlated with greater high school science class enrollment, particularly for advanced biological science classes, and that, for some students, HEB exposure may have influenced their enrollment, because the students found the content interesting and relevant. The results also suggested that students with higher K--12 HEB exposure felt more prepared for undergraduate science coursework. There was a positive correlation between HEB exposure and interest in a STEM degree and an indirect relationship between higher HEB exposure and motivation to pursue a STEM career. Regarding a number of socioscientific issues, including but not limited to climate change, homosexuality, and stem cell research, students' behaviors and decision-making more closely reflected a scientific viewpoint---or less-closely aligned to a religion-based perspective---when students had greater HEB exposure
Baldi, P. [California Inst. of Tech., Pasadena, CA (United States)
This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In this tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.
Gorunescu, Florin; Belciug, Smaranda
The purpose of this paper is twofold: first, to propose an evolutionary-based method for building a decision model and, second, to assess and validate the model's performance using five different real-world medical datasets (breast cancer and liver fibrosis) by comparing it with state-of-the-art machine learning techniques. The evolutionary-inspired approach has been used to develop the learning-based decision model in the following manner: the hybridization of algorithms has been considered as "crossover", while the development of new variants which can be thought of as "mutation". An appropriate hierarchy of the component algorithms was established based on a statistically built fitness measure. A synergetic decision-making process, based on a weighted voting system, involved the collaboration between the selected algorithms in making the final decision. Well-established statistical performance measures and comparison tests have been extensively used to design and implement the model. Finally, the proposed method has been tested on five medical datasets, out of which four publicly available, and contrasted with state-of-the-art techniques, showing its efficiency in supporting the medical decision-making process. Copyright © 2014 Elsevier Inc. All rights reserved.
Nesse, Randolph M.; Ganten, Detlev; Gregory, T. Ryan; Omenn, Gilbert S.
Evolution has long provided a foundation for population genetics, but many major advances in evolutionary biology from the 20th century are only now being applied in molecular medicine. They include the distinction between proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are further transforming evolutionary biology and creating yet more opportunities for progress at the interface of evolution with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and others to speed the development of evolutionary molecular medicine. PMID:22544168
Auerbach, Anna Jo; Schussler, Elisabeth E.
Active learning (or learner-centered) pedagogies have been shown to enhance student learning in introductory biology courses. Student collaboration has also been shown to enhance student learning and may be a critical part of effective active learning practices. This study focused on documenting the use of individual active learning and group…
Neroni, Joyce; Gijselaers, Jérôme; Kirschner, Paul A.; De Groot, Renate
Learning is crucial for everyone. The association between biological (eg, sleep, nutrition) and psychological factors (eg, test anxiety, goal orientation) and learning performance has been well established for children, adolescents and college students in traditional education. Evidence for these
Full Text Available Recent progress made on epigenetic studies revealed the conservation of epigenetic features in deep diverse branching species including Stramenopiles, plants and animals. This suggests their fundamental role in shaping species genomes across different evolutionary time scales. Diatoms are a highly successful and diverse group of phytoplankton with a fossil record of about 190 million years ago. They are distantly related from other super-groups of Eukaryotes and have retained some of the epigenetic features found in mammals and plants suggesting their ancient origin. Phaeodactylum tricornutum and Thalassiosira pseudonana, pennate and centric diatoms, respectively, emerged as model species to address questions on the evolution of epigenetic phenomena such as what has been lost, retained or has evolved in contemporary species. In the present work, we will discuss how the study of non-model or emerging model organisms, such as diatoms, helps understand the evolutionary history of epigenetic mechanisms with a particular focus on DNA methylation and histone modifications.
Fürstenberg, Dr Kai
Institutions are hard to define and hard to study. Long prominent in political science have been two theories: Rational Choice Institutionalism (RCI) and Historical Institutionalism (HI). Arising from the life sciences is now a third: Evolutionary Institutionalism (EI). Comparative strengths and weaknesses of these three theories warrant review, and the value-to-be-added by expanding the third beyond Darwinian evolutionary theory deserves consideration. Should evolutionary institutionalism expand to accommodate new understanding in ecology, such as might apply to the emergence of stability, and in genetics, such as might apply to political behavior? Core arguments are reviewed for each theory with more detailed exposition of the third, EI. Particular attention is paid to EI's gene-institution analogy; to variation, selection, and retention of institutional traits; to endogeneity and exogeneity; to agency and structure; and to ecosystem effects, institutional stability, and empirical limitations in behavioral genetics. RCI, HI, and EI are distinct but complementary. Institutional change, while amenable to rational-choice analysis and, retrospectively, to criticaljuncture and path-dependency analysis, is also, and importantly, ecological. Stability, like change, is an emergent property of institutions, which tend to stabilize after change in a manner analogous to allopatric speciation. EI is more than metaphorically biological in that institutional behaviors are driven by human behaviors whose evolution long preceded the appearance of institutions themselves.
Arnold, M L; Ballerini, E S; Brothers, A N
Estimates of hybrid fitness have been used as either a platform for testing the potential role of natural hybridization in the evolution of species and species complexes or, alternatively, as a rationale for dismissing hybridization events as being of any evolutionary significance. From the time of Darwin's publication of The Origin, through the neo-Darwinian synthesis, to the present day, the observation of variability in hybrid fitness has remained a challenge for some models of speciation. Yet, Darwin and others have reported the elevated fitness of hybrid genotypes under certain environmental conditions. In modern scientific terminology, this observation reflects the fact that hybrid genotypes can demonstrate genotype × environment interactions. In the current review, we illustrate the development of one plant species complex, namely the Louisiana Irises, into a 'model system' for investigating hybrid fitness and the role of genetic exchange in adaptive evolution and diversification. In particular, we will argue that a multitude of approaches, involving both experimental and natural environments, and incorporating both manipulative analyses and surveys of natural populations, are necessary to adequately test for the evolutionary significance of introgressive hybridization. An appreciation of the variability of hybrid fitness leads to the conclusion that certain genetic signatures reflect adaptive evolution. Furthermore, tests of the frequency of allopatric versus sympatric/parapatric divergence (that is, divergence with ongoing gene flow) support hybrid genotypes as a mechanism of evolutionary diversification in numerous species complexes.
Conner, Lindsey; Gunstone, Richard
This paper reports on a qualitative case study investigation of the knowledge and use of learning strategies by 16 students in a final year high school biology class to expand their conscious knowledge of learning. Students were provided with opportunities to engage in purposeful inquiry into the biological, social and ethical aspects of cancer. A constructivist approach was implemented to access prior content and procedural knowledge in various ways. Students were encouraged to develop evaluation of their learning skills independently through activities that promoted metacognition. Those students who planned and monitored their work produced essays of higher quality. The value and difficulties of promoting metacognitive approaches in this context are discussed, as well as the idea that metacognitive processes are difficult to research, because they have to be conscious in order to be identified by the learner, thereby making them accessible to the researcher.
Bean, Thomas E.; Sinatra, Gale M.; Schrader, P. G.
The use of computer simulations as educational tools may afford the means to develop understanding of evolution as a natural, emergent, and decentralized process. However, special consideration of developmental constraints on learning may be necessary when using these technologies. Specifically, the essentialist (biological forms possess an immutable essence), teleological (assignment of purpose to living things and/or parts of living things that may not be purposeful), and intentionality (assumption that events are caused by an intelligent agent) biases may be reinforced through the use of computer simulations, rather than addressed with instruction. We examine the video game Spore for its depiction of evolutionary content and its potential to reinforce these cognitive biases. In particular, we discuss three pedagogical strategies to mitigate weaknesses of Spore and other computer simulations: directly targeting misconceptions through refutational approaches, targeting specific principles of scientific inquiry, and directly addressing issues related to models as cognitive tools.
Biology Seminar is a course in Biology Education Study Program of Faculty of Teacher Training and Education University of Maritim Raja Ali Haji (FKIP UMRAH) that requires students to have the ability to apply scientific attitudes, perform scientific writing and undertake scientific publications on a small scale. One of the learning strategies that can drive the achievement of learning outcomes in this course is Research-Based Learning. Research-Based Learning principles are considered in accordance with learning outcomes in Biology Seminar courses and generally in accordance with the purpose of higher education. On this basis, this article which is derived from a qualitative research aims at describing Research-based Learning on Biology Seminar course. Based on a case study research, it was known that Research-Based Learning on Biology Seminar courses is applied through: designing learning activities around contemporary research issues; teaching research methods, techniques and skills explicitly within program; drawing on personal research in designing and teaching courses; building small-scale research activities into undergraduate assignment; and infusing teaching with the values of researchers.
Schlaepfer, Martin A.; Sherman, P.W.; Blossey, B.; Runge, M.C.
Invasive species can alter environments in such a way that normal behavioural decision-making rules of native species are no longer adaptive. The evolutionary trap concept provides a useful framework for predicting and managing the impact of harmful invasive species. We discuss how native species can respond to changes in their selective regime via evolution or learning. We also propose novel management strategies to promote the long-term co-existence of native and introduced species in cases where the eradication of the latter is either economically or biologically unrealistic.
Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain – at least to some extent. Therefore three suitable machine learning algorithms are selected – algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the...
Monje, Francisco J; Divisch, Isabella; Demit, Marvie; Lubec, Gert; Pollak, Daniela D
Studies of synaptic plasticity using the marine mollusk Aplysia californica as model system have been successfully used to identify proteins involved in learning and memory. The importance of molecular elements regulated by the learning- related neurotransmitter serotonin in Aplysia can then be explored in rodent models and finally tested for their relevance for human physiology and pathology. Herein, 2-DE gel-based electrophoresis has been used to investigate protein level changes after treatment with serotonin in Aplysia abdominal ganglia. Twenty-one proteins have been found to be regulated by serotonin, and protein level changes of actin depolymerizing factor (ADF), deleted in azoospermia associated protein (DAZAP-1), and Flotillin-1 have been verified by Western blotting. Flotillin-1, a member of the flotillin/reggie family of scaffolding proteins, has been previously found to be involved in neuritic branching and synapse formation in hippocampal neurons in vitro. However, its importance for hippocampal- dependent learning and memory in the mouse has not been examined. Here, elevated levels of Flotillin-1 in hippocampal tissue of mice trained in the Morris water maze confirmed the relevance of Flotillin-1 for memory-related processes in a mammalian system. Thus, a translational approach-from invertebrates to rodents-led to the identification of Flotillin-1 as evolutionary-conserved memory-related protein.
Wass, Christopher; Denman-Brice, Alexander; Rios, Chris; Light, Kenneth R; Kolata, Stefan; Smith, Andrew M; Matzel, Louis D
Contemporary descriptions of human intelligence hold that this trait influences a broad range of cognitive abilities, including learning, attention, and reasoning. Like humans, individual genetically heterogeneous mice express a "general" cognitive trait that influences performance across a diverse array of learning and attentional tasks, and it has been suggested that this trait is qualitatively and structurally analogous to general intelligence in humans. However, the hallmark of human intelligence is the ability to use various forms of "reasoning" to support solutions to novel problems. Here, we find that genetically heterogeneous mice are capable of solving problems that are nominally indicative of inductive and deductive forms of reasoning, and that individuals' capacity for reasoning covaries with more general learning abilities. Mice were characterized for their general learning ability as determined by their aggregate performance (derived from principal component analysis) across a battery of five diverse learning tasks. These animals were then assessed on prototypic tests indicative of deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping") and inductive reasoning (execution of an efficient search strategy in a binary decision tree). The animals exhibited systematic abilities on each of these nominal reasoning tasks that were predicted by their aggregate performance on the battery of learning tasks. These results suggest that the coregulation of reasoning and general learning performance in genetically heterogeneous mice form a core cognitive trait that is analogous to human intelligence. (c) 2012 APA, all rights reserved.
The purpose of this study is to examine motivation of science high school students towards learning biology and their attitude towards biology lessons. The sample of the study consists of 564 high school students (308 females, 256 males) studying at two science high schools in Aksaray, Turkey. In the study, the relational scanning method, which is…
Diogo, Rui; Ziermann, Janine M; Linde-Medina, Marta
, or the strepsirrhines and lemurs within the Primates, for instance. This review will contribute to improving our understanding of these broad evolutionary issues and of the evolution of the vertebrate Bauplans, and hopefully will stimulate future phylogenetic, evolutionary and developmental studies of these clades. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.
Graves, Joseph L; Reiber, Chris; Thanukos, Anna; Hurtado, Magdalena; Wolpaw, Terry
Evolutionary science is indispensable for understanding biological processes. Effective medical treatment must be anchored in sound biology. However, currently the insights available from evolutionary science are not adequately incorporated in either pre-medical or medical school curricula. To illuminate how evolution may be helpful in these areas, examples in which the insights of evolutionary science are already improving medical treatment and ways in which evolutionary reasoning can be practiced in the context of medicine are provided. In order to facilitate the learning of evolutionary principles, concepts derived from evolutionary science that medical students and professionals should understand are outlined. These concepts are designed to be authoritative and at the same time easily accessible for anyone with the general biological knowledge of a first-year medical student. Thus we conclude that medical practice informed by evolutionary principles will be more effective and lead to better patient outcomes.Furthermore, it is argued that evolutionary medicine complements general medical training because it provides an additional means by which medical students can practice the critical thinking skills that will be important in their future practice. We argue that core concepts from evolutionary science have the potential to improve critical thinking and facilitate more effective learning in medical training. © The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.
Evolution as an idea has a lengthy history, even though the idea of evolution is generally associated with Darwin today. Rebecca Stott provides an engaging and thoughtful overview of this history of evolutionary thinking in her 2013 book, Darwin's Ghosts: The Secret History of Evolution. Since Darwin, the debate over evolution-both how it takes place and, in a long war of words with religiously-oriented thinkers, whether it takes place-has been sustained and heated. A growing share of this debate is now devoted to examining how evolutionary thinking affects areas outside of biology. How do our lives change when we recognize that all is in flux? What can we learn about life more generally if we study change instead of stasis? Carter Phipps' book, Evolutionaries: Unlocking the Spiritual and Cultural Potential of Science's Greatest Idea, delves deep into this relatively new development. Phipps generally takes as a given the validity of the Modern Synthesis of evolutionary biology. His story takes us into, as the subtitle suggests, the spiritual and cultural implications of evolutionary thinking. Can religion and evolution be reconciled? Can evolutionary thinking lead to a new type of spirituality? Is our culture already being changed in ways that we don't realize by evolutionary thinking? These are all important questions and Phipps book is a great introduction to this discussion. Phipps is an author, journalist, and contributor to the emerging "integral" or "evolutionary" cultural movement that combines the insights of Integral Philosophy, evolutionary science, developmental psychology, and the social sciences. He has served as the Executive Editor of EnlightenNext magazine (no longer published) and more recently is the co-founder of the Institute for Cultural Evolution, a public policy think tank addressing the cultural roots of America's political challenges. What follows is an email interview with Phipps.
This paper summarizes a "lessons learned" study that reviews DoD's approach to managing the GCCS program on behalf on the Assistant Secretary of Defense for Command, Control, Communications, and Intelligence (ASD/C3I...
Mørch , Anders I.; Engen , Bård Ketil; Hansen Åsand , Hege-René; Brynhildsen , Camilla; Tødenes , Ida
Over a 2-year period, we have participated in the introduction of e-learning in a Norwegian service company, a gas station division of an oil company. This company has an advanced computer network infrastructure for communication and information sharing, but the primary task of the employees is serving customers. We identify some challenges to introducing e-learning in this kind of environment. A primary emphasis has been on using participatory design techniques during the planning stages and...
Horn, Michael S.; Phillips, Brenda C.; Evans, Evelyn Margaret; Block, Florian; Diamond, Judy; Shen, Chia
In this study, we investigate museum visitor learning and engagement at an interactive visualization of an evolutionary tree of life consisting of over 70,000 species. The study was conducted at two natural history museums where visitors collaboratively explored the tree of life using direct touch gestures on a multi-touch tabletop display. In the…
The study investigated the effect of using cooperative learning method on tenth grade students' learning achievement in biology and their attitude towards the subject in a Higher Secondary School in Bhutan. The study used a mixed method approach. The quantitative component included an experimental design where cooperative learning was the…
Acampora, G.; Gaeta, M.; Loia, V.
Recent researches in e-Learning area highlight the need to define novel and advanced support mechanism for commercial and academic organizations in order to enhance the skills of employees and students and, consequently, to increase the overall competitiveness in the new economy world. This is due
De Juan, Joaquin; Pérez-Cañaveras, Rosa M.; Segovia, Yolanda; Girela, Jose Luis; Martínez-Ruiz, Noemi; Romero-Rameta, Alejandro; Gómez-Torres, Maria José; Vizcaya-Moreno, M. Flores
Cell biology is an academic discipline that organises and coordinates the learning of the structure, function and molecular composition of cells in some undergraduate biomedical programs. Besides course content and teaching methodologies, the laboratory environment is considered a key element in the teaching of and learning of cell biology. The…
Zhang, Hai-Feng; Wu, Zhi-Xi; Wang, Bing-Hong
One of the prototypical mechanisms in understanding the ubiquitous cooperation in social dilemma situations is the win–stay, lose–shift rule. In this work, a generalized win–stay, lose–shift learning model—a reinforcement learning model with dynamic aspiration level—is proposed to describe how humans adapt their social behaviors based on their social experiences. In the model, the players incorporate the information of the outcomes in previous rounds with time-dependent aspiration payoffs to regulate the probability of choosing cooperation. By investigating such a reinforcement learning rule in the spatial prisoner's dilemma game and public goods game, a most noteworthy viewpoint is that moderate greediness (i.e. moderate aspiration level) favors best the development and organization of collective cooperation. The generality of this observation is tested against different regulation strengths and different types of network of interaction as well. We also make comparisons with two recently proposed models to highlight the importance of the mechanism of adaptive aspiration level in supporting cooperation in structured populations
Nesse, Randolph M; Stearns, Stephen C
Evolutionary biology is an essential basic science for medicine, but few doctors and medical researchers are familiar with its most relevant principles. Most medical schools have geneticists who understand evolution, but few have even one evolutionary biologist to suggest other possible applications. The canyon between evolutionary biology and medicine is wide. The question is whether they offer each other enough to make bridge building worthwhile. What benefits could be expected if evolution were brought fully to bear on the problems of medicine? How would studying medical problems advance evolutionary research? Do doctors need to learn evolution, or is it valuable mainly for researchers? What practical steps will promote the application of evolutionary biology in the areas of medicine where it offers the most? To address these questions, we review current and potential applications of evolutionary biology to medicine and public health. Some evolutionary technologies, such as population genetics, serial transfer production of live vaccines, and phylogenetic analysis, have been widely applied. Other areas, such as infectious disease and aging research, illustrate the dramatic recent progress made possible by evolutionary insights. In still other areas, such as epidemiology, psychiatry, and understanding the regulation of bodily defenses, applying evolutionary principles remains an open opportunity. In addition to the utility of specific applications, an evolutionary perspective fundamentally challenges the prevalent but fundamentally incorrect metaphor of the body as a machine designed by an engineer. Bodies are vulnerable to disease - and remarkably resilient - precisely because they are not machines built from a plan. They are, instead, bundles of compromises shaped by natural selection in small increments to maximize reproduction, not health. Understanding the body as a product of natural selection, not design, offers new research questions and a framework for
Suwono, Hadi; Wibowo, Agung
Biology learning emphasizes problem-based learning as a learning strategy to develop students ability in identifying and solving problems in the surrounding environment. Problem identification skills are closely correlated with questioning skills. By holding this skill, students tend to deliver a procedural question instead of the descriptive one. Problem-based learning through field investigation is an instruction model which directly exposes the students to problems or phenomena that occur in the environment, and then the students design the field investigation activities to solve these problems. The purpose of this research was to describe the improvement of undergraduate biology students on questioning skills, biological literacy, and academic achievement through problem-based learning through field investigation (PBFI) compared with the lecture-based instruction (LBI). This research was a time series quasi-experimental design. The research was conducted on August - December 2015 and involved 26 undergraduate biology students at the State University of Malang on the Freshwater Ecology course. The data were collected during the learning with LBI and PBFI, in which questioning skills, biological literacy, and academic achievement were collected 3 times in each learning model. The data showed that the procedural correlative and causal types of questions are produced by the students to guide them in conducting investigations and problem-solving in PBFI. The biological literacy and academic achievement of the students at PBFI are significantly higher than those at LBI. The results show that PBFI increases the questioning skill, biological literacy, and the academic achievement of undergraduate biology students.
Koseoglu, Pinar; Efendioglu, Akin
The aim of the present study was to determine the effects of multimedia-based biology teaching (Mbio) and teacher-centered biology (TCbio) instruction approaches on learners' biology achievements, as well as their views towards learning approaches. During the research process, an experimental design with two groups, TCbio (n = 22) and Mbio (n =…
Hallyburton, Chad L.; Lunsford, Eddie
The history of learning biology through distance education is documented. A review of terminology and unique problems associated with biology instruction is presented. Using published research and their own teaching experience, the authors present recommendations and best practices for managing biology in distance-based formats. They offer ideas…
Nogaj, Luiza A.
This article describes the conversion of a lecture-based molecular biology course into an active learning environment in a studio classroom. Specific assignments and activities are provided as examples. The goal of these activities is to involve students in collaborative learning, teach them how to participate in the learning process, and give…
Sletten, Sarah Rae
In flipped classrooms, lectures, which are normally delivered in-class, are assigned as homework in the form of videos, and assignments that were traditionally assigned as homework, are done as learning activities in class. It was hypothesized that the effectiveness of the flipped model hinges on a student's desire and ability to adopt a self-directed learning style. The purpose of this study was twofold; it aimed at examining the relationship between two variables—students' perceptions of the flipped model and their self-regulated learning (SRL) behaviors—and the impact that these variables have on achievement in a flipped class. For the study, 76 participants from a flipped introductory biology course were asked about their SRL strategy use and perceptions of the flipped model. SRL strategy use was measured using a modified version of the Motivated Strategies for Learning Questionnaire (MSLQ; Wolters et al. 2005), while the flipped perceptions survey was newly derived. Student letter grades were collected as a measure of achievement. Through regression analysis, it was found that students' perceptions of the flipped model positively predict students' use of several types of SRL strategies. However, the data did not indicate a relationship between student perceptions and achievement, neither directly nor indirectly, through SRL strategy use. Results suggest that flipped classrooms demonstrate their successes in the active learning sessions through constructivist teaching methods. Video lectures hold an important role in flipped classes, however, students may need to practice SRL skills to become more self-directed and effectively learn from them.
Gokhale, Chaitanya S.; Traulsen, Arne
Evolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g.\\ increase less than linear wi...
Reznikova, Zh I; Panteleeva, S N
There is a plethora of works on the origin and genesis of behavioral traditions in different animal species. Nevertheless, it still remains unclear as for which factors facilitate and which factors hinder the spreading those forms of behavior that are new for a population. Here, we present an analytical review on the topic, considering also the results of studies on 'culture' in animals and analyzing contradictions that arise when attempting to clarify the ethological mechanisms of cultural succession. The hypothesis of 'distributed social learning' is formulated, meaning that for spreading of complex behavioral stereotypes in a population the presence of few carriers of consistent stereotypes is enough under the condition that the rest of animals carry incomplete genetic programmes that start up these stereotypes. Existence of 'dormant' fragments of such programmes determines an inborn predisposition of their bearer to perform a certain sequence of acts. To complete the consistent stereotype, the simplest forms of social learning ('social alleviation') turn to be enough. The hypothesis is examined at the behavioral level and supported by experimental data obtained when studying the scenarios of hunting behavior development in ants Myrmica rubra L. It makes possible to explain the spreading of behavioral models in animal communities in a simpler way than cultural succession.
Lima, Alan M.M. de; Schirru, Roberto
Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for function optimization. The purpose of this work is to introduce a new parallelization method to be applied to the Population-Based Incremental Learning (PBIL) algorithm. PBIL combines standard genetic algorithm mechanisms with simple competitive learning and has ben successfully used in combinatorial optimization problems. The development of this algorithm aims its application to the reload optimization of PWR nuclear reactors. Tests have been performed with combinatorial optimization problems similar to the reload problem. Results are compared to the serial PBIL ones, showing the new method's superiority and its viability as a tool for the nuclear core reload problem solution. (author)
Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping
The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
Andressa, Helen; Mavrikaki, Evangelia; Dermitzaki, Irini
The purpose of this study was to investigate students’ motivation towards biology learning and to determine the factors that are related to it: students’ gender and their parents’ occupation (relevant with biology or not) were investigated. The sample of the study consisted of 360 Greek high school students of the 10th grade (178 boys and 182 girls). The data were collected through Students’ Motivation Toward Science Learning (SMTSL) questionnaire. It was found that it was a valid and reliabl...
Kudish, Philip; Shores, Robin; McClung, Alex; Smulyan, Lisa; Vallen, Elizabeth A.; Siwicki, Kathleen K.
Study group meetings (SGMs) are voluntary-attendance peer-led team-learning workshops that supplement introductory biology lectures at a selective liberal arts college. While supporting all students? engagement with lecture material, specific aims are to improve the success of underrepresented minority (URM) students and those with weaker backgrounds in biology. Peer leaders with experience in biology courses and training in science pedagogy facilitate work on faculty-generated challenge prob...
Santas, Amy J.
Service-learning has become a popular pedagogy because of its numerous and far-reaching benefits (e.g. student interest, engagement, and retention). In part, the benefits are a result of the student learning while providing a service that reflects a true need--not simply an exercise. Although service-learning projects have been developed in the…
Given the problems associated with the traditional lecture method, the constraints associated with large classes, and the effectiveness of active learning, continued development and testing of efficient student-centered learning approaches are needed. This study explores the effectiveness of team-based learning (TBL) in a large-enrollment…
Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing
By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.
Patrick Osawaru Ajaja,
Full Text Available The major purpose of this study was to determine the effects of learning cycle as an instructional strategy on biology andchemistry students achievement. To guide this study, six research hypotheses were stated and tested at 0.05 level ofsignificance. The design of this study was 2x2x3x6 Pre-test Post-test non-equivalent control group quasi experimental design.These included two instructional groups (experimental and control groups, sex (male and female, repeated testing (Pre,Post and follow-up tests, and six weeks of experience. The samples of the study included six senior secondary schools, 112science students, and 12 biology and chemistry teachers. The instruments used for this study were: teacher’s questionnaireon knowledge and use of learning cycle (KULC; and Biology and Chemistry Achievement Test (BCAT. The data collected wereanalyzed with simple percentage, Analysis of Covariance (ANCOVA and student t-test statistics. The major findings of thestudy included that only 30.43% and 26.31% of biology and chemistry teachers have the knowledge that learning cycle is aninstructional method; all the biology and chemistry teachers sampled have never used learning cycle as an instructionalmethod; learning cycle had a significant effect on students achievement in biology and chemistry; students taught withlearning cycle significantly achieved better in biology/chemistry Post-test than those taught with lecture method; the posttestscores of students in the learning cycle group increased over the period of experience; non-significant difference in Posttestscores between males and females taught with learning cycle; non-significant interaction effect between method andsex on achievement; and a significant higher retention of biology and chemistry knowledge by students taught with learningcycle than those taught with lecture method. It was concluded that the method seems an appropriate instructional modelthat could be used to solve the problems of
Bell, Justine C.
To test the claim that digital learning tools enhance the acquisition of visual literacy in this generation of biology students, a learning intervention was carried out with 33 students enrolled in an introductory college biology course. This study compared learning outcomes following two types of learning tools: a traditional drawing activity, or…
This thesis reports on a design research project about a learning, supervising and teaching strategy to enable students in agricultural preparatory vocational secondary education (VMBO) to recognize the functionality of biological knowledge of reproduction in work placement sites. Although
Gijselaers, H. J. M. (2015, 20 October). Biological lifestyle factors in adult distance education: predicting cognitive and learning performance. Presentation given for the inter-faculty Data Science group at the Open University of the Netherlands, Heerlen, The Netherlands.
Full Text Available The aim of the present study was to determine the effects of multimedia-based biology teaching (Mbio and teacher-centered biology (TCbio instruction approaches on learners' biology achievements, as well as their views towards learning approaches. During the research process, an experimental design with two groups, TCbio (n = 22 and Mbio (n = 26, were used. The results of the study proved that the Mbio approach was more effective than the TCbio approach with regard to supporting meaningful learning, academic achievement, enjoyment and motivation. Moreover, the TCbio approach is ineffective in terms of time management, engaging attention, and the need for repetition of subjects. Additionally, the results were discussed in terms of teaching, learning, multimedia design as well as biology teaching/learning.
Gardiner, N.; Bjerklie, D. M.
Ongoing research into the evolution of fishes in the lower Congo River suggests a close tie between diversity and hydraulic complexity of flow in the channel. For example, fish populations on each side of the rapids at the head of the lower Congo are within 1.5 km of one another, a distance normally allowing for interbreeding in river systems of comparable size, yet these fish populations show about 5% divergence in their mitochondrial DNA signatures. The proximal reason for this divergence is hydraulic complexity: the speed and turbulence of water moving through the thalweg is a barrier to dispersal for these fishes. Further examination of fish diversity suggests additional correlations of evolutionary divergence of fish clades in association with geomorphic and hydraulic features such as deep pools, extensive systems of rapids, alternating sections of fast and slow current, and recurring whirlpools. Due to prohibitive travel costs, limited field time, and the large geographic domain (approximately 400 river km) of the study area, we undertook a nested set of remote sensing analyses to extract habitat features, geomorphic descriptors, and hydraulic parameters including channel forming velocity, depth, channel roughness, slope, and shear stress. Each of these estimated parameters is mapped for each 1 km segment of the river from the rapids described above to below Inga Falls, a massive cataract where several endemic fish species have been identified. To validate remote sensing estimates, we collected depth and velocity data within the river using gps-enabled sonar measurements from a kayak and Doppler profiling from a motor-driven dugout canoe. Observations corroborate remote sensing estimates of geomorphic parameters. Remote sensing-based estimates of channel-forming velocity and depth were less than the observed maximum channel depth but correlated well with channel properties within 1 km reach segments. This correspondence is notable. The empirical models used
M. Claire Horner-Devine
Full Text Available While the biological sciences have achieved gender parity in the undergraduate and graduate career stages, this is not the case at the faculty level. The WEBS (Women Evolving the Biological Sciences symposia go beyond traditional scientific training and professional development to address factors critical to women’s persistence in faculty careers: community and empowerment. Through a series of panel discussions, personal reflections and skills workshops, WEBS creates a community-based professional development experience and a space for participants to grapple with central issues affecting their scientific careers. Longitudinal qualitative survey data suggest that WEBS bolsters the participants’ confidence and empowerment, in addition to providing concrete skills for addressing a range of issues necessary to navigating scientific careers, leading to increased career satisfaction and career self-efficacy (i.e., the belief in one’s capacity to pursue their chosen career. These results highlight the importance and need for programs and opportunities for women in STEM that go beyond training in scientific skills and traditional professional development to include those that create a sense of community and empowerment.
Griffith, Oliver W; Blackburn, Daniel G; Brandley, Matthew C; Van Dyke, James U; Whittington, Camilla M; Thompson, Michael B
To understand evolutionary transformations it is necessary to identify the character states of extinct ancestors. Ancestral character state reconstruction is inherently difficult because it requires an accurate phylogeny, character state data, and a statistical model of transition rates and is fundamentally constrained by missing data such as extinct taxa. We argue that model based ancestral character state reconstruction should be used to generate hypotheses but should not be considered an analytical endpoint. Using the evolution of viviparity and reversals to oviparity in squamates as a case study, we show how anatomical, physiological, and ecological data can be used to evaluate hypotheses about evolutionary transitions. The evolution of squamate viviparity requires changes to the timing of reproductive events and the successive loss of features responsible for building an eggshell. A reversal to oviparity requires that those lost traits re-evolve. We argue that the re-evolution of oviparity is inherently more difficult than the reverse. We outline how the inviability of intermediate phenotypes might present physiological barriers to reversals from viviparity to oviparity. Finally, we show that ecological data supports an oviparous ancestral state for squamates and multiple transitions to viviparity. In summary, we conclude that the first squamates were oviparous, that frequent transitions to viviparity have occurred, and that reversals to oviparity in viviparous lineages either have not occurred or are exceedingly rare. As this evidence supports conclusions that differ from previous ancestral state reconstructions, our paper highlights the importance of incorporating biological evidence to evaluate model-generated hypotheses. © 2015 Wiley Periodicals, Inc.
Green, Sara; Wolkenhauer, Olaf
on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational......With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to “reverse engineer” the functional organization of biological systems using methodologies from mathematics, engineering and computer science while...... taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw...
Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia
Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human…
Reid, Noah M; Whitehead, Andrew
Marine pollution is ubiquitous, and is one of the key factors influencing contemporary marine biodiversity worldwide. To protect marine biodiversity, how do we surveil, document and predict the short- and long-term impacts of pollutants on at-risk species? Modern genomics tools offer high-throughput, information-rich and increasingly cost-effective approaches for characterizing biological responses to environmental stress, and are important tools within an increasing sophisticated kit for surveiling and assessing impacts of pollutants on marine species. Through the lens of recent research in marine killifish, we illustrate how genomics tools may be useful for screening chemicals and pollutants for biological activity and to reveal specific mechanisms of action. The high dimensionality of transcriptomic responses enables their usage as highly specific fingerprints of exposure, and these fingerprints can be used to diagnose environmental problems. We also emphasize that molecular pathways recruited to respond at physiological timescales are the same pathways that may be targets for natural selection during chronic exposure to pollutants. Gene complement and sequence variation in those pathways can be related to variation in sensitivity to environmental pollutants within and among species. Furthermore, allelic variation associated with evolved tolerance in those pathways could be tracked to estimate the pace of environmental health decline and recovery. We finish by integrating these paradigms into a vision of how genomics approaches could anchor a modernized framework for advancing the predictive capacity of environmental and ecotoxicological science. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: email@example.com.
Koksal, Mustafa Serdar
The degree to which pre-service teachers learn biology is related to both motivational factors of self-regulation and factors regarding epistemological beliefs. At the same time, self-regulation and epistemological beliefs are also associated with one another. Based on this relationship, the purpose of this study was to investigate the…
DebBurman, Shubhik K
Facilitating not only the mastery of sophisticated subject matter, but also the development of process skills is an ongoing challenge in teaching any introductory undergraduate course. To accomplish this goal in a sophomore-level introductory cell biology course, I require students to work in groups and complete several mock experiential research projects that imitate the professional activities of the scientific community. I designed these projects as a way to promote process skill development within content-rich pedagogy and to connect text-based and laboratory-based learning with the world of contemporary research. First, students become familiar with one primary article from a leading peer-reviewed journal, which they discuss by means of PowerPoint-based journal clubs and journalism reports highlighting public relevance. Second, relying mostly on primary articles, they investigate the molecular basis of a disease, compose reviews for an in-house journal, and present seminars in a public symposium. Last, students author primary articles detailing investigative experiments conducted in the lab. This curriculum has been successful in both quarter-based and semester-based institutions. Student attitudes toward their learning were assessed quantitatively with course surveys. Students consistently reported that these projects significantly lowered barriers to primary literature, improved research-associated skills, strengthened traditional pedagogy, and helped accomplish course objectives. Such approaches are widely suited for instructors seeking to integrate process with content in their courses.
Lin, Tzu-Chiang; Liang, Jyh-Chong; Tsai, Chin-Chung
This study aims to explore Taiwanese university students' conceptions of learning biology as memorizing or as understanding, and their self-efficacy. To this end, two questionnaires were utilized to survey 293 Taiwanese university students with biology-related majors. A questionnaire for measuring students' conceptions of memorizing and…
Nugraini, Siti Hadiati; Choo, Koo Ah; Hin, Hew Soon; Hoon, Teoh Sian
This paper considers the design and development of a Website for Biology in senior high schools in Indonesia. The teaching media, namely e-AV Biology, was developed with the main features of video lessons and other features in supporting the students' learning process. Some video lessons describe the production process of Biofuel or Renewable…
Bramwell-Lalor, Sharon; Rainford, Marcia
This paper reports on a Mixed Methods study involving an investigation into the attitudes of advanced level biology teachers towards assessment and describes the teachers' experiences while being engaged in Assessment for Learning (AfL) practices such as sharing of learning objectives and peer- and self-assessment. Quantitative data were collected…
Samsudin, Mohd Wahid; Daik, Rusli; Abas, Azlan; Meerah, T. Subahan Mohd; Halim, Lilia
In this study, the learning of science outside the classroom is believe to be an added value to science learning as well as it offers students to interact with the environment. This study presents data obtained from two days' workshop on Lichen as Biological Indicator for Air Quality. The aim of the workshop is for the students to gain an…
Nie, Pu-Yan; Zhang, Pei-Ai
Evolutionary graph theory (EGT) is recently proposed by Lieberman et al. in 2005. EGT is successful for explaining biological evolution and some social phenomena. It is extremely important to consider the time of fixation for EGT in many practical problems, including evolutionary theory and the evolution of cooperation. This study characterizes the time to asymptotically reach fixation.
Gangestad, S.W.; Tybur, J.M.
Functional approaches in psychology - which ask what behavior is good for - are almost as old as scientific psychology itself. Yet sophisticated, generative functional theories were not possible until developments in evolutionary biology in the mid-20th century. Arising in the last three decades,
Explains an interdisciplinary approach to biology and writing which increases students' mastery of vocabulary, scientific concepts, creativity, and expression. Describes modifications of the clustering technique used to summarize lectures, integrate reading and understand textbook material. (RT)
Günes, M. Handan
This study has been carried out with the aim of researching dominant learning styles of the students studying at the biology departments of the faculty of science or the faculty of arts and sciences as well as the dominant learning styles of the prospective biology teachers studying at the faculty of education of universities in Turkey, by taking…
Sadi, Özlem; Dagyar, Miray
The current work reveals the data of the study which examines the relationships among epistemological beliefs, conceptions of learning, and self-efficacy for biology learning with the help of the Structural Equation Modeling. Three questionnaires, the Epistemological Beliefs, the Conceptions of Learning Biology and the Self-efficacy for Learning…
Cahyani, R.; Mardiana, D.; Noviantoro, N.
Scientific inquiry is highly recommended to teach science. The reality in the schools and colleges is that many educators still have not implemented inquiry learning because of their lack of understanding. The study aims to1) analyze students’ difficulties in learning General Biology, 2) design General Biology learning program based on multimedia-assisted scientific inquiry learning, and 3) validate the proposed design. The method used was Research and Development. The subjects of the study were 27 pre-service students of general elementary school/Islamic elementary schools. The workflow of program design includes identifying learning difficulties of General Biology, designing course programs, and designing instruments and assessment rubrics. The program design is made for four lecture sessions. Validation of all learning tools were performed by expert judge. The results showed that: 1) there are some problems identified in General Biology lectures; 2) the designed products include learning programs, multimedia characteristics, worksheet characteristics, and, scientific attitudes; and 3) expert validation shows that all program designs are valid and can be used with minor revisions. The first section in your paper.
Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik
Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.
Cuperman, Dan; Verner, Igor M.
This paper considers an approach to studying issues in technology and science, which integrates design and inquiry activities towards creating and exploring technological models of scientific phenomena. We implemented this approach in a context where the learner inquires into a biological phenomenon and develops its representation in the form of a…
Batiza, Ann; Luo, Wen; Zhang, Bo; Gruhl, Mary; Nelson, David; Hoelzer, Mark; Ning, Ling; Roberts, Marisa; Knopp, Jonathan; Harrington, Tom; LaFlamme, Donna; Haasch, Mary Anne; Vogt, Gina; Goodsell, David; Marcey, David
The SUN approach to biological energy transfer education is fundamentally different from past practices that trace chemical and energy inputs and outputs. The SUN approach uses a hydrogen fuel cell to convince learners that electrons can move from one substance to another based on differential attraction. With a hydrogen fuel cell, learners can…
Waldrop, Lindsay D; Adolph, Stephen C; Diniz Behn, Cecilia G; Braley, Emily; Drew, Joshua A; Full, Robert J; Gross, Louis J; Jungck, John A; Kohler, Brynja; Prairie, Jennifer C; Shtylla, Blerta; Miller, Laura A
This article provides a summary of the ideas discussed at the 2015 Annual Meeting of the Society for Integrative and Comparative Biology society-wide symposium on Leading Students and Faculty to Quantitative Biology through Active Learning. It also includes a brief review of the recent advancements in incorporating active learning approaches into quantitative biology classrooms. We begin with an overview of recent literature that shows that active learning can improve students' outcomes in Science, Technology, Engineering and Math Education disciplines. We then discuss how this approach can be particularly useful when teaching topics in quantitative biology. Next, we describe some of the recent initiatives to develop hands-on activities in quantitative biology at both the graduate and the undergraduate levels. Throughout the article we provide resources for educators who wish to integrate active learning and technology into their classrooms. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: firstname.lastname@example.org.
Skinner, Kerri M.; Hoback, W. Wyatt
Presents a website that addresses concepts that form a foundation for understanding ecology, pest management, and environmental ethics. Key features of the website include its self-contained, non-linear design; a learning environment that allows students to test ideas without penalty; real-world examples; and built-in assessment tools that…
Wozniak, Breann M.
The purpose of this study was to examine the effect of process-oriented guided-inquiry learning (POGIL) on non-majors college biology students' understanding of biological classification. This study addressed an area of science instruction, POGIL in the non-majors college biology laboratory, which has yet to be qualitatively and quantitatively researched. A concurrent triangulation mixed methods approach was used. Students' understanding of biological classification was measured in two areas: scores on pre and posttests (consisting of 11 multiple choice questions), and conceptions of classification as elicited in pre and post interviews and instructor reflections. Participants were Minnesota State University, Mankato students enrolled in BIOL 100 Summer Session. One section was taught with the traditional curriculum (n = 6) and the other section in the POGIL curriculum (n = 10) developed by the researcher. Three students from each section were selected to take part in pre and post interviews. There were no significant differences within each teaching method (p familiar animal categories and aquatic habitats, unfamiliar organisms, combining and subdividing initial groupings, and the hierarchical nature of classification. The POGIL students were the only group to surpass these challenges after the teaching intervention. This study shows that POGIL is an effective technique at eliciting students' misconceptions, and addressing these misconceptions, leading to an increase in student understanding of biological classification.
Evolutionary game theory has been viewed as an evolutionary repair of rational actor game theory in the hope that a population of boundedly rational players may attain convergence to classic rational solutions, such as the Nash Equilibrium, via some learning or evolutionary process. In this thesis
Kudish, Philip; Shores, Robin; McClung, Alex; Smulyan, Lisa; Vallen, Elizabeth A.; Siwicki, Kathleen K.
Study group meetings (SGMs) are voluntary-attendance peer-led team-learning workshops that supplement introductory biology lectures at a selective liberal arts college. While supporting all students' engagement with lecture material, specific aims are to improve the success of underrepresented minority (URM) students and those with weaker…
Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung
This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely 'multiple-source,' 'uncertainty,' 'development,' and 'justification.' COLB is further divided into 'constructivist' and 'reproductive' conceptions, while SLB represents deep strategies and surface learning strategies. Questionnaire responses were gathered from 303 college students. The results of the confirmatory factor analysis and structural equation modelling showed acceptable model fits. Mediation testing further revealed two paths with complete mediation. In sum, students' epistemic beliefs of 'uncertainty' and 'justification' in biology were statistically significant in explaining the constructivist and reproductive COLB, respectively; and 'uncertainty' was statistically significant in explaining the deep SLB as well. The results of mediation testing further revealed that 'uncertainty' predicted surface strategies through the mediation of 'reproductive' conceptions; and the relationship between 'justification' and deep strategies was mediated by 'constructivist' COLB. This study provides evidence for the essential roles some epistemic beliefs play in predicting students' learning.
Richard M. Magsino
Full Text Available The purpose of this research was to examine students' perspectives of their learning in marine biology in the collaborative group context of Problem-based Learning (PBL. Students’ higher order thinking skills (HOTS using PBL involves the development of their logical thinking and reasoning abilities which stimulates their curiosity and associative thinking. This study aimed to investigate how critical thinking skills, particularly analysis, synthesis and evaluation were enhanced in a marine biology class through PBL. Qualitative research approach was used to examine student responses in a questionnaire involving 10 open-ended questions that target students’ HOTS on a problem presented in a marine biology class for BS Biology students. Using axial coding as a qualitative data analysis technique by which grounded theory can be performed, the study was able to determine how students manifest their higher reasoning abilities when confronted with a marine biology situation. Results show student responses yielding affirmative remarks on the 10 questions intended to know their level of analysis (e.g., analyzing, classifying, inferring, discriminating and relating or connecting, synthesis (e.g., synthesizing and collaborating, and evaluation (e.g., comparing, criticizing, and convincing of information from the presented marine biology problem. Consequently, students were able to effectively design experiments to address the presented issue through problem-based learning. Results of the study show that PBL is an efficient instructional strategy embedded within a conventional curriculum used to develop or enhance critical thinking in marine biology.
Bobick, Sandra Burin
This study investigated the influence of learning style on concept acquisition within a sample of community college students in a general biology course. There are two subproblems within the larger problem: (1) the influence of demographic variables (age, gender, number of college credits, prior exposure to scientific information) on learning style, and (2) the correlations between prior scientific knowledge, learning style and student understanding of the concept of the gene. The sample included all students enrolled in an introductory general biology course during two consecutive semesters at an urban community college. Initial data was gathered during the first week of the semester, at which time students filled in a short questionnaire (age, gender, number of college credits, prior exposure to science information either through reading/visual sources or a prior biology course). Subjects were then given the Inventory of Learning Processes-Revised (ILP-R) which measures general preferences in five learning styles; Deep Learning; Elaborative Learning, Agentic Learning, Methodical Learning and Literal Memorization. Subjects were then given the Gene Conceptual Knowledge pretest: a 15 question objective section and an essay section. Subjects were exposed to specific concepts during lecture and laboratory exercises. At the last lab, students were given the Genetics Conceptual Knowledge Posttest. Pretest/posttest gains were correlated with demographic variables and learning styles were analyzed for significant correlations. Learning styles, as the independent variable in a simultaneous multiple regression, were significant predictors of results on the gene assessment tests, including pretest, posttest and gain. Of the learning styles, Deep Learning accounted for the greatest positive predictive value of pretest essay and pretest objective results. Literal Memorization was a significant negative predictor for posttest essay, essay gain and objective gain. Simultaneous
Waldrop, Lindsay D; Miller, Laura A
The broad aim of this symposium and set of associated papers is to motivate the use of inquiry-based, active-learning teaching techniques in undergraduate quantitative biology courses. Practical information, resources, and ready-to-use classroom exercises relevant to physicists, mathematicians, biologists, and engineers are presented. These resources can be used to address the lack of preparation of college students in STEM fields entering the workforce by providing experience working on interdisciplinary and multidisciplinary problems in mathematical biology in a group setting. Such approaches can also indirectly help attract and retain under-represented students who benefit the most from "non-traditional" learning styles and strategies, including inquiry-based, collaborative, and active learning. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: email@example.com.
of Computational Intelligence. First, comprehensive surveys of genetic algorithms, genetic programming, evolution strategies, parallel evolutionary algorithms are presented, which are readable and constructive so that a large audience might find them useful and – to some extent – ready to use. Some more general...... kinds of evolutionary algorithms, have been prudently analyzed. This analysis was followed by a thorough analysis of various issues involved in stochastic local search algorithms. An interesting survey of various technological and industrial applications in mechanical engineering and design has been...... topics like the estimation of distribution algorithms, indicator-based selection, etc., are also discussed. An important problem, from a theoretical and practical point of view, of learning classifier systems is presented in depth. Multiobjective evolutionary algorithms, which constitute one of the most...
Scudo, Francesco M
Since a century evolution has mostly been interpreted by two simple, "opposite" kinds of "theories" i.e. as due either to fitness differences among genotypes or to some other simple mechanism while bona fide, more complex theories were less popular throughout. In particular by far the most complete theories ever produced were suddenly, almost universally abandoned just after World War II, though not as a consequence of major breakthroughs. The causes of this situation are examined by analogy with much earlier developments and their demise by Cartesianism. The down to earth solutions these "complete" theories provide to the problems of "speciation" and the origins of cells are contrasted with the "miraculous" approaches by systemic neo-Darwinists.
Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong
Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.
Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune
Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.
Conducting cell biology experiments in microgravity can be among the most technically challenging events in a biologist's life. Conflicting events of spaceflight include waiting to get manifested, delays in manifest schedules, training astronauts to not shake your cultures and to add reagents slowly, as shaking or quick injection can activate signaling cascades and give you erroneous results. It is important to select good hardware that is reliable. Possible conflicting environments in flight include g-force and vibration of launch, exposure of cells to microgravity for extended periods until hardware is turned on, changes in cabin gases and cosmic radiation. One should have an on-board 1-g control centrifuge in order to eliminate environmental differences. Other obstacles include getting your funding in a timely manner (it is not uncommon for two to three years to pass between notification of grant approval for funding and actually getting funded). That said, it is important to note that microgravity research is worthwhile since all terrestrial life evolved in a gravity field and secrets of biological function may only be answered by removing the constant of gravity. Finally, spaceflight experiments are rewarding and worth your effort and patience.
Huang, Huang; Cruz, William; Chen, Juan; Zheng, Gang
Synthetic lipoproteins represent a relevant tool for targeted delivery of biological/chemical agents (chemotherapeutics, siRNAs, photosensitizers, and imaging contrast agents) into various cell types. These nanoparticles offer a number of advantages for drugs delivery over their native counterparts while retaining their natural characteristics and biological functions. Their ultra-small size (lipoprotein receptors, i.e., low-density lipoprotein receptor (LDLR) and Scavenger receptor class B member 1 (SRB1) that are found in a number of pathological conditions (e.g., cancer, atherosclerosis), make them superior delivery strategies when compared with other nanoparticle systems. We review the various approaches that have been developed for the generation of synthetic lipoproteins and their respective applications in vitro and in vivo. More specifically, we summarize the approaches employed to address the limitation on use of reconstituted lipoproteins by means of natural or recombinant apolipoproteins, as well as apolipoprotein mimetic molecules. Finally, we provide an overview of the advantages and disadvantages of these approaches and discuss future perspectives for clinical translation of these nanoparticles. © 2014 Wiley Periodicals, Inc.
Full Text Available In this article, we advance the concept of “evolutionary awareness,” a metacognitive framework that examines human thought and emotion from a naturalistic, evolutionary perspective. We begin by discussing the evolution and current functioning of the moral foundations on which our framework rests. Next, we discuss the possible applications of such an evolutionarily-informed ethical framework to several domains of human behavior, namely: sexual maturation, mate attraction, intrasexual competition, culture, and the separation between various academic disciplines. Finally, we discuss ways in which an evolutionary awareness can inform our cross-generational activities—which we refer to as “intergenerational extended phenotypes”—by helping us to construct a better future for ourselves, for other sentient beings, and for our environment.
Lehmann, Torsten; Woodburn, Robin
Self-learning chips to implement many popular ANN (artificial neural network) algorithms are very difficult to design. We explain why this is so and say what lessons previous work teaches us in the design of self-learning systems. We offer a contribution to the "biologically-inspired" approach......, explaining what we mean by this term and providing an example of a robust, self-learning design that can solve simple classical-conditioning tasks, We give details of the design of individual circuits to perform component functions, which can then be combined into a network to solve the task. We argue...
Ermayanti; Susanti, R.; Anwar, Y.
This study aims to obtaining students’ representation ability in understanding the structure and function of plant tissues in plant anatomy course. Thirty students of The Biology Education Department of Sriwijaya University were involved in this study. Data on representation ability were collected using test and observation. The instruments had been validated by expert judgment. Test scores were used to represent students’ ability in 4 categories: 2D-image, 3D-image, spatial, and verbal representations. The results show that students’ representation ability is still low: 2D-image (40.0), 3D-image (25.0), spatial (20.0), and verbal representation (45.0). Based on the results of this study, it is suggested that instructional strategies be developed for plant anatomy course.
Dekker, Sanne; Jolles, Jelle
This study evaluated a new teaching module about "Brain and Learning" using a controlled design. The module was implemented in high school biology classes and comprised three lessons: (1) brain processes underlying learning; (2) neuropsychological development during adolescence; and (3) lifestyle factors that influence learning performance. Participants were 32 biology teachers who were interested in "Brain and Learning" and 1241 students in grades 8-9. Teachers' knowledge and students' beliefs about learning potential were examined using online questionnaires. Results indicated that before intervention, biology teachers were significantly less familiar with how the brain functions and develops than with its structure and with basic neuroscientific concepts (46 vs. 75% correct answers). After intervention, teachers' knowledge of "Brain and Learning" had significantly increased (64%), and more students believed that intelligence is malleable (incremental theory). This emphasizes the potential value of a short teaching module, both for improving biology teachers' insights into "Brain and Learning," and for changing students' beliefs about intelligence.
Semsar, Katharine; Knight, Jennifer K.; Birol, Gülnur; Smith, Michelle K.
This paper describes a newly adapted instrument for measuring novice-to-expert-like perceptions about biology: the Colorado Learning Attitudes about Science Survey for Biology (CLASS-Bio). Consisting of 31 Likert-scale statements, CLASS-Bio probes a range of perceptions that vary between experts and novices, including enjoyment of the discipline, propensity to make connections to the real world, recognition of conceptual connections underlying knowledge, and problem-solving strategies. CLASS-Bio has been tested for response validity with both undergraduate students and experts (biology PhDs), allowing student responses to be directly compared with a consensus expert response. Use of CLASS-Bio to date suggests that introductory biology courses have the same challenges as introductory physics and chemistry courses: namely, students shift toward more novice-like perceptions following instruction. However, students in upper-division biology courses do not show the same novice-like shifts. CLASS-Bio can also be paired with other assessments to: 1) examine how student perceptions impact learning and conceptual understanding of biology, and 2) assess and evaluate how pedagogical techniques help students develop both expertise in problem solving and an expert-like appreciation of the nature of biology. PMID:21885823
Semsar, Katharine; Knight, Jennifer K; Birol, Gülnur; Smith, Michelle K
This paper describes a newly adapted instrument for measuring novice-to-expert-like perceptions about biology: the Colorado Learning Attitudes about Science Survey for Biology (CLASS-Bio). Consisting of 31 Likert-scale statements, CLASS-Bio probes a range of perceptions that vary between experts and novices, including enjoyment of the discipline, propensity to make connections to the real world, recognition of conceptual connections underlying knowledge, and problem-solving strategies. CLASS-Bio has been tested for response validity with both undergraduate students and experts (biology PhDs), allowing student responses to be directly compared with a consensus expert response. Use of CLASS-Bio to date suggests that introductory biology courses have the same challenges as introductory physics and chemistry courses: namely, students shift toward more novice-like perceptions following instruction. However, students in upper-division biology courses do not show the same novice-like shifts. CLASS-Bio can also be paired with other assessments to: 1) examine how student perceptions impact learning and conceptual understanding of biology, and 2) assess and evaluate how pedagogical techniques help students develop both expertise in problem solving and an expert-like appreciation of the nature of biology.
Maskiewicz, April Lee
Educational studies report that secondary and college level students have developed only limited understandings of the most basic biological processes and their interrelationships from typical classroom experiences. Furthermore, students have developed undesirable reasoning schemes and beliefs that directly affect how they make sense of and account for biological phenomena. For these reasons, there exists a need to rethink instructional practices in biology. This dissertation discusses how the principles of Harel's (1998, 2001) DNR-based instruction in mathematics could be applied to the teaching and learning of biology. DNR is an acronym for the three foundational principles of the system: Duality, Necessity, and Repeated-reasoning. This study examines the application of these three principles to ecology instruction. Through clinical and teaching interviews, I developed models of students' existing ways of understanding in ecology and inferred their ways of thinking. From these models a hypothetical learning trajectory was developed for 16 college level freshmen enrolled in a 10-week ecology teaching experiment. Through cyclical, interpretive analysis I documented and analyzed the evolution of the participants' progress. The results provide empirical evidence to support the claim that the DNR principles are applicable to ecology instruction. With respect to the Duality Principle, helping students develop specific ways of understanding led to the development of model-based reasoning---a way of thinking and the cognitive objective guiding instruction. Through carefully structured problem solving tasks, the students developed a biological understanding of the relationship between matter cycling, energy flow, and cellular processes such as photosynthesis and respiration, and used this understanding to account for observable phenomena in nature. In the case of intellectual necessity, the results illuminate how problem situations can be developed for biology learners
Kudish, Philip; Shores, Robin; McClung, Alex; Smulyan, Lisa; Vallen, Elizabeth A; Siwicki, Kathleen K
Study group meetings (SGMs) are voluntary-attendance peer-led team-learning workshops that supplement introductory biology lectures at a selective liberal arts college. While supporting all students' engagement with lecture material, specific aims are to improve the success of underrepresented minority (URM) students and those with weaker backgrounds in biology. Peer leaders with experience in biology courses and training in science pedagogy facilitate work on faculty-generated challenge problems. During the eight semesters assessed in this study, URM students and those with less preparation attended SGMs with equal or greater frequency than their counterparts. Most agreed that SGMs enhanced their comprehension of biology and ability to articulate solutions. The historical grade gap between URM and non-URM students narrowed slightly in Biology 2, but not in other biology and science, technology, engineering, and mathematics courses. Nonetheless, URM students taking introductory biology after program implementation have graduated with biology majors or minors at the same rates as non-URM students, and have enrolled in postcollege degree programs at equal or greater rates. These results suggest that improved performance as measured by science grade point average may not be necessary to improve the persistence of students from underrepresented groups as life sciences majors. © 2016 P. Kudish et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Telli, S.; Brok, den P.J.; Tekkaya, C.; Cakiroglu, J.
This study investigates the effects of gender and grade level on Turkish secondary school students’ perceptions of their biology learning environment. A total of 1474 high school students completed the What is Happening in This Classroom (WIHIC) questionnaire. The WIHIC maps several important
Burrowes, Patricia; Nazario, Gladys
The authors engaged in an education experiment to determine if the integration of lab and lecture activities in zoology and botany proved beneficial to student learning and motivation toward biology. Their results revealed that this strategy positively influenced students' academic achievement, conceptual understanding, and ability to apply…
Solis, Juan D.
This publication presents four science curriculum units designed to meet the learning problems of students with special language handicaps. The materials are written in both English and Spanish, and deal with topics in biology suitable for students in grades 7 through 11. All four units were classroom tested during 1970-1972 in the Calexico…
Gijselaers, Jérôme; De Groot, Renate; Kirschner, Paul A.
An important part of learning performance is influenced by individual characteristics. One of those are the environmental influences determined by lifestyle. We call these influences biological lifestyle factors (BLFs). Physical activity, sleep and nutrition are such BLFs and they contribute to
Krauss, David A.; Salame, Issa I.; Goodwyn, Lauren N.
If a picture is worth a thousand words, think about how long it takes your students to read a thousand words. Case studies are effective and stimulating ways to teach a variety of subjects, including the biological sciences. In learning the details of a particular case, students develop skills in both deductive and inductive reasoning, hypothesis…
Gehring, Kathleen M; Eastman, Deborah A
Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to promote information fluency are being promoted on many college and university campuses. Information fluency refers to discipline-specific processing of information, and it involves integration of gathered information with specific ideas to form logical conclusions. We have implemented the use of inquiry-based learning to enhance and study discipline-specific information fluency skills in an upper-level undergraduate Developmental Biology course. In this study, an information literacy tutorial and a set of linked assignments using primary literature analysis were integrated with two inquiry-based laboratory research projects. Quantitative analysis of student responses suggests that the abilities of students to identify and apply valid sources of information were enhanced. Qualitative assessment revealed a set of patterns by which students gather and apply information. Self-assessment responses indicated that students recognized the impact of the assignments on their abilities to gather and apply information and that they were more confident about these abilities for future biology courses and beyond.
Gyuri Csoka; William J. Mattson; Graham N. Stone; Peter W. Price
This proceedings explores many facets of the ever intriguing and enigmatic relationships between plants and their gall-forming herbivores. The research reported herein ranges from studies on classical biology and systematics of galling to molecular phylogeny, population genetics, and ecological and evolutionary theory. Human kind has much to learn and gain from...
Baer, B; Millar, A H
Evolutionary ecologists are traditionally gene-focused, as genes propagate phenotypic traits across generations and mutations and recombination in the DNA generate genetic diversity required for evolutionary processes. As a consequence, the inheritance of changed DNA provides a molecular explanation for the functional changes associated with natural selection. A direct focus on proteins on the other hand, the actual molecular agents responsible for the expression of a phenotypic trait, receives far less interest from ecologists and evolutionary biologists. This is partially due to the central dogma of molecular biology that appears to define proteins as the 'dead-end of molecular information flow' as well as technical limitations in identifying and studying proteins and their diversity in the field and in many of the more exotic genera often favored in ecological studies. Here we provide an overview of a newly forming field of research that we refer to as 'Evolutionary Proteomics'. We point out that the origins of cellular function are related to the properties of polypeptide and RNA and their interactions with the environment, rather than DNA descent, and that the critical role of horizontal gene transfer in evolution is more about coopting new proteins to impact cellular processes than it is about modifying gene function. Furthermore, post-transcriptional and post-translational processes generate a remarkable diversity of mature proteins from a single gene, and the properties of these mature proteins can also influence inheritance through genetic and perhaps epigenetic mechanisms. The influence of post-transcriptional diversification on evolutionary processes could provide a novel mechanistic underpinning for elements of rapid, directed evolutionary changes and adaptations as observed for a variety of evolutionary processes. Modern state-of the art technologies based on mass spectrometry are now available to identify and quantify peptides, proteins, protein
In evolutionary robotics, a suitable robot control system is developed automatically through evolution due to the interactions between the robot and its environment. It is a complicated task, as the robot and the environment constitute a highly dynamical system. Several methods have been tried by various investigators to ...
Almeida, M. J.; Nobre, Alexandra; Pinto, Augusta; Cunha, Lília; Maciel, Elsa Marina Costa; Almeida Aguiar, Cristina; Forjaz, Maria Antónia
The development of teaching and learning strategies that effectively assist in the understanding of scientific knowledge is an ongoing challenge. Doing experiments outside the classroom, one of the recommended approaches, presents some risks, because students can divert their attention from the pedagogical objective of activity . However, experts agree in considering that learning outside the classroom can be used to facilitate Education. Providing students with learning activities in rele...
Colmenares, Fernando; Hernández-Lloreda, María Victoria
In humans and other animals, the individuals' ability to adapt efficiently and effectively to the niches they have actively contributed to construct relies heavily on an evolved psychology which has been shaped by biological, social, and cultural processes over evolutionary time. As expected, although many of the behavioral and cognitive components of this evolved psychology are widely shared across species, many others are species-unique. Although many animal species are known to acquire group-specific traditions (or cultures) via social learning, human culture is unique in terms of its contents and characteristics (observable and unobservable products, cumulative effects, norm conformity, and norm enforcement) and of its cognitive underpinnings (imitation, instructed teaching, and language). Here we provide a brief overview of some of the issues that are currently tackled in the field. We also highlight some of the strengths of a biological, comparative, non-anthropocentric and evolutionarily grounded approach to the study of culture. The main contributions of this approach to the science of culture are its emphasis (a) on the integration of information on mechanisms, function, and evolution, and on mechanistic factors located at different levels of the biological hierarchy, and (b) on the search for general principles that account for commonalities and differences between species, both in the cultural products and in the processes of innovation, dissemination, and accumulation involved that operate during developmental and evolutionary timespans.
Biel, Rachel; Brame, Cynthia J
Online courses are a large and growing part of the undergraduate education landscape, but many biology instructors are skeptical about the effectiveness of online instruction. We reviewed studies comparing the effectiveness of online and face-to-face (F2F) undergraduate biology courses. Five studies compared student performance in multiple course sections at community colleges, while eight were smaller scale and compared student performance in particular biology courses at a variety of types of institutions. Of the larger-scale studies, two found that students in F2F sections outperformed students in online sections, and three found no significant difference; it should be noted, however, that these studies reported little information about course design. Of the eight smaller scale studies, six found no significant difference in student performance between the F2F and online sections, while two found that the online sections outperformed the F2F sections. In alignment with general findings about online teaching and learning, these results suggest that well-designed online biology courses can be effective at promoting student learning. Three recommendations for effective online instruction in biology are given: the inclusion of an online orientation to acclimate students to the online classroom; student-instructor and student-student interactions facilitated through synchronous and asynchronous communication; and elements that prompt student reflection and self-assessment. We conclude that well-designed online biology courses can be as effective as their traditional counterparts, but that more research is needed to elucidate specific course elements and structures that can maximize online students' learning of key biology skills and concepts.
Full Text Available Online courses are a large and growing part of the undergraduate education landscape, but many biology instructors are skeptical about the effectiveness of online instruction. We reviewed studies comparing the effectiveness of online and face-to-face (F2F undergraduate biology courses. Five studies compared student performance in multiple course sections at community colleges, while eight were smaller scale and compared student performance in particular biology courses at a variety of types of institutions. Of the larger-scale studies, two found that students in F2F sections outperformed students in online sections, and three found no significant difference; it should be noted, however, that these studies reported little information about course design. Of the eight smaller scale studies, six found no significant difference in student performance between the F2F and online sections, while two found that the online sections outperformed the F2F sections. In alignment with general findings about online teaching and learning, these results suggest that well-designed online biology courses can be effective at promoting student learning. Three recommendations for effective online instruction in biology are given: the inclusion of an online orientation to acclimate students to the online classroom; student-instructor and student-student interactions facilitated through synchronous and asynchronous communication; and elements that prompt student reflection and self-assessment. We conclude that well-designed online biology courses can be as effective as their traditional counterparts, but that more research is needed to elucidate specific course elements and structures that can maximize online students’ learning of key biology skills and concepts.
The purpose of this study is to investigate the influence of the web-aided cooperative learning environment on biology preservice teachers' motivation and on their self-efficacy beliefs in biology teaching. The study was carried out with 30 biology preservice teachers attending a state university in Turkey. In the study, the pretest-posttest…
Auerbach, Anna Jo; Schussler, Elisabeth
Increasing faculty use of active-learning (AL) pedagogies in college classrooms is a persistent challenge in biology education. A large research-intensive university implemented changes to its biology majors’ two-course introductory sequence as outlined by the Vision and Change in Undergraduate Biology Education final report. One goal of the curricular reform was to integrate core biological concepts and competencies into the courses using AL pedagogical approaches. The purpose of this study was to observe the instructional practices used by faculty (N = 10) throughout the 3-year process of reform to determine whether the use of AL strategies (including student collaboration) increased, given that it can maximize student learning gains. Instructors participated in yearly interviews to track any change in their perceptions of AL instruction. Instructors increased their average use of AL by 12% (group AL by 8%) of total class time throughout the 3-year study. Interviews revealed that instructors shifted their definitions of AL and talked more about how to assess student learning over the 3 years of the project. Collaboration, feedback, and time may have been important factors in the reform, suggesting that small shifts over time can accumulate into real change in the classroom. PMID:29146663
Full Text Available The paper analyzes the comparative effectiveness of Computer-Assisted Learning (CAL and the traditional teaching method in biology on primary school pupils. A stratified random sample consisted of 214 pupils from two primary schools in Novi Sad. The pupils in the experimental group learned the biology content (Chordate using CAL, whereas the pupils in the control group learned the same content using traditional teaching. The research design was the pretest-posttest equivalent groups design. All instruments (the pretest, the posttest and the retest contained the questions belonging to three different cognitive domains: knowing, applying, and reasoning. Arithmetic mean, standard deviation, and standard error were analyzed using the software package SPSS 14.0, and t-test was used in order to establish the difference between the same statistical indicators. The analysis of results of the posttest and the retest showed that the pupils from the CAL group achieved significantly higher quantity and quality of knowledge in all three cognitive domains than the pupils from the traditional group. The results accomplished by the pupils from the CAL group suggest that individual CAL should be more present in biology teaching in primary schools, with the aim of raising the quality of biology education in pupils. [Projekat Ministarstva nauke Republike Srbije, br. 179010: Quality of Educational System in Serbia in the European Perspective
Smith, Wade Clay, Jr.
The primary goals of this dissertation were to determine the relationships between interpersonal teaching behaviors and student achievement and affective learning outcomes. The instrument used to collect student perceptions of teacher interpersonal teaching behaviors was the Questionnaire on Teacher Interactions (QTI). The instrument used to assess student affective learning outcomes was the Biology Student Affective Instrument (BSAI). The interpersonal teaching behavior data were collected using students as the observers. 111 students in an urban influenced, rural high school answered the QTI and BSAI in September 1997 and again in April 1998. At the same time students were pre and post tested using the Biology End of Course Examination (BECE). The QTI has been used primarily in European and Oceanic areas. The instrument was also primarily used in educational stratified environment. This was the first time the BSAI was used to assess student affective learning outcomes. The BECE is a Texas normed cognitive assessment test and it is used by Texas schools districts as the end of course examination in biology. The interpersonal teaching behaviors model was tested to ascertain if predictive power in the USA and in a non-stratified educational environment. Findings indicate that the QTI is an adequate predictor of student achievement in biology. The results were not congruent with the non-USA data and results, this indicates that the QTI is a society/culturally sensitive instrument and the instrument needs to be normed to a particular society/culture before it is used to affect teachers' and students' educational environments.
Gnanakkan, Dionysius Joseph
This multiple case-study investigated how high school biology teachers used modern learning technologies (probes, interactive simulations and animations, animated videos) in their classrooms and why they used the learning technologies. Another objective of the study was to assess whether the use of learning technologies alleviated misconceptions…
Full Text Available Inquiry-based learning is one of the learning methods which can provide an active and authentic scientific learning process in order students are able to improve the creative thinking skills and scientific attitude. This study aims at improving creative thinking skills and scientific attitude through inquiry-based learning in basic biology lecture toward students of biology education at the Institut Agama Islam Negeri (IAIN Jember, Indonesia. This study is included in a descriptive quantitative research. The research focused on the topic of cell transport which was taught toward 25 students of Biology 2 class from 2017 academic year of Biology Education Department at the IAIN Jember. The learning process was conducted in two meetings in November 2017. The enhancement of students' creative thinking skills was determined by one group pre-test and post-test research design using test instrument meanwhile the scientific attitude focused on curiosity and objectivity were observed using the non-test instrument. Research result showed that students' creative thinking skills enhanced highly and students' scientific attitude improved excellently through inquiry-based learning in basic biology lecture.
Judith S. Rabacal
Full Text Available This is a descriptive study aimed to determine the academic achievement on science process skills of the BS Biology Students of Northern Negros State College of Science and Technology, Philippines with the end view of developing learning exercises which will enhance their academic achievement on basic and integrated science process skills. The data in this study were obtained using a validated questionnaire. Mean was the statistical tool used to determine the academic achievement on the above mentioned science process skills; t-test for independent means was used to determine significant difference on the academic achievement of science process skills of BS Biology students while Pearson Product Moment of Correlation Coefficient was used to determine the significant relationship between basic and integrated science process skills of the BS Biology students. A 0.05 level of significance was used to determine whether the hypothesis set in the study will be rejected or accepted. Findings revealed that the academic achievement on basic and integrated science process skills of the BS Biology students was average. Findings revealed that there are no significant differences on the academic performance of the BS Biology students when grouped according to year level and gender. Findings also revealed that there is a significant difference on the academic achievement between basic and integrated science process skills of the BS Biology students. Findings revealed that there is a significant relationship between academic achievement on the basic and integrated science process skills of the BS Biology students.
Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan
Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388
Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten
Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use....... Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively...
Photovoice projects traditionally include original visual imagery and minimal text to tell a powerful story. Photovoice student projects have been utilized in the health and social sciences to involve students with the local community and also in community-based projects to help at-risk youth call attention to their community problems, such as disease and drug use. The tool of the photovoice can be used in the biology classroom to engage students in the active learning process through communi...
Nellman, Stephen William
As growing student populations continue to tax the resources of public high schools, administrators are constantly looking for ways to address the needs of all students. One option for increasing the number of students in a classroom without sacrificing quality of instruction is to use "blended learning". Blended learning is defined by Marsh et al. (2003, p.2) as a situation where "face-to-face and distance education delivery methods and resources are merged". In such a course, students receive the benefits of classroom-based instruction, while also benefiting from several aspects of distance learning. This is especially true for science courses that rely heavily on both hands-on labs and various multimedia. The purpose of this study was a formative evaluation of a high school blended learning biology course, focusing on a genetics unit. The research question addressed by the study was "Will participants increase their domain knowledge and problem-solving skills after instruction in a high school level blended distance learning biology course? Also investigated was if higher levels of self-regulation skills were correlated to higher levels of content-understanding and problem-solving. The study was composed of a pilot study and a main study. Participants were students in an urban Southern California public high school biology course. Classroom instruction was from a single instructor, and online content was managed using the "Moodle" course management system. Participants were assessed for their gains in genetics content-understanding, genetics problem-solving skills (Punnett squares), and self-regulation. Additionally, participant reactions to the blended instruction model were surveyed. Results indicated that significant increases (pself-regulation skills were not shown to be significantly correlated to increased content-understanding, or problem-solving skills. Participants reacted positively to the blended model, suggesting that it be used more often in their
Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae
Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. 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
Cary, Tawnya; Branchaw, Janet
The Vision and Change in Undergraduate Biology Education: Call to Action report has inspired and supported a nationwide movement to restructure undergraduate biology curricula to address overarching disciplinary concepts and competencies. The report outlines the concepts and competencies generally but does not provide a detailed framework to guide the development of the learning outcomes, instructional materials, and assessment instruments needed to create a reformed biology curriculum. In this essay, we present a detailed Vision and Change core concept framework that articulates key components that transcend subdisciplines and scales for each overarching biological concept, the Conceptual Elements (CE) Framework. The CE Framework was developed using a grassroots approach of iterative revision and incorporates feedback from more than 60 biologists and undergraduate biology educators from across the United States. The final validation step resulted in strong national consensus, with greater than 92% of responders agreeing that each core concept list was ready for use by the biological sciences community, as determined by scientific accuracy and completeness. In addition, we describe in detail how educators and departments can use the CE Framework to guide and document reformation of individual courses as well as entire curricula. PMID:28450444
Oral health is an integral component of overall health and well-being. The human oral cavity is the entry point for all food, the first active step of the human digestive system, and the entry point for many pathogens. Little is known about the physiological and biological processes involved in the
Full Text Available The main goal of the current study is to take advantage of advanced numerical and intelligent tools to predict the speed of a vehicle using time series. It is clear that the uncertainty caused by temporal behavior of the driver as well as various external disturbances on the road will affect the vehicle speed, and thus, the vehicle power demands. The prediction of upcoming power demands can be employed by the vehicle powertrain control systems to improve significantly the fuel economy and emission performance. Therefore, it is important to systems design engineers and automotive industrialists to develop efficient numerical tools to overcome the risk of unpredictability associated with the vehicle speed profile on roads. In this study, the authors propose an intelligent tool called evolutionary least learning machine (E-LLM to forecast the vehicle speed sequence. To have a practical evaluation regarding the efficacy of E-LLM, the authors use the driving data collected on the San Francisco urban roads by a private Honda Insight vehicle. The concept of sliding window time series (SWTS analysis is used to prepare the database for the speed forecasting process. To evaluate the performance of the proposed technique, a number of well-known approaches, such as auto regressive (AR method, back-propagation neural network (BPNN, evolutionary extreme learning machine (E-ELM, extreme learning machine (ELM, and radial basis function neural network (RBFNN, are considered. The performances of the rival methods are then compared in terms of the mean square error (MSE, root mean square error (RMSE, mean absolute percentage error (MAPE, median absolute percentage error (MDAPE, and absolute fraction of variances (R2 metrics. Through an exhaustive comparative study, the authors observed that E-LLM is a powerful tool for predicting the vehicle speed profiles. The outcomes of the current study can be of use for the engineers of automotive industry who have been
Sletten, Sarah Rae
In flipped classrooms, lectures, which are normally delivered in-class, are assigned as homework in the form of videos, and assignments that were traditionally assigned as homework, are done as learning activities in class. It was hypothesized that the effectiveness of the flipped model hinges on a student's desire and ability to adopt a…
Caetano da Costa
Full Text Available To address the usually decontextualized transmission of information in biochemistry teaching, three interventions in a discipline (Metabolism for Biology majors were applied as innovative study guides. We describe the development, application, and evaluation of two study guides, contextualized with a real problem or an integrative view, using broad themes like evolution and metabolic adaptation. In order to evaluate the impact of both interventions on interest, motivation, and learning of the metabolic pathways, a design-based research with cycles of application and assessment was carried out, by means of classroom observation, grade analysis in written exams, and students’ interviews. Analysis and interpretation of the results point to benefits for teaching and learning, with helpful information to guide elaboration and refinement of new teaching materials and to make active learning more meaningful.
Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature; highlights common themes and notable distinctions among methods; and identifies likely directions of future research and open problems in the area. PMID:28570593
Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.
Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405
Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.
Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.
Haapasaari, Päivi Elisabet; Kulmala, Soile; Kuikka, Sakari
of the Baltic salmon stocks, using the Bayesian networks. It enabled the analysis of the outcomes of different management measures from biological, social and economic perspectives. The synthesis was the final output of a learning process of eight years. We reflect how and what kind of interdisciplinarity...... between natural scientists, economists and social scientists grew from the need to better understand complexity related to the salmon fisheries in the Baltic Sea, what we learned about the fishery, and what we learned about interdisciplinary collaboration.......It has been acknowledged that natural sciences cannot provide an adequate basis for the management of complex environmental problems. The scientific knowledge base has to be expanded towards a more holistic direction by incorporating social and economic issues. Besides this, the multifaceted...
Rodríguez, Juan Antonio; Marigorta, Urko M; Navarro, Arcadi
The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles. Copyright © 2014 Elsevier Ltd. All rights reserved.
Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Richter, Caleb; Cha, Kenny
Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p > 0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.
Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Richter, Caleb; Cha, Kenny
Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p > 0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.
Iniesta, Raquel; Stahl, Daniel Richard; McGuffin, Peter
Psychiatric research has entered the age of ‘Big Data’. Datasets now routinely involve thousands of heterogeneous vari- ables, including clinical, neuroimaging, genomic, proteomic, transcriptomic and other ‘omic’ measures. The analysis of these datasets is challenging, especially when the number of measurements exceeds the number of individuals, and may be further complicated by missing data for some subjects and variables that are highly correlated. Statistical learning- based models are a n...
Hacisalihoglu, Gokhan; Stephens, Desmond; Johnson, Lewis; Edington, Maurice
Active learning is a pedagogical approach that involves students engaging in collaborative learning, which enables them to take more responsibility for their learning and improve their critical thinking skills. While prior research examined student performance at majority universities, this study focuses on specifically Historically Black Colleges and Universities (HBCUs) for the first time. Here we present work that focuses on the impact of active learning interventions at Florida A&M University, where we measured the impact of active learning strategies coupled with a SCALE-UP (Student Centered Active Learning Environment with Upside-down Pedagogies) learning environment on student success in General Biology. In biology sections where active learning techniques were employed, students watched online videos and completed specific activities before class covering information previously presented in a traditional lecture format. In-class activities were then carefully planned to reinforce critical concepts and enhance critical thinking skills through active learning techniques such as the one-minute paper, think-pair-share, and the utilization of clickers. Students in the active learning and control groups covered the same topics, took the same summative examinations and completed identical homework sets. In addition, the same instructor taught all of the sections included in this study. Testing demonstrated that these interventions increased learning gains by as much as 16%, and students reported an increase in their positive perceptions of active learning and biology. Overall, our results suggest that active learning approaches coupled with the SCALE-UP environment may provide an added opportunity for student success when compared with the standard modes of instruction in General Biology.
Sitton, Jennifer Susan
Education research has focused on defining and identifying student learning style preferences and how to incorporate this knowledge into teaching practices that are effective in engaging student interest and transmitting information. One objective was determining the learning style preferences of undergraduate students in Biology courses at New Mexico State University by using the online VARK Questionnaire and an investigator developed survey (Self Assessed Learning Style Survey, LSS). Categories include visual, aural, read-write, kinesthetic, and multimodal. The courses differed in VARK single modal learning preferences (p = 0.035) but not in the proportions of the number of modes students preferred (p = 0.18). As elsewhere, the majority of students were multimodal. There were similarities and differences between LSS and VARK results and between students planning on attending medical school and those not. Preferences and modalities tended not to match as expected for ratings of helpfulness of images and text. To detect relationships between VARK preferred learning style and academic performance, ANOVAs were performed using modality preferences and normalized learning gains from pre and post tests over material taught in the different modalities, as well as on end of semester laboratory and lecture grades. Overall, preference did not affect the performance for a given modality based activity, quiz, or final lecture or laboratory grades (p > 0.05). This suggests that a student's preference does not predict an improved performance when supplied with material in that modality. It is recommended that methods be developed to aid learning in a variety of modalities, rather than catering to individual learning styles. Another topic that is heavily debated in the field of education is the use of simulations or videos to replace or supplement dissections. These activities were compared using normalized learning gains from pre and post tests, as well as attitude surveys
Thayer, Bradley A
American social scientists rarely ever use evolutionary concepts to explain behavior, despite the potential of such concepts to elucidate major social problems. I argue that this observation can be understood as the product of three influences: an ideologically narrowed political liberalism; a fear of ''Social Darwinism'' as a scientific idea, rather than a scientific apostasy; and a widely believed criticism of evolutionary thinking as deterministic, reductionistic, and Panglossian. I ask what is to be done to encourage social scientists to learn and to apply evolutionary lessons. I answer with four solutions. First, evolutionary social scientists should more effectively educate their non-evolutionary students and colleagues. Second, they should publicize, even popularize, accessible refutations of perennially misleading criticisms. Third, they should more credibly assure skeptics that evolutionary theory not only keeps the ''social'' in social science but better explains social behavior than can any individual-level theory, such as rational-choice theory. Fourth, they should recall that biology took generations to become Darwinian, and they must understand that the social sciences may take as long to become evolutionary.
Szabó, György; Fáth, Gábor
Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.
Yoon, Susan Anne
Understanding the world through a complex systems lens has recently garnered a great deal of interest in many knowledge disciplines. In the educational arena, interactional studies, through their focus on understanding patterns of system behaviour including the dynamical processes and trajectories of learning, lend support for investigating how a complex systems approach can inform educational research. This study uses previously existing literature and tools for complex systems applications and seeks to extend this research base by exploring learning outcomes of a complex systems framework when applied to curriculum and instruction. It is argued that by applying the evolutionary dynamics of variation, interaction and selection, complexity may be harnessed to achieve growth in both the social and cognitive systems of the classroom. Furthermore, if the goal of education, i.e., the social system under investigation, is to teach for understanding, conceptual knowledge of the kind described in Popper's (1972; 1976) World 3, needs to evolve. Both the study of memetic processes and knowledge building pioneered by Bereiter (cf. Bereiter, 2002) draw on the World 3 notion of ideas existing as conceptual artifacts that can be investigated as products outside of the individual mind providing an educational lens from which to proceed. The curricular topic addressed is the development of an ethical understanding of the scientific and technological issues of genetic engineering. 11 grade 8 students are studied as they proceed through 40 hours of curricular instruction based on the complex systems evolutionary framework. Results demonstrate growth in both complex systems thinking and content knowledge of the topic of genetic engineering. Several memetic processes are hypothesized to have influenced how and why ideas change. Categorized by factors influencing either reflective or non-reflective selection, these processes appear to have exerted differential effects on students
Blackburn, M.R.; Nguyen, H.G.
The objective is to design an artificial vision system for use in robotics applications. Because the desired performance is equivalent to that achieved by nature, the authors anticipate that the objective will be accomplished most efficiently through modeling aspects of the neuroanatomy and neurophysiology of the biological visual system. Information enters the biological visual system through the retina and is passed to the lateral geniculate and optic tectum. The lateral geniculate nucleus (LGN) also receives information from the cerebral cortex and the result of these two inflows is returned to the cortex. The optic tectum likewise receives the retinal information in a context of other converging signals and organizes motor responses. A computer algorithm is described which implements models of the biological visual mechanisms of the retina, thalamic lateral geniculate and perigeniculate nuclei, and primary visual cortex. Motion and pattern analyses are performed in parallel and interact in the cortex to construct perceptions. We hypothesize that motion reflexes serve as unconditioned pathways for the learning and recall of pattern information. The algorithm demonstrates this conditioning through a learning function approximating heterosynaptic facilitation.
Many researchers have called for implementation of active learning practices in undergraduate science classrooms as one method to increase retention and persistence in STEM, yet there has been little research on the potential increases in student anxiety that may accompany these practices. This is of concern because excessive anxiety can decrease student performance. Levels and sources of student anxiety in three introductory biology lecture classes were investigated via an online survey and student interviews. The survey (n = 327) data revealed that 16% of students had moderately high classroom anxiety, which differed among the three classes. All five active learning classroom practices that were investigated caused student anxiety, with students voluntarily answering a question or being called on to answer a question causing higher anxiety than working in groups, completing worksheets, or answering clicker questions. Interviews revealed that student anxiety seemed to align with communication apprehension, social anxiety, and test anxiety. Additionally, students with higher general anxiety were more likely to self-report lower course grade and the intention to leave the major. These data suggest that a subset of students in introductory biology experience anxiety in response to active learning, and its potential impacts should be investigated. PMID:28771564
Yuliana, Sriyati, Siti; Sanjaya, Yayan
Indonesian society is a pluralistic society with different cultures and local potencies that exist in each region. Some of local community still adherethe tradition from generation to generation in managing natural resources wisely. The application of the values of local wisdom is necessary to teach back to student to be more respect the culture and local potentials in the region. There are many ways developing student character by exploring local wisdom and implementing them as a learning resources. This study aims at revealing the values of local wisdom Ngata Toro indigenous people of Central Sulawesi Province in managing forest as a source of learning biology. This research was conducted by in-depth interviews, participant non-observation, documentation studies, and field notes. The data were analyzed with triangulation techniques by using a qualitative interaction analysis that is data collection, data reduction, and data display. Ngata Toro local community manage forest by dividing the forest into several zones, those arewana ngkiki, wana, pangale, pahawa pongko, oma, and balingkea accompanied by rules in the management of result-based forest conservation and sustainable utilization. By identifying the purpose of zonation and regulation of the forest, such values as the value of environmental conservation, balance value, sustainable value, and the value of mutual cooperation. These values are implemented as a biological learning resource which derived from the competences standard of analyze the utilization and conservation of the environment.
This study explored three aspects related to ESL students in a mainstream grade 11 biology classroom: (1) the nature of students' participation in classroom activities, (2) the factors that enhanced or constrained ESL students' engagement in social interactions, and (3) the role of language in the learning of science. Ten ESL students were observed over an eight-month period in this biology classroom. Data were collected using qualitative research methods such as participant observation, audio-recordings of lessons, field notes, semi-structured interviews, short lesson recall interviews and students' written work. The study was framed within sociocultural perspectives, particularly the social constructivist perspectives of Vygotsky (1962, 1978) and Wertsch (1991). Data were analysed with respect to the three research aspects. Firstly, the findings showed that ESL students' preferred and exhibited a variety of participation practices that ranged from personal-individual to socio-interactive in nature. Both personal-individual and socio-interactive practices appeared to support science and language learning. Secondly, the findings indicated that ESL students' engagement in classroom social interactions was most likely influenced by the complex interactions between a number of competing factors at the individual, interpersonal and community/cultural levels (Rogoff, Radziszewska, & Masiello, 1995). In this study, six factors that appeared to enhance or constrain ESL students' engagement in classroom social interactions were identified. These factors were socio-cultural factors, prior classroom practice, teaching practices, affective factors, English language proficiency, and participation in the research project. Thirdly, the findings indicated that language played a significant mediational role in ESL students' learning of science. The data revealed that the learning of science terms and concepts can be explained by a functional model of language that includes: (1
Van Rooy, Wilhelmina S.
Background: The ubiquity, availability and exponential growth of digital information and communication technology (ICT) creates unique opportunities for learning and teaching in the senior secondary school biology curriculum. Digital technologies make it possible for emerging disciplinary knowledge and understanding of biological processes…
Cooper, Katelyn M.; Brownell, Sara E.
As we transition our undergraduate biology classrooms from traditional lectures to active learning, the dynamics among students become more important. These dynamics can be influenced by student social identities. One social identity that has been unexamined in the context of undergraduate biology is the spectrum of lesbian, gay, bisexual,…
Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar
Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.
Schrodt, Fabian; Layher, Georg; Neumann, Heiko; Butz, Martin V
Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons.
Full Text Available Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons.
Emerling, Christopher A
Regressive evolution of anatomical traits often corresponds with the regression of genomic loci underlying such characters. As such, studying patterns of gene loss can be instrumental in addressing questions of gene function, resolving conflicting results from anatomical studies, and understanding the evolutionary history of clades. The evolutionary origins of snakes involved the regression of a number of anatomical traits, including limbs, taste buds and the visual system, and by analyzing serpent genomes, I was able to test three hypotheses associated with the regression of these features. The first concerns two keratins that are putatively specific to claws. Both genes that encode these keratins are pseudogenized/deleted in snake genomes, providing additional evidence of claw-specificity. The second hypothesis is that snakes lack taste buds, an issue complicated by conflicting results in the literature. I found evidence that different snakes have lost one or more taste receptors, but all snakes examined retained at least one gustatory channel. The final hypothesis addressed is that the earliest snakes were adapted to a dim light niche. I found evidence of deleted and pseudogenized genes with light-associated functions in snakes, demonstrating a pattern of gene loss similar to other dim light-adapted clades. Molecular dating estimates suggest that dim light adaptation preceded the loss of limbs, providing some bearing on interpretations of the ecological origins of snakes. Copyright © 2017 Elsevier Inc. All rights reserved.
Ricardo Ferreira das Neves
Full Text Available The research aimed to analyze the didactic value (VD of the images related to the concept of cell in biology books of High School and Higher Education, supported by Cognitivist Theory of Multimedia Learning (TCAM. With the technological advent there was a better development of the layout of production techniques and layout of the images in books, in order to help the study of abstract concepts and often complex, such as the cell. However sometimes it not happens. From the application of TCAM principles, we noted that the images related to cell concept presented VD elements with deviations on the principles of Consistency, Signaling and Spatial Contiguity, with great emphasis to the last one. It is necessary to establish eligibility criteria and inclusion of images in books, because the images represent potential resource to reduce abstraction and to facilitate conceptual learning.
Costa, C ; Galembeck, E. Costa, C ; Galembeck, E.
Full Text Available One of the difficulties for biochemistry learning is the persistence of traditional teaching methods, based on transmission and memorization of abstract and detailed information, usually in a decontextualized way. Such scenario results in surface learning and content reproduction. In order to address these problems, three interventions in a discipline (Metabolism for Biology majors were applied, in the form of innovative teaching tools (study guides. OBJECTIVES: The main goal is to evaluate the impact of these interventions on interest, motivation, and learning of the metabolic pathways. MATERIALS AND METHODS: We describe the development, application, and evaluation of two study guides – one created from a problem used as a contextual connection for glycogen metabolism study and another embedding an integrative view based on glutamate metabolism. Both materials were guided by broad themes like evolution, metabolic adaptation, and comparative biochemistry. The development of the study guides combined submicroscopic (molecular and macroscopic (body, environment levels, aiming to motivate reading and discussion. A design-based research with cycles of application and assessment was carried out, by means of classroom observation, grade analysis in written exams, and students’ interviews. RESULTS AND DISCUSSION: In general, based on in-class student feedback to professors and to the researcher in the interviews, the study guides arouse curiosity and fostered peer discussion. Final average grades indicate a good global performance in all proposed activities. Whole data from study guides’ application in classroom evidenced their impact on interest, motivation, and learning. The strategy of developing problem or integrative situation linking molecular (micro and contextual (macro levels were helpful to foster critical thinking and to value topics of scientific literacy. CONCLUSIONS: Analysis and interpretation of the results point to benefits for
Hawley, Wayne R; Grissom, Elin M; Barratt, Harriet E; Conrad, Taylor S; Dohanich, Gary P
When learning to navigate toward a goal in a spatial environment, rodents employ distinct learning strategies that are governed by specific regions of the brain. In the early stages of learning, adult male rats prefer a hippocampus-dependent place strategy over a striatum-dependent response strategy. Alternatively, female rats exhibit a preference for a place strategy only when circulating levels of estradiol are elevated. Notably, male rodents typically perform better than females on a variety of spatial learning tasks, which are mediated by the hippocampus. However, limited research has been done to determine if the previously reported male spatial advantage corresponds with a greater reliance on a place strategy, and, if the male preference for a place strategy is impacted by removal of testicular hormones. A dual-solution water T-maze task, which can be solved by adopting either a place or a response strategy, was employed to determine the effects of biological sex and hormonal status on learning strategy. In the first experiment, male rats made more correct arm choices than female rats during training and exhibited a bias for a place strategy on a probe trial. The results of the second experiment indicated that testicular hormones modulated arm choice accuracy during training, but not the preference for a place strategy. Together, these findings suggest that the previously reported male spatial advantage is associated with a greater reliance on a place strategy, and that only performance during the training phase of a dual-solution learning task is impacted by removal of testicular hormones. Copyright © 2011 Elsevier Inc. All rights reserved.
Drier, Yotam; Domany, Eytan
The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.
Full Text Available The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.
Sarantopoulos, Helen D.
Purpose. The purpose of this study was to identify, according to the Productivity Environment Preference Survey (PEPS) instrument, which learning-style domains (environmental, emotional, sociological, and physiological) were favored among Latino/Hispanic community college students enrolled in introductory biology classes in a large, urban community college. An additional purpose of this study was to determine whether statistically significant differences existed between the learning-style preferences and the demographic variables of age, gender, number of prior science courses, second language learner status, and earlier exposure to scientific information. Methodology. The study design was descriptive and ex post facto. The sample consisted of a total of 332 Latino/Hispanic students enrolled in General Biology 3. Major findings. The study revealed that Latino/Hispanic students enrolled in introductory biology at a large urban community college scored higher for the learning preference element of structure. Students twenty-five years and older scored higher for the learning preference elements of light, design, persistence, responsibility, and morning time (p learning-style preferences were found between second English language learners and those who learned English as their primary language (p tactile (p learning-style model and instruments and on recent learning-style research articles on ethnically diverse groups of adult learners; and (2) Instructors should plan their instruction to incorporate the learning-style preferences of their students.
Mating systems in caridean shrimp (Decapoda: Caridea and their evolutionary consequences for sexual dimorphism and reproductive biology Sistemas de apareamiento en camarones carideos (Decapoda: Caridea y sus consecuencias evolutivas en el dimorfismo sexual y biología reproductiva
Full Text Available In this paper we review functional and evolutionary relationships among mating systems of caridean shrimp and specific traits such as general biology/ecology, sexual systems, behavior and morphology. Four mating systems are described based on reports from available literature, and a fifth system is recognized but published information is insufficient to describe it in detail. `Monogamy' occurs in many species inhabiting monopolizable refuges or hosts, especially when environmental conditions restrict the probability of intraspecific interactions. In contrast, free-living species experience higher encounter rates and males can dominate or search. In `neighborhoods of dominance' mating systems, large males have higher reproductive success since they perform better in fights for receptive females. In `pure searching' mating systems, small and agile males do better because they search more efficiently for mates within the population. The fourth mating system is `search & attend' occurring in solitary symbionts, which experience variable ecological and demographic environments: depending on environmental conditions and ontogenetic stages it may either be profitable for males to search or to attend hosts with sexually attractive females. Sexual systems of caridean shrimp are characterized by their high diversity and intraspecific plasticity, including gonochorism and different forms of protandric or simultaneous hermaphroditism. The identified mating systems partially explained this diversity: In monogamous species, low encounter rates and lack of sexual dimorphism favors simultaneous hermaphroditism but gonochory usually occurs among these species probably because mates are not strictly faithful. Species with neighborhoods of dominance mating are gonochoristic because both sexes benefit from being large. Pure searching species have a wide opportunity for the evolution of protandry since small males benefit while the opposite is true for females. In
Van Rooy, Wilhelmina S.
Background: The ubiquity, availability and exponential growth of digital information and communication technology (ICT) creates unique opportunities for learning and teaching in the senior secondary school biology curriculum. Digital technologies make it possible for emerging disciplinary knowledge and understanding of biological processes previously too small, large, slow or fast to be taught. Indeed, much of bioscience can now be effectively taught via digital technology, since its representational and symbolic forms are in digital formats. Purpose: This paper is part of a larger Australian study dealing with the technologies and modalities of learning biology in secondary schools. Sample: The classroom practices of three experienced biology teachers, working in a range of NSW secondary schools, are compared and contrasted to illustrate how the challenges of limited technologies are confronted to seamlessly integrate what is available into a number of molecular genetics lessons to enhance student learning. Design and method: The data are qualitative and the analysis is based on video classroom observations and semi-structured teacher interviews. Results: Findings indicate that if professional development opportunities are provided where the pedagogy of learning and teaching of both the relevant biology and its digital representations are available, then teachers see the immediate pedagogic benefit to student learning. In particular, teachers use ICT for challenging genetic concepts despite limited computer hardware and software availability. Conclusion: Experienced teachers incorporate ICT, however limited, in order to improve the quality of student learning.
Full Text Available The article analyzes the extent to which predictions based on the theory of evolutionary aesthetics are utilized by the advertising industry. The purpose of a comprehensive content analysis of print advertising is to determine whether the items indicated by evolutionists such as animals, flowers, certain types of landscapes, beautiful humans, and some colors are part of real advertising strategies. This article has shown that many evolutionary hypotheses (although not all of them are supported by empirical data. Along with these hypotheses, some inferences from Bourdieu’s cultural capital theory were tested. It turned out that advertising uses both biological schemata and cultural patterns to make an image more likable.
This study aims to determine the effectiveness of the model KNOS-KGS, to improve the learning outcomes of Biology at the ecosystem material in class X SMA PGRI 1 Banjarmasin. This research is a classroom action research, conducted in two cycles. Each cycle is done with two meetings. This study was conducted on 25 students in class X1. The research data is the result of student learning that consists of cognitive learning outcomes such as pretest and posttest. Affective learning outcomes such ...
Catley, Kefyn M.; Novick, Laura R.; Shade, Courtney K.
The authors argue that some diagrams in biology textbooks and the popular press presented as depicting evolutionary relationships suggest an inappropriate (anagenic) conception of evolutionary history. The goal of this research was to provide baseline data that begin to document how college students conceptualize the evolutionary relationships…
Full Text Available The emergence of -omics technologies has allowed the collection of vast amounts of data on biological systems. Although the pace of such collection has been exponential, the impact of these data remains small on many critical biomedical applications such as drug development. Limited resources, high costs and low hit-to-lead ratio have led researchers to search for more cost effective methodologies. A possible alternative is to incorporate computational methods of potential drug target prediction early during drug discovery workflow. Computational methods based on systems approaches have the advantage of taking into account the global properties of a molecule not limited to its sequence, structure or function. Machine learning techniques are powerful tools that can extract relevant information from massive and noisy data sets. In recent years the scientific community has explored the combined power of these fields to propose increasingly accurate and low cost methods to propose interesting drug targets. In this mini-review, we describe promising approaches based on the simultaneous use of systems biology and machine learning to access gene and protein druggability. Moreover, we discuss the state-of-the-art of this emerging and interdisciplinary field, discussing data sources, algorithms and the performance of the different methodologies. Finally, we indicate interesting avenues of research and some remaining open challenges.
Shimansky, Yury P
Learning processes in the brain are usually associated with plastic changes made to optimize the strength of connections between neurons. Although many details related to biophysical mechanisms of synaptic plasticity have been discovered, it is unclear how the concurrent performance of adaptive modifications in a huge number of spatial locations is organized to minimize a given objective function. Since direct experimental observation of even a relatively small subset of such changes is not feasible, computational modeling is an indispensable investigation tool for solving this problem. However, the conventional method of error back-propagation (EBP) employed for optimizing synaptic weights in artificial neural networks is not biologically plausible. This study based on computational experiments demonstrated that such optimization can be performed rather efficiently using the same general method that bacteria employ for moving closer to an attractant or away from a repellent. With regard to neural network optimization, this method consists of regulating the probability of an abrupt change in the direction of synaptic weight modification according to the temporal gradient of the objective function. Neural networks utilizing this method (regulation of modification probability, RMP) can be viewed as analogous to swimming in the multidimensional space of their parameters in the flow of biochemical agents carrying information about the optimality criterion. The efficiency of RMP is comparable to that of EBP, while RMP has several important advantages. Since the biological plausibility of RMP is beyond a reasonable doubt, the RMP concept provides a constructive framework for the experimental analysis of learning in natural neural networks.
Didimus Tanah Boleng
Full Text Available Pengaruh Model Pembelajaran Cooperative Script dan Think-Pair-Share terhadap Keterampilan Berpikir Kritis, Sikap Sosial, dan Hasil Belajar Kognitif Biologi Siswa SMA Multietnis Abstract: Biological learning process with multiethnic students requires a learning models which allow students to work independently, to work together in small groups, and to share with other groups. The purpose of this study was to determine the effect of learning models, ethnicity, and the interaction of learning model and ethnic on critical thinking skills, social attitudes, and cognitive achievement. This quasi experimental study was conducted in 11th grade of Natural Science Class Highschool students with six ethnicaly and Junior Highschool National score groups consisted of 132 samples. The results of Covarian Analysis showed that the learning models significantly affected the social attitudes and increased the critical thinking skills and cognitive achievement. Ethnicity significantly affected the social attitudes and cognitive achievement. Interaction of learning models and ethnicity significantly affected students social attitudes. Key Words: cooperative script, think-pair-share, critical thinking skills, social attitudes, biology cognitive achievement, multiethnic students Abstrak: Pengelolaan proses pembelajaran biologi pada siswa multietnis memerlukan model pembelajaran yang memungkinkan siswa bekerja mandiri, bekerja sama dalam kelompok kecil, dan berbagi dengan kelompok lain. Tujuan penelitian ini untuk mengetahui pengaruh model pembelajaran, etnis, serta interaksi model pembelajaran dan etnis terhadap keterampilan berpikir kritis, sikap sosial, dan hasil belajar kognitif biologi siswa. Penelitian eksperimen semu ini dilakukan di kelas XI IPA SMA dengan sampel sebanyak 132 orang siswa terbagi dalam enam kelas yang homogen berdasarkan etnis dan nilai ujian nasional SMP siswa. Hasil analisis data dengan menggunakan Analisis Kovarian menunjukkan bahwa model
Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high
Ploeger, A.; van der Maas, H.L.J.; Raijmakers, M.E.J.
Evolutionary psychology has been proposed as a metatheoretical framework for psychology. We argue that evolutionary psychology should be expanded if it is to offer new insights regarding the major issues in psychology. Evolutionary developmental biology can provide valuable new insights into issues
Chacon Diaz, Lucia Bernardette
Science teaching and learning in higher education has been evolving over the years to encourage student retention in STEM fields and reduce student attrition. As novel pedagogical practices emerge in the college science classroom, research on the effectiveness of such approaches must be undertaken. The following research applied a case study research design in order to evaluate the experiences of college students in a TEAL classroom. This case study was conducted during the 2017 Summer Cellular and Organismal Biology course at a four-year Hispanic Serving Institution located in the Southwest region of the United States. The main components evaluated were students' exam performance, self-efficacy beliefs, and behaviors and interactions in the Technology-Enhanced Active Learning (TEAL) classroom. The findings suggest that students enrolled in a TEAL classroom are equally capable of answering high and low order thinking questions. Additionally, students are equally confident in answering high and low order thinking items related to cellular biology. In the TEAL classroom, student-student interactions are encouraged and collaborative behaviors are exhibited. Gender and ethnicity do not influence self-efficacy beliefs in students in the TEAL room, and the overall class average of self-efficacy beliefs tended to be higher compared to exam performance. Based on the findings of this case study, TEAL classrooms are greatly encouraged in science higher education in order to facilitate learning and class engagement for all students. Providing students with the opportunity to expand their academic talents in the science classroom accomplishes a crucial goal in STEM higher education.
McCoy, Roger Wesley
Statement of the problem. Few studies in biology education have examined the underlying presuppositions which guide thinking and concept learning in adolescents. The purpose of this study was to describe and understand the biological world views of a variety of high school students before they take biology courses. Specifically, the study examined student world views in the domains of Classification, Relationship and Causation related to the concepts of heredity, evolution and biotechnology. The following served as guiding questions: (1) What are the personal world views of high school students entering biology classes, related to the domain of Classification, Relationship and Causality? (2) How do these student world views confound or enhance the learning of basic concepts in genetics and evolution? Methods. An interpretive method was chosen for this study. The six student participants were ninth graders and represented a wide range of world view backgrounds. A series of three interviews was conducted with each participant, with a focus group used for triangulation of data. The constant comparative method was used to categorize the data and facilitate the search for meaningful patterns. The analysis included a thick description of each student's personal views of classification, evolution and the appropriate use of biotechnology. Results. The study demonstrates that world view is the basis upon which students build knowledge in biology. The logic of their everyday thinking may not match that of scientists. The words they use are sometimes inconsistent with scientific terminology. This study provides evidence that students voice different opinions depending on the social situation, since they are strongly influenced by peers. Students classify animals based on behaviors. They largely believe that the natural world is unpredictable, and that humans are not really part of that world. Half are unlikely to accept the evolution of humans, but may accept it in other
Armbruster, Peter; Patel, Maya; Johnson, Erika; Weiss, Martha
We describe the development and implementation of an instructional design that focused on bringing multiple forms of active learning and student-centered pedagogies to a one-semester, undergraduate introductory biology course for both majors and nonmajors. Our course redesign consisted of three major elements: 1) reordering the presentation of the course content in an attempt to teach specific content within the context of broad conceptual themes, 2) incorporating active and problem-based learning into every lecture, and 3) adopting strategies to create a more student-centered learning environment. Assessment of our instructional design consisted of a student survey and comparison of final exam performance across 3 years-1 year before our course redesign was implemented (2006) and during two successive years of implementation (2007 and 2008). The course restructuring led to significant improvement of self-reported student engagement and satisfaction and increased academic performance. We discuss the successes and ongoing challenges of our course restructuring and consider issues relevant to institutional change.
Beyeler, Michael; Rokem, Ariel; Boynton, Geoffrey M.; Fine, Ione
The ‘bionic eye’—so long a dream of the future—is finally becoming a reality with retinal prostheses available to patients in both the US and Europe. However, clinical experience with these implants has made it apparent that the visual information provided by these devices differs substantially from normal sight. Consequently, the ability of patients to learn to make use of this abnormal retinal input plays a critical role in whether or not some functional vision is successfully regained. The goal of the present review is to summarize the vast basic science literature on developmental and adult cortical plasticity with an emphasis on how this literature might relate to the field of prosthetic vision. We begin with describing the distortion and information loss likely to be experienced by visual prosthesis users. We then define cortical plasticity and perceptual learning, and describe what is known, and what is unknown, about visual plasticity across the hierarchy of brain regions involved in visual processing, and across different stages of life. We close by discussing what is known about brain plasticity in sight restoration patients and discuss biological mechanisms that might eventually be harnessed to improve visual learning in these patients.
Numerous psychological, biological, and evolutionary theories have been proposed to explain sexual orientation. For a theory to be valid it must account for the evolutionary or Darwinian paradox of how homosexual behavior seemingly blocking evolutionary fitness could have evolved. Typically it is only evolutionary based theories that attempt to address this issue. All theories proposed to date have limitations, a major one being that they tend to be specific for male or female sexual orientat...
Hendry, Andrew P; Kinnison, Michael T; Heino, Mikko; Day, Troy; Smith, Thomas B; Fitt, Gary; Bergstrom, Carl T; Oakeshott, John; Jørgensen, Peter S; Zalucki, Myron P; Gilchrist, George; Southerton, Simon; Sih, Andrew; Strauss, Sharon; Denison, Robert F; Carroll, Scott P
Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology.
Ubonwan Leawudomchai; Kittima Panprueksa; Somsiri Singlop; Thanawuth Latwong
The objectives of this research were to study learning achievement and learning behavior in Biology on “genes and chromosomes” using storyline teaching for 12th grade students. The sample for this research consisted of 36 twelfth grade students from Piboonbumpen Demonstration School in the first semester of 2014. The sample was randomly selected for the experimental group using cluster random sampling. The research instruments were the lesson plans using storyline teaching on g...
Otulaja, Femi Segun
The body of research work presented in this dissertation integrates critical ethnography with video and conversation analyses in order to provide ways to articulate and understand the complexities associated with social life enactment as it unfolds during cogenerative dialogues and in the science classroom as the teacher and her students engage in science teaching and learning. The primary goal is to improve the teaching and learning of science in an urban science classroom at a public high school in Philadelphia, Pennsylvania. In order to understand what is going on in the classroom and why, I worked with a female science teacher who identify as an African-American and her culturally diversified students in a biology class to examine teacher's and students' conscious and unconscious patterned actions, (i.e., classroom practices, that structure teaching and learning in the classroom. It is my belief that to improve science teaching and learning in the classroom, it is salient to improve science teacher's practices as a precursor to transforming students' practices. In order to ameliorate breaches in the fluency of encounters in the classroom, the teacher and her students need to establish and sustain critical, collaborative and collective conversations through cogen. I employ theoretical lenses of cultural sociology that I triangulate with sociology of emotions and critical pedagogy. I focus on culture as schemas and associated practices layered with the triple dialectics of agency, passivity and structure as new or hybridized/interstitial cultures that are produced get enacted in the science classroom to transform teacher's and her students' encounters with each other. The salient implication is that since encounters are imbued with emotions, teacher and her students learn to generate positive emotional energy during cogen that gets reproduced and transformed in the science classroom. Positive emotional energy creates resources that help to initiate and sustain
Darwin's principle of evolution by natural selection is readily casted into a mathematical formalism. Molecular biology revealed the mechanism of mutation and provides the basis for a kinetic theory of evolution that models correct reproduction and mutation as parallel chemical reaction channels. A result of the kinetic theory is the existence of a phase transition in evolution occurring at a critical mutation rate, which represents a localization threshold for the population in sequence space. Occurrence and nature of such phase transitions depend critically on fitness landscapes. The fitness landscape being tantamount to a mapping from sequence or genotype space into phenotype space is identified as the true source of complexity in evolution. Modeling evolution as a stochastic process is discussed and neutrality with respect to selection is shown to provide a major challenge for understanding evolutionary processes (author)
Ganea, Patricia A; Ma, Lili; Deloache, Judy S
Preschool children (N = 104) read a book that described and illustrated color camouflage in animals (frogs and lizards). Children were then asked to indicate and explain which of 2 novel animals would be more likely to fall prey to a predatory bird. In Experiment 1, 3- and 4-year-olds were tested with pictures depicting animals in camouflage and noncamouflage settings; in Experiment 2, 4-year-olds were tested with real animals. The results show that by 4 years of age, children can learn new biological facts from a picture book. Of particular importance, transfer from books to real animals was found. These findings point to the importance that early book exposure can play in framing and increasing children's knowledge about the world. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.
Snyder, Julia J; Wiles, Jason R
This study evaluated hypothesized effects of the Peer-Led Team Learning (PLTL) instructional model on undergraduate peer leaders' critical thinking skills. This investigation also explored peer leaders' perceptions of their critical thinking skills. A quasi-experimental pre-test/post-test with control group design was used to determine critical thinking gains in PLTL/non-PLTL groups. Critical thinking was assessed using the California Critical Thinking Skills Test (CCTST) among participants who had previously completed and been successful in a mixed-majors introductory biology course at a large, private research university in the American Northeast. Qualitative data from open-ended questionnaires confirmed that factors thought to improve critical thinking skills such as interaction with peers, problem solving, and discussion were perceived by participants to have an impact on critical thinking gains. However, no significant quantitative differences in peer leaders' critical thinking skills were found between pre- and post-experience CCTST measurements or between experimental and control groups.
Marisa Laporta Chudo; Maria Cecília Sonzogno
Objective. To analyze the teach-learning process of high school students, in the scope of Educational Biology. To plan and to develop a methodology with lesson strategies that facilitate the learning. To analyze, in the students vision, the positive and negative points in the process. Method. A research was developed -- of which had participated students of the first semester of the Pedagogy of a high school private institution in São Paulo city -- of the type action-research, with increased ...
Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David
Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.
Malacinski, George M
In this junior-level undergraduate course, developmental life cycles exhibited by various organisms are reviewed, with special attention--where relevant--to the human embryo. Morphological features and processes are described and recent insights into the molecular biology of gene expression are discussed. Ways are studied in which model systems, including marine invertebrates, amphibia, fruit flies and other laboratory species are employed to elucidate general principles which apply to fertilization, cleavage, gastrulation and organogenesis. Special attention is given to insights into those topics which will soon be researched with data from the Human Genome Project. The learning experience is divided into three parts: Part I is a in which the Socratic (inquiry) method is employed by the instructor (GMM) to organize a review of classical developmental phenomena; Part II represents an in which students study the details related to the surveys included in Part I as they have been reported in research journals; Part III focuses on a class project--the preparation of a spiral bound on a topic of relevance to human developmental biology (e.g.,Textbook of Embryonal Stem Cells). Student response to the use of the Socratic method increases as the course progresses and represents the most successful aspect of the course.
Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth
The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. firstname.lastname@example.org or email@example.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: firstname.lastname@example.org
Bravo, Paulina; Cofré, Hernán
This work explores how pedagogical content knowledge (PCK) on evolution was modified by two biology teachers who participated in a professional development programme (PDP) that included a subsequent follow-up in the classroom. The PDP spanned a semester and included activities such as content updates, collaborative lesson planning, and the presentation of planned lessons. In the follow-up part, the lessons were videotaped and analysed, identifying strategies, activities, and conditions based on student learning about the theory of evolution. Data were collected in the first round with an interview before the training process, identifying these teachers' initial content representation (CoRe) for evolution. Then, a group interview was conducted after the lessons, and, finally, an interview of stimulated recall with each teacher was conducted regarding the subject taught to allow teachers to reflect on their practice (final CoRe). This information was analysed by the teachers and the researchers, reflecting on the components of the PCK, possible changes, and the rationale behind their actions. The results show that teachers changed their beliefs and knowledge about the best methods and strategies to teach evolution, and about students' learning obstacles and misconceptions on evolution. They realised how a review of their own practices promotes this transformation.
Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra
The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.
Rahmawati, D.; Sajidan; Ashadi
Problem solving is a critical component of comprehensive learning in 21st century. Problem solving is defined as a process used to obtain the best answer from a problem. Someone who can solve the problem is called a problem solver. Problem solver obtains many benefits in the future and has a chance to be an innovator, such as be an innovative entrepreneur, modify behavior, improve creativity, and cognitive skills. The goal of this research is to analyze problem solving skills of students in Senior High School Surakarta in learning Biology. Participants of this research were students of grade 12 SMA (Senior High School) N Surakarta. Data is collected by using multiple choice questions base on analysis problem solving skills on Mourtus. The result of this research showed that the percentage of defining problem was 52.38%, exploring the problem was 53.28%, implementing the solution was 50.71% for 50.08% is moderate, while the percentage of designing the solution was 34.42%, and evaluating was low for 39.24%. Based on the result showed that the problem solving skills of students in SMAN Surakarta was Low.
Costa-Silva, Daniela; Côrtes, Juliana A; Bachinski, Rober F; Spiegel, Carolina N; Alves, Gutemberg G
Although the discipline of cell biology (CB) is part of the curricula of predoctoral dental schools, students often fail to recognize its practical relevance. The aim of this study was to assess the effectiveness of a practical-theoretical project-based course in closing the gaps among CB, scientific research, and dentistry for dental students. A project-based learning course was developed with nine sequential lessons to evaluate 108 undergraduate dental students enrolled in CB classes of a Brazilian school of dentistry during 2013-16. To highlight the relevance of in vitro studies in the preclinical evaluation of dental materials at the cellular level, the students were challenged to complete the process of drafting a protocol and performing a cytocompatibility assay for a bone substitute used in dentistry. Class activities included small group discussions, scientific database search and article presentations, protocol development, lab experimentation, and writing of a final scientific report. A control group of 31 students attended only one laboratory class on the same theme, and the final reports were compared between the two groups. The results showed that the project-based learning students had superior outcomes in acknowledging the relevance of in vitro methods during biocompatibility testing. Moreover, they produced scientifically sound reports with more content on methodological issues, the relationship with dentistry, and the scientific literature than the control group (p<0.05). The project-based learning students also recognized a higher relevance of scientific research and CB to dental practice. These results suggest that a project-based approach can help contextualize scientific research in dental curricula.
Zena M Hira
Full Text Available Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap.
regulation. We wish to ascertain whether we can identify such genes promptly in a comprehensive manner. The ease of manipulation using the zebrafish system allows us to conduct an exhaustive exploration of novel genes and small molecular compounds that can be linked to the senescence phenotype and thereby facilitates searching for the evolutionary and developmental origins of aging in vertebrates. Copyright © 2011 Wiley-Liss, Inc.
Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D
Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.
Lebec, Michael Thomas
Due to discipline specific shortages, web-based learning has been proposed as a convenient way to upgrade the content knowledge of instructors interested in learning to teach science. Despite quantitative evidence that web-based instruction is equivalent to traditional methods, questions remain regarding its use. The efficiency and practicality of this approach with teachers in particular has not been extensively studied. This investigation examines learning in an online biology course designed to help teachers prepare for science certification exams. Research questions concern flow teachers learn biology in the online environment and how this setting influences the learning process. Quantitative and qualitative methodologies are employed in an attempt to provide a more complete perspective than typical studies of online learning. Concept maps, tests, and online discussion transcripts are compared as measures of assimilated knowledge, while interviews reflect participants' views on the course. Findings indicate that participants experienced gains in declarative knowledge, but little improvement with respect to conditional knowledge. Qualitative examination of concept maps demonstrates gaps in participants' understandings of key course ideas. Engagement in the use of online resources varied according to participants' attitudes towards online learning. Subjects also reported a lack of motivation to fully engage in the course due to busy teaching schedules and the absence of accountability.
Full Text Available Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A pivotal feature of the evolutionary approach is that it considers the whole robot at once, and enables the exploitation of robot features in a holistic manner. Evolutionary robotics can also be seen as an innovative approach to the study of evolution based on a new kind of experimentalism. The use of robots as a substrate can help address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies. In this paper we consider the main achievements of evolutionary robotics, focusing particularly on its contributions to both engineering and biology. We briefly elaborate on methodological issues, review some of the most interesting findings, and discuss important open issues and promising avenues for future work.
Joosten, Reinoud A.M.G.; Roorda, Berend
We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary
This thesis describes a research project that was carried out at the Centre for Science and Mathematics Education at Utrecht University between 1998 and 2002. The study addresses problems in learning and teaching genetics in upper secondary biology education. The aim of the study is to develop a
Based on the assumption that most students have a natural curiosity about the plant and animal life residing in the oceans, this document provides students in grades five through eight with activities in marine biology. The book provides illustrated information and learning activities dealing with: (1) diatoms; (2) the life cycle of the jellyfish;…
Nixon, Brenda Chaumont
This study evaluated the cognitive benefits and costs of incorporating biology-textbook and student-generated photographic images into the learning and assessment processes within a 10th grade biology classroom. The study implemented Wandersee's (2000) 20-Q Model of Image-Based Biology Test-Item Design (20-Q Model) to explore the use of photographic images to assess students' understanding of complex biological processes. A thorough review of the students' textbook using ScaleMaster R with PC Interface was also conducted. The photographs, diagrams, and other representations found in the textbook were measured to determine the percentage of each graphic depicted in the book and comparisons were made to the text. The theoretical framework that guided the research included Human Constructivist tenets espoused by Mintzes, Wandersee and Novak (2000). Physiological and cognitive factors of images and image-based learning as described by Robin (1992), Solso (1997) and Wandersee (2000) were examined. Qualitative case study design presented by Yin (1994), Denzin and Lincoln (1994) was applied and data were collected through interviews, observations, student activities, student and school artifacts and Scale Master IIRTM measurements. The results of the study indicate that although 24% of the high school biology textbook is devoted to photographic images which contribute significantly to textbook cost, the teacher and students paid little attention to photographic images other than as aesthetic elements for creating biological ambiance, wasting valuable opportunities for learning. The analysis of the photographs corroborated findings published by the Association American Association for the Advancement of Science that indicated "While most of the books are lavishly illustrated, these representations are rarely helpful, because they are too abstract, needlessly complicated, or inadequately explained" (Roseman, 2000, p. 2). The findings also indicate that applying the 20-Q
In this article, I argue that distinguishing 'evolutionary' from 'Darwinian' medicine will help us assess the variety of roles that evolutionary explanations can play in a number of medical contexts. Because the boundaries of evolutionary and Darwinian medicine overlap to some extent, however, they are best described as distinct 'research traditions' rather than as competing paradigms. But while evolutionary medicine does not stand out as a new scientific field of its own, Darwinian medicine is united by a number of distinctive theoretical and methodological claims. For example, evolutionary medicine and Darwinian medicine can be distinguished with respect to the styles of evolutionary explanations they employ. While the former primarily involves 'forward looking' explanations, the latter depends mostly on 'backward looking' explanations. A forward looking explanation tries to predict the effects of ongoing evolutionary processes on human health and disease in contemporary environments (e.g., hospitals). In contrast, a backward looking explanation typically applies evolutionary principles from the vantage point of humans' distant biological past in order to assess present states of health and disease. Both approaches, however, are concerned with the prevention and control of human diseases. In conclusion, I raise some concerns about the claim that 'nothing in medicine makes sense except in the light of evolution'.
Hayes, Spencer J; Dutoy, Chris A; Elliott, Digby; Gowen, Emma; Bennett, Simon J
Learning a novel movement requires a new set of kinematics to be represented by the sensorimotor system. This is often accomplished through imitation learning where lower-level sensorimotor processes are suggested to represent the biological motion kinematics associated with an observed movement. Top-down factors have the potential to influence this process based on the social context, attention and salience, and the goal of the movement. In order to further examine the potential interaction between lower-level and top-down processes in imitation learning, the aim of this study was to systematically control the mediating effects during an imitation of biological motion protocol. In this protocol, we used non-human agent models that displayed different novel atypical biological motion kinematics, as well as a control model that displayed constant velocity. Importantly the three models had the same movement amplitude and movement time. Also, the motion kinematics were displayed in the presence, or absence, of end-state-targets. Kinematic analyses showed atypical biological motion kinematics were imitated, and that this performance was different from the constant velocity control condition. Although the imitation of atypical biological motion kinematics was not modulated by the end-state-targets, movement time was more accurate in the absence, compared to the presence, of an end-state-target. The fact that end-state targets modulated movement time accuracy, but not biological motion kinematics, indicates imitation learning involves top-down attentional, and lower-level sensorimotor systems, which operate as complementary processes mediated by the environmental context. Copyright © 2015 Elsevier B.V. All rights reserved.
Cooper, Katelyn M; Brownell, Sara E
As we transition our undergraduate biology classrooms from traditional lectures to active learning, the dynamics among students become more important. These dynamics can be influenced by student social identities. One social identity that has been unexamined in the context of undergraduate biology is the spectrum of lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQIA) identities. In this exploratory interview study, we probed the experiences and perceptions of seven students who identify as part of the LGBTQIA community. We found that students do not always experience the undergraduate biology classroom to be a welcoming or accepting place for their identities. In contrast to traditional lectures, active-learning classes increase the relevance of their LGBTQIA identities due to the increased interactions among students during group work. Finally, working with other students in active-learning classrooms can present challenges and opportunities for students considering their LGBTQIA identity. These findings indicate that these students' LGBTQIA identities are affecting their experience in the classroom and that there may be specific instructional practices that can mitigate some of the possible obstacles. We hope that this work can stimulate discussions about how to broadly make our active-learning biology classes more inclusive of this specific population of students. © 2016 K. M. Cooper and S. E. Brownell. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Peterson, Erik L
Though a prominent British developmental biologist in his day, a close friend of Theodosius Dobzhansky, and a frequent correspondent with Ernst Mayr, C.H. Waddington did not enter the ranks of "architect" of the Modern Synthesis. By the end of his career, in fact, he recognized that other biologists reacted to his work "as though they feel obscurely uneasy"; and that the best that some philosophers of biology could say of his work was that he was not "wholly orthodox" (Waddington 1975c, 11). In this essay, I take Waddington's self-assessments at face value and explore three potential reasons why his work did not have more of a direct impact: Waddington's explicit support for the philosophy of Alfred North Whitehead; a lack of institutional support; and Waddington's occasional marginalization from the core network of American neo-Darwinians. Though excluded from the Modern Synthesis in the mid-20th century, it now appears that Waddington's work does undergird the emerging evo-devo synthesis. Whether this indicates concomitant, if implicit, support for Whiteheadian philosophy is an interesting question not explored here.
Creanza, Nicole; Kolodny, Oren; Feldman, Marcus W
Human cultural traits-behaviors, ideas, and technologies that can be learned from other individuals-can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene-culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment.
The purpose of this course is to learn the philosophy, principles, and techniques of modern biology. The course is particularly designed for those who have not learned biology previously or whose major is other than biology, and who may think that they do not need to know any biology at all. The topics are covered in a rather general, overview manner, but certain level of diligence in grasping concepts and memorizing the terminology is expected.
Butler, Wilbert, Jr.
This quasi-experimental, mixed-methods study assessed the influence of the nature of science (NOS) instruction on college students' learning of biological evolution. In this research, conducted in two introductory biology courses, in each course the same instruction was employed, with one important exception: in the experimental section students were involved in an explicit, reflective treatment of the nature of science (Explicit, reflective NOS), in the traditional treatment section, NOS was implicitly addressed (traditional treatment). In both sections, NOS aspects of science addressed included is tentative, empirically based, subjective, inferential, and based on relationship between scientific theories and laws. Students understanding of evolution, acceptance of evolution, and understanding of the nature of science were assessed before, during and after instruction. Data collection entailed qualitative and quantitative methods including Concept Inventory for Natural Selection (CINS), Measure of Acceptance of the Theory of Evolution (MATE) survey, Views of nature of Science (VNOS-B survey), as well as interviews, classroom observations, and journal writing to address understand students' views of science and understanding and acceptance of evolution. The quantitative data were analyzed via inferential statistics and the qualitative data were analyzed using grounded theory. The data analysis allowed for the construction and support for four assertions: Assertion 1: Students engaged in explicit and reflective NOS specific instruction significantly improved their understanding of the nature of science concepts. Alternatively, students engaged in instruction using an implicit approach to the nature of science did not improve their understanding of the nature of science to the same degree. The VNOS-B results indicated that students in the explicit, reflective NOS class showed the better understanding of the NOS after the course than students in the implicit NOS class
Enquist, Magnus; Lind, Johan; Ghirlanda, Stefano
Behaving efficiently (optimally or near-optimally) is central to animals' adaptation to their environment. Much evolutionary biology assumes, implicitly or explicitly, that optimal behavioural strategies are genetically inherited, yet the behaviour of many animals depends crucially on learning. The question of how learning contributes to optimal behaviour is largely open. Here we propose an associative learning model that can learn optimal behaviour in a wide variety of ecologically relevant ...
This study aimed to analyze the relationship between high school students' self-efficacy perceptions regarding biology, the metacognitive strategies they use in this course and their academic motivation for learn biology. The sample of the study included 286 high school students enrolled in three high schools who attended a biology course in Kars,…
Full Text Available This study describes the implementation and effectiveness of small-group active engagement (GAE exercises in an introductory biology course (BSCI207 taught in a large auditorium setting. BSCI207 (Principles of Biology III—Organismal Biology is the third introductory core course for Biological Sciences majors. In fall 2014, the instructors redesigned one section to include GAE activities to supplement lecture content. One section (n = 198 employed three lectures per week. The other section (n = 136 replaced one lecture per week with a GAE class. We explored the benefits and challenges associated with implementing GAE exercises and their relative effectiveness for unique student groups (e.g., minority students, high- and low-grade point average [GPA] students. Our findings show that undergraduates in the GAE class exhibited greater improvement in learning outcomes than undergraduates in the traditional class. Findings also indicate that high-achieving students experienced the greatest benefit from GAE activities. Some at-risk student groups (e.g., two-year transfer students showed comparably low learning gains in the course, despite the additional support that may have been afforded by active learning. Collectively, these findings provide valuable feedback that may assist other instructors who wish to revise their courses and recommendations for institutions regarding prerequisite coursework approval policies.
Connell, Georgianne L.; Donovan, Deborah A.; Chambers, Timothy G.
Student-centered strategies are being incorporated into undergraduate classrooms in response to a call for reform. We tested whether teaching in an extensively student-centered manner (many active-learning pedagogies, consistent formative assessment, cooperative groups; the Extensive section) was more effective than teaching in a moderately student-centered manner (fewer active-learning pedagogies, less formative assessment, without groups; the Moderate section) in a large-enrollment course. One instructor taught both sections of Biology 101 during the same quarter, covering the same material. Students in the Extensive section had significantly higher mean scores on course exams. They also scored significantly higher on a content postassessment when accounting for preassessment score and student demographics. Item response theory analysis supported these results. Students in the Extensive section had greater changes in postinstruction abilities compared with students in the Moderate section. Finally, students in the Extensive section exhibited a statistically greater expert shift in their views about biology and learning biology. We suggest our results are explained by the greater number of active-learning pedagogies experienced by students in cooperative groups, the consistent use of formative assessment, and the frequent use of explicit metacognition in the Extensive section. PMID:26865643
Julia J Snyder
Full Text Available This study evaluated hypothesized effects of the Peer-Led Team Learning (PLTL instructional model on undergraduate peer leaders' critical thinking skills. This investigation also explored peer leaders' perceptions of their critical thinking skills. A quasi-experimental pre-test/post-test with control group design was used to determine critical thinking gains in PLTL/non-PLTL groups. Critical thinking was assessed using the California Critical Thinking Skills Test (CCTST among participants who had previously completed and been successful in a mixed-majors introductory biology course at a large, private research university in the American Northeast. Qualitative data from open-ended questionnaires confirmed that factors thought to improve critical thinking skills such as interaction with peers, problem solving, and discussion were perceived by participants to have an impact on critical thinking gains. However, no significant quantitative differences in peer leaders' critical thinking skills were found between pre- and post-experience CCTST measurements or between experimental and control groups.
Snyder, Julia J.; Wiles, Jason R.
This study evaluated hypothesized effects of the Peer-Led Team Learning (PLTL) instructional model on undergraduate peer leaders’ critical thinking skills. This investigation also explored peer leaders’ perceptions of their critical thinking skills. A quasi-experimental pre-test/post-test with control group design was used to determine critical thinking gains in PLTL/non-PLTL groups. Critical thinking was assessed using the California Critical Thinking Skills Test (CCTST) among participants who had previously completed and been successful in a mixed-majors introductory biology course at a large, private research university in the American Northeast. Qualitative data from open-ended questionnaires confirmed that factors thought to improve critical thinking skills such as interaction with peers, problem solving, and discussion were perceived by participants to have an impact on critical thinking gains. However, no significant quantitative differences in peer leaders’ critical thinking skills were found between pre- and post-experience CCTST measurements or between experimental and control groups. PMID:25629311
Full Text Available Virtual Field Trip is a computer aided module of science developed to study the Colonisation and Succession in Mangrove Swamps, as an alternative to the real field trip in Form for Biology. This study is to identify the effectiveness of the Virtual Field Trip (VFT module towards the level of achievement in the formative test for this topic. This study was conducted to 60 students employing a quasi-experimental design involving a treatment group taught using the VFT module and a control group who were taught using conventional methods. Analysis into the effectiveness of the virtual module was done descriptively, followed by inferential analysis involving the two-way ANOVA. The results showed significant differences in the mean scores of pre and post achievement between students taught using VFT and students who were taught using conventional methods for objective, structure and essay type questions. The study concluded that teaching and learning by using the VFT module, integrated with ICT, has a positive impact on student achievement whencompared to conventional methods. This study focuses on the use of the VFT recognizing that teachers are often unable to conduct a real field trip on location.
Saputri, A. C.; Sajidan; Rinanto, Y.
Critical thinking is an important and necessary skill to confront the challenges of the 21st century. Critical thinking skills accommodate activities that can improve high-order thinking skills. This study aims to determine senior high school students' critical thinking skills in Biology learning. This research is descriptive research using instruments developed based on the core aspects of critical thinking skills according to Facione which include interpretation, analysis, evaluation, explanation, conclusion, and self-regulation. The subjects in this study were 297 students in grade 12 of a senior high school in Surakarta selected through purposive sampling technique. The results of this study showed that the students' critical thinking skills on evaluation and self-regulation are in good criterion with 78% and 66% acquisition while 52% interpretation, 56% analysis, 52% conclusion and 42% explanation indicate sufficient criteria. The conclusion from this research is that critical thinking skill of the students still was in enough category, so that needed a way to enhance it on some indicators.
Ha, Minsu; Nehm, Ross H.; Urban-Lurain, Mark; Merrill, John E.
Our study explored the prospects and limitations of using machine-learning software to score introductory biology students' written explanations of evolutionary change. We investigated three research questions: 1) Do scoring models built using student responses at one university function effectively at another university? 2) How many human-scored…
Connell, Georgianne L; Donovan, Deborah A; Chambers, Timothy G
Student-centered strategies are being incorporated into undergraduate classrooms in response to a call for reform. We tested whether teaching in an extensively student-centered manner (many active-learning pedagogies, consistent formative assessment, cooperative groups; the Extensive section) was more effective than teaching in a moderately student-centered manner (fewer active-learning pedagogies, less formative assessment, without groups; the Moderate section) in a large-enrollment course. One instructor taught both sections of Biology 101 during the same quarter, covering the same material. Students in the Extensive section had significantly higher mean scores on course exams. They also scored significantly higher on a content postassessment when accounting for preassessment score and student demographics. Item response theory analysis supported these results. Students in the Extensive section had greater changes in postinstruction abilities compared with students in the Moderate section. Finally, students in the Extensive section exhibited a statistically greater expert shift in their views about biology and learning biology. We suggest our results are explained by the greater number of active-learning pedagogies experienced by students in cooperative groups, the consistent use of formative assessment, and the frequent use of explicit metacognition in the Extensive section. © 2016 G. L. Connell, D. A. Donovan, and T. G. Chambers. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Jeffrey T. Olimpo
Full Text Available Most introductory courses in the biological sciences are inherently content-dense and rich with jargon—jargon that is often confusing and nonsensical to novice students. These characteristics present an additional paradox to instructors, who strive to achieve a balance between simply promoting passive, rote memorization of facts and engaging students in developing true, concrete understanding of the terminology. To address these concerns, we developed and implemented a Biology Taboo Wiktionary that provided students with an interactive opportunity to review and describe concepts they had encountered during their first semester of introductory biology. However, much like the traditional Taboo game, the rules were such that students could not use obvious terms to detail the main term. It was our belief that if the student could synthesize a thoughtful, scientific explanation of the term under these conditions, he or she demonstrated a true understanding of the conceptual context and meaning of the term.
Masters, Roger D
Despite advances in fields like genetics, evolutionary psychology, and human behavior and evolution--which generally focus on individual or small group behavior from a biological perspective--evolutionary biology has made little impact on studies of political change and social history. Theories of natural selection often seem inapplicable to human history because our social behavior is embedded in language (which makes possible the concepts of time and social identity on which what we call "history" depends). Peter Corning's Holistic Darwinism reconceptualizes evolutionary biology, making it possible to go beyond the barriers separating the social and natural sciences. Corning focuses on two primary processes: "synergy" (complex multivariate interactions at multiple levels between a species and its environment) and "cybernetics" (the information systems permitting communication between individuals and groups over time). Combining this frame of reference with inclusive fitness theory, it is possible to answer the most important (and puzzling) question in human history: How did a species that lived for millennia in hunter-gatherer bands form centralized states governing large populations of non-kin (including multi-ethnic empires as well as modern nation-states)? The fragility and contemporary ethnic violence in Kenya and the Congo should suffice as evidence that these issues need to be taken seriously. To explain the rise and fall of states as well as changes in human laws and customs--the core of historical research--it is essential to show how the provision of collective goods can overcome the challenge of self-interest and free-riding in some instances, yet fail to do so in others. To this end, it is now possible to consider how a state providing public goods can--under circumstances that often include effective leadership--contribute to enhanced inclusive fitness of virtually all its members. Because social behavior needs to adapt to ecology, but ecological
Chrisantha Thomas Fernando
Full Text Available We consider approaches to brain dynamics and function that have been claimed to be Darwinian. These include Edelman’s theory of neuronal group selection, Changeux’s theory of synaptic selection and selective stabilization of pre-representations, Seung’s Darwinian synapse, Loewenstein’s synaptic melioration, Adam’s selfish synapse and Calvin’s replicating activity patterns. Except for the last two, the proposed mechanisms are selectionist but not truly Darwinian, because no replicators with information transfer to copies and hereditary variation can be identified in them. All of them fit, however, a generalized selectionist framework conforming to the picture of Price’s covariance formulation, which deliberately was not specific even to selection in biology, and therefore does not imply an algorithmic picture of biological evolution. Bayesian models and reinforcement learning are formally in agreement with selection dynamics. A classification of search algorithms is shown to include Darwinian replicators (evolutionary units with multiplication, heredity and variability as the most powerful mechanism in a sparsely occupied search space. Examples of why parallel competitive search with information transfer among the units is efficient are given. Finally, we review our recent attempts to construct and analyze simple models of true Darwinian evolutionary units in the brain in terms of connectivity and activity copying of neuronal groups. Although none of the proposed neuronal replicators include miraculous mechanisms, their identification remains a challenge but also a great promise.
Zhu, Zhengming; Zhang, Juan; Ji, Xiaomei; Fang, Zhen; Wu, Zhimeng; Chen, Jian; Du, Guocheng
Microbial cells have been widely used in the industry to obtain various biochemical products, and evolutionary engineering is a common method in biological research to improve their traits, such as high environmental tolerance and improvement of product yield. To obtain better integrate functions of microbial cells, evolutionary engineering combined with other biotechnologies have attracted more attention in recent years. Classical laboratory evolution has been proven effective to letting more beneficial mutations occur in different genes but also has some inherent limitations such as a long evolutionary period and uncontrolled mutation frequencies. However, recent studies showed that some new strategies may gradually overcome these limitations. In this review, we summarize the evolutionary strategies commonly used in industrial microorganisms and discuss the combination of evolutionary engineering with other biotechnologies such as systems biology and inverse metabolic engineering. Finally, we prospect the importance and application prospect of evolutionary engineering as a powerful tool especially in optimization of industrial microbial cell factories.
Lee, Jun-Ki; Kwon, Yong-Ju
Using functional magnetic resonance imaging (fMRI), this study investigates and discusses neurological explanations for, and the educational implications of, the neural network activations involved in hypothesis-generating and hypothesis-understanding for biology education. Two sets of task paradigms about biological phenomena were designed:…
Randler, Christoph; Kummer, Barbara; Wilhelm, Christian
The aim of this study was to assess the outcome of a zoo visit in terms of learning and retention of knowledge concerning the adaptations and behavior of vertebrate species. Basis of the work was the concept of implementing zoo visits as an out-of-school setting for formal, curriculum based learning. Our theoretical framework centers on the…
Lacquaniti, Francesco; Ivanenko, Yuri P; d'Avella, Andrea; Zelik, Karl E; Zago, Myrka
The identification of biological modules at the systems level often follows top-down decomposition of a task goal, or bottom-up decomposition of multidimensional data arrays into basic elements or patterns representing shared features. These approaches traditionally have been applied to mature, fully developed systems. Here we review some results from two other perspectives on modularity, namely the developmental and evolutionary perspective. There is growing evidence that modular units of development were highly preserved and recombined during evolution. We first consider a few examples of modules well identifiable from morphology. Next we consider the more difficult issue of identifying functional developmental modules. We dwell especially on modular control of locomotion to argue that the building blocks used to construct different locomotor behaviors are similar across several animal species, presumably related to ancestral neural networks of command. A recurrent theme from comparative studies is that the developmental addition of new premotor modules underlies the postnatal acquisition and refinement of several different motor behaviors in vertebrates.
Poolton, J M; Masters, R S W; Maxwell, J P
Heuristics of evolutionary biology (e.g., survival of the fittest) dictate that phylogenetically older processes are inherently more stable and resilient to disruption than younger processes. On the grounds that non-declarative behaviour emerged long before declarative behaviour, Reber (1992) argues that implicit (non-declarative) learning is supported by neural processes that are evolutionarily older than those supporting explicit learning. Reber suggested that implicit learning thus leads to performance that is more robust than explicit learning. Applying this evolutionary framework to motor performance, we examined whether implicit motor learning, relative to explicit motor learning, conferred motor output that was resilient to physiological fatigue and durable over time. In Part One of the study a fatigued state was induced by a double Wingate Anaerobic test protocol. Fatigue had no affect on performance of participants in the implicit condition; whereas, performance of participants in the explicit condition deteriorated significantly. In Part Two of the study a convenience sample of participants was recalled following a one-year hiatus. In both the implicit and the explicit condition retention of performance was seen and, contrary to the findings in Part One, so was resilience to fatigue. The resilient performance in the explicit condition after one year may have resulted from forgetting (the decay of declarative knowledge) or from consolidation of declarative knowledge as implicit memories. In either case, implicit processes were left to more effectively support motor performance.
Stearns, Stephen C
This review is aimed at readers seeking an introductory overview, teaching courses and interested in visionary ideas. It first describes the range of topics covered by evolutionary medicine, which include human genetic variation, mismatches to modernity, reproductive medicine, degenerative disease, host-pathogen interactions and insights from comparisons with other species. It then discusses priorities for translational research, basic research and health management. Its conclusions are that evolutionary thinking should not displace other approaches to medical science, such as molecular medicine and cell and developmental biology, but that evolutionary insights can combine with and complement established approaches to reduce suffering and save lives. Because we are on the cusp of so much new research and innovative insights, it is hard to estimate how much impact evolutionary thinking will have on medicine, but it is already clear that its potential is enormous.
Hendry, A. P.; Kinnison, M. T.; Heino, M.
Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles...... are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design...... of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently...
Lankau, Richard; Jørgensen, Peter Søgaard; Harris, David J.
As policymakers and managers work to mitigate the effects of rapid anthropogenic environmental changes, they need to consider organisms’ responses. In light of recent evidence that evolution can be quite rapid, this now includes evolutionary responses. Evolutionary principles have a long history...... in conservation biology, and the necessary next step for the field is to consider ways in which conservation policy makers and managers can proactively manipulate evolutionary processes to achieve their goals. In this review, we aim to illustrate the potential conservation benefits of an increased understanding...... of evolutionary history and prescriptive manipulation of three basic evolutionary factors: selection, variation, and gene flow. For each, we review and propose ways that policy makers and managers can use evolutionary thinking to preserve threatened species, combat pest species, or reduce undesirable evolutionary...
Throughout his career as a writer, Sigmund Freud maintained an interest in the evolutionary origins of the human mind and its neurotic and psychotic disorders. In common with many writers then and now, he believed that the evolutionary past is conserved in the mind and the brain. Today the "evolutionary Freud" is nearly forgotten. Even among Freudians, he is regarded to be a red herring, relevant only to the extent that he diverts attention from the enduring achievements of the authentic Freud. There are three ways to explain these attitudes. First, the evolutionary Freud's key work is the "Overview of the Transference Neurosis" (1915). But it was published at an inopportune moment, forty years after the author's death, during the so-called "Freud wars." Second, Freud eventually lost interest in the "Overview" and the prospect of a comprehensive evolutionary theory of psychopathology. The publication of The Ego and the Id (1923), introducing Freud's structural theory of the psyche, marked the point of no return. Finally, Freud's evolutionary theory is simply not credible. It is based on just-so stories and a thoroughly discredited evolutionary mechanism, Lamarckian use-inheritance. Explanations one and two are probably correct but also uninteresting. Explanation number three assumes that there is a fundamental difference between Freud's evolutionary narratives (not credible) and the evolutionary accounts of psychopathology that currently circulate in psychiatry and mainstream journals (credible). The assumption is mistaken but worth investigating.
Full Text Available Introduction: Teaching biomedical disciplines for students with disabilities in highereducation is considered a major challenge, especially when it comes to the curriculum, themethods and the resources. In Brazil there are few reports on how the processes ofteaching and learning biomedical disciplines in higher education are conducted. In Spain,since the 70’s the School of Physiotherapy from the National Organization of Spanish blindpeople (ONCE offers exclusively for students with disabilities undergraduate degree inPhysiotherapy, as well as many post graduation courses in biomedicine. Thus, the aim ofthis study was to verify in situ what were the resources and methods used by theprofessors of biochemistry and cell biology to teach their students with visual impairments.Material and Methods: Technical visits were conducted using the following instruments tocollect the data: Unstructured interviews with teachers, students and staff (audio-recordedand later transcribed and classroom observation using photographs and reports. Thedata generated by the interviews were analyzed by the discourse analysis.Discussion and results: Reports indicated that the main methodological resources are:embossed boards made with Swell paper and with the help of an oven called Ricohfuser®; commercially sold models of cells and body structures; the technique of descriptivediscourse where the professor describes an image to be studied, individual touchtechniques where the professor shows an image using the touch of the student. It wasobserved that certain sectors inside the school are especially distinguished. Overall, theschool does not present any other routine different from a regular school, and according tothe professors, it happens intentionally, so that the future professionals are able to work inenvironments not adapted for their needs.Conclusion: The observed adjustments in the school of physiotherapy at ONCE could beseen as an example for Brazilian
Hoellinger, Thomas; Petieau, Mathieu; Duvinage, Matthieu; Castermans, Thierry; Seetharaman, Karthik; Cebolla, Ana-Maria; Bengoetxea, Ana; Ivanenko, Yuri; Dan, Bernard; Cheron, Guy
The existence of dedicated neuronal modules such as those organized in the cerebral cortex, thalamus, basal ganglia, cerebellum, or spinal cord raises the question of how these functional modules are coordinated for appropriate motor behavior. Study of human locomotion offers an interesting field for addressing this central question. The coordination of the elevation of the 3 leg segments under a planar covariation rule (Borghese et al., 1996) was recently modeled (Barliya et al., 2009) by phase-adjusted simple oscillators shedding new light on the understanding of the central pattern generator (CPG) processing relevant oscillation signals. We describe the use of a dynamic recurrent neural network (DRNN) mimicking the natural oscillatory behavior of human locomotion for reproducing the planar covariation rule in both legs at different walking speeds. Neural network learning was based on sinusoid signals integrating frequency and amplitude features of the first three harmonics of the sagittal elevation angles of the thigh, shank, and foot of each lower limb. We verified the biological plausibility of the neural networks. Best results were obtained with oscillations extracted from the first three harmonics in comparison to oscillations outside the harmonic frequency peaks. Physiological replication steadily increased with the number of neuronal units from 1 to 80, where similarity index reached 0.99. Analysis of synaptic weighting showed that the proportion of inhibitory connections consistently increased with the number of neuronal units in the DRNN. This emerging property in the artificial neural networks resonates with recent advances in neurophysiology of inhibitory neurons that are involved in central nervous system oscillatory activities. The main message of this study is that this type of DRNN may offer a useful model of physiological central pattern generator for gaining insights in basic research and developing clinical applications.
Preszler, Ralph W; Dawe, Angus; Shuster, Charles B; Shuster, Michèle
With the advent of wireless technology, new tools are available that are intended to enhance students' learning and attitudes. To assess the effectiveness of wireless student response systems in the biology curriculum at New Mexico State University, a combined study of student attitudes and performance was undertaken. A survey of students in six biology courses showed that strong majorities of students had favorable overall impressions of the use of student response systems and also thought that the technology improved their interest in the course, attendance, and understanding of course content. Students in lower-division courses had more strongly positive overall impressions than did students in upper-division courses. To assess the effects of the response systems on student learning, the number of in-class questions was varied within each course throughout the semester. Students' performance was compared on exam questions derived from lectures with low, medium, or high numbers of in-class questions. Increased use of the response systems in lecture had a positive influence on students' performance on exam questions across all six biology courses. Students not only have favorable opinions about the use of student response systems, increased use of these systems increases student learning.
Sadler, Troy D.; Romine, William L.; Menon, Deepika; Ferdig, Richard E.; Annetta, Leonard
This study explored student learning in the context of innovative biotechnology curricula and the effects of gaming as a central element of the learning experience. The quasi-experimentally designed study compared learning outcomes between two curricular approaches: One built around a computer-based game, and the other built around a narrative…
Yaman, Melek; Graf, Dittmar
At the beginning of the 21st century, virtual learning was thought to have the potential to revolutionize learning arrangements. This enthusiastic notion has given way to a kind of disillusionment, which has, however, led to a more realistic assessment of the potential of e-learning, the development of new conceptions, new methodical approaches,…
Gnanakkan, Dionysius Joseph
This multiple case-study investigated how high school biology teachers used modern learning technologies (probes, interactive simulations and animations, animated videos) in their classrooms and why they used the learning technologies. Another objective of the study was to assess whether the use of learning technologies alleviated misconceptions in Biology documented by American Association for the Advancement of Science. The sample consisted of eight teachers: four rural public school teachers, two public selective enrollment school teachers, and two private school teachers. Each teacher was followed for two Units of instruction. Data collected included classroom observations, field notes, student assignments and tests, teacher interviews, and pre-and post-misconception assessments. Paired t-tests were done to analyze the pre-post test data at a significance level of 0.05 and the qualitative data was analyzed using the constant comparative method. Each case study was characterized and then a cross-case analyses was done to find common themes across the different cases. Teachers were found to use the learning technologies as a tool to supplement instruction to visualize abstract processes, collect data, and explore abstract concepts and processes. Teachers were found to situate learning, use scaffolding and questioning and make students work in collaborative groups. The genetics, photosynthesis, and evolution misconceptions were better alleviated than cellular respiration. Student work that was collected demonstrated a superficial understanding of the concepts under discussion even when they had misconceptions. The teachers used the learning technologies in their classrooms for a variety of reasons: visual illustrations, time-saving measure to collect data, best way to collect data, engaging and fun for students and the interactive nature of the visualization tools and models. The study's findings had many implications for research, professional development
Larios-Sanz, Maia; Simmons, Alexandra D; Bagnall, Ruth Ann; Rosell, Rosemarie C
Here we discuss the implementation of a service-learning module in two upper-division biology classes, Medical Microbiology and Cell Biology. This exciting hands-on learning experience provided our students with an opportunity to extend their learning of in-class topics to a real-life scenario. Students were required to volunteer their time (a minimum of 10 hours in a semester) at an under-served clinic in Houston, Texas. As they interacted with the personnel at the clinic, they were asked to identify the most prevalent disease (infectious for Medical Microbiology, and cellular-based for Cell) seen at the clinic and, working in groups, come up with educational material in the form of a display or brochure to be distributed to patients. The material was meant to educate patients about the disease in general terms, as well as how to recognize (symptoms), prevent and treat it. Students were required to keep a reflective journal in the form of a blog throughout the semester, and present their final materials to the class orally. Students were surveyed about their opinion of the experience at the end of the semester. The vast majority of student participants felt that the project was a positive experience and that it helped them develop additional skills beyond what they learn in the classroom and understand how lecture topics relate to every day life.
Prasetya, A. T.; Ridlo, S.
The purpose of this study is to test the learning motivation of science instruments and compare the learning motivation of science from chemistry and biology teacher candidates. Kuesioner Motivasi Sains (KMS) in Indonesian adoption of the Science Motivation Questionnaire II (SMQ II) consisting of 25 items with a 5-point Likert scale. The number of respondents for the Exploratory Factor Analysis (EFA) test was 312. The Kaiser-Meyer-Olkin (KMO), determinant, Bartlett’s Sphericity, Measures of Sampling Adequacy (MSA) tests against KMS using SPSS 20.0, and Lisrel 8.51 software indicate eligible indications. However testing of Communalities obtained results that there are 4 items not qualified, so the item is discarded. The second test, all parameters of eligibility and has a magnitude of Root Mean Square Error of Approximation (RMSEA), P-Value for the Test of Close Fit (RMSEA <0.05), Goodness of Fit Index (GFI) was good. The new KMS with 21 valid items and composite reliability of 0.9329 can be used to test the level of learning motivation of science which includes Intrinsic Motivation, Sefl-Efficacy, Self-Determination, Grade Motivation and Career Motivation for students who master the Indonesian language. KMS trials of chemistry and biology teacher candidates obtained no significant difference in the learning motivation between the two groups.
Clancy, Thomas R
As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.
Diferenças de gênero no desenvolvimento sexual: integração dos paradigmas biológico, psicanalítico e evolucionista Gender differences in sexual development: biologic, psychoanalytic and evolutionary paradigms integration
Full Text Available O desenvolvimento sexual masculino e feminino tem sido fonte de incontáveis questionamentos em várias áreas do conhecimento humano ao longo da história da humanidade. Diversas especialidades têm estudado o tópico da sexualidade de forma dissociada, dificultando a sua compreensão global e a abordagem terapêutica de seus transtornos. A busca de integração de diferentes teorias oriundas, tanto dos processos fisiológicos básicos que originam a vida, quanto dos campos mais complexos da psicanálise, tem sido um dos grandes desafios da prática clínica. Propõe-se, então, um artigo com o objetivo de descrever as diferenças de gênero no desenvolvimento sexual humano, à luz dos vértices biológico, psicanalítico e evolucionista, buscando-se pontes de conexão entre estes paradigmas, para uma visão mais integrada do processo de ser masculino ou feminino.Male and female sexual development has been source of many controversies through the human history. Many specialties have studied the sexuality from a disconnected point of view, raising difficulties to its integral understanding and therapeutic approach. The search for integration between physiology and psychoanalysis has been one of the major challenges in clinical practice. In this article we describe gender differences in sexual human development under the biological, psychoanalytical and evolutionary perspectives, searching connections between these paradigms in order to find a more integrated vision of male and female development.
a promising, but still largely unexplored research niche and deserve to be included into the agenda of molecular ecologists, ..... cess involves the generation of double-strand DNA breaks in ...... 2012 Embryonic stem cell potency fluctuates.
Chela-Flores, Julian [Instituto de Estudios Avanzados, Caracas (Venezuela); [Abdus Salam International Centre for Theoretical Physics, Trieste (Italy)
A major objective in solar system exploration is the insertion of appropriate biology-oriented experiments in future missions. We discuss various reasons for suggesting that this type of research be considered a high priority for feasibility studies and, subsequently, for technological development of appropriate melters and submersibles. Based on numerous examples, we argue in favour of the assumption that Darwin's theory is valid for the evolution of life anywhere in the universe. We have suggested how to obtain preliminary insights into the question of the distribution of life in the universe. Universal evolution of intelligent behaviour is at the end of an evolutionary pathway, in which evolution of ion channels in the membrane of microorganisms occurs in its early stages. Further, we have argued that a preliminary test of this conjecture is feasible with experiments on the Europan surface or ocean, involving evolutionary biosignatures (ion channels). This aspect of the exploration for life in the solar system should be viewed as a complement to the astronomical approach for the search of evidence of the later stages of the evolutionary pathways towards intelligent behaviour. (author)
David F. Bjorklund
Full Text Available Developmental thinking is gradually becoming integrated within mainstream evolutionary psychology. This is most apparent with respect to the role of parenting, with proponents of life history theory arguing that cognitive and behavioral plasticity early in life permits children to select different life history strategies, with such strategies being adaptive solutions to different fitness trade-offs. I argue that adaptations develop and are based on the highly plastic nature of infants’ and children’s behavior/cognition/brains. The concept of evolved probabilistic cognitive mechanisms is introduced, defined as information processing mechanisms evolved to solve recurrent problems faced by ancestral populations that are expressed in a probabilistic fashion in each individual in a generation and are based on the continuous and bidirectional interaction over time at all levels of organization, from the genetic through the cultural. Early perceptual/cognitive biases result in behavior that, when occurring in a species-typical environment, produce continuous adaptive changes in behavior (and cognition, yielding adaptive outcomes. Examples from social learning and tool use are provided, illustrating the development of adaptations via evolved probabilistic cognitive mechanisms. The integration of developmental concepts into mainstream evolutionary psychology (and evolutionary concepts into mainstream developmental psychology will provide a clearer picture of what it means to be human.
Gilbert, Scott F
Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines." Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, developmental biology remains vigorous, pluripotent, and relatively undifferentiated. In many disciplines, especially in evolutionary biology and oncology, the developmental perspective is being reasserted as an important research program.
Gafford, Kenneth Allen
The differences between two experimental groups using cooperative learning activities were examined during the initial eight weeks of a biology course. While both groups participated in the same cooperative learning activities, only one group received deliberate instructor interventions. These interventions were designed to help students think positively about working in cooperative learning groups while alleviating anxiety toward cooperative learning. Initially, all students were uncomfortable and reported trouble staying focused during cooperative learning. The final quantitative results indicated that the group who received the interventions had more positive perceptions toward cooperative learning but their attitudes and anxiety levels showed no significant difference from the non-intervention group; advantages occurred specifically for thinking on task, student engagement, perceptions of task importance, and best levels of challenge and skill. Intervention participants had a higher mean score on the class exam administered during the eight-week study but it was not significantly different. Qualitative data revealed that the intervention participants experienced greater overall consequence, mainly in the areas of engagement, believed skill, and self-worth. According to flow theory, when students are actively engaged, the probability of distraction by fears and unrelated ideas is reduced, for instance, how they are perceived by others. These findings corroborate constructivist theories, particularly the ones relative to students working in cooperative groups. Researchers should continue to use appropriate methods to further explore how students of various abilities and developmental levels are affected by their perceptions, attitudes, and anxieties relative to different instructional contexts. Given the highly contextual nature of students' learning and motivation, researchers need to examine a number of meaningful questions by comparing students' perceptions
Rajab, Adel Mohammad
The problem of low persistence of science majors has resulted in calls for changes in undergraduate instruction toward environments that foster positive self-efficacy among beginning science majors. Low science self-efficacy and poor attitudes toward science may contribute to high attrition rates of science majors. Classroom environments that foster positive self-efficacy development include pedagogies that promote authentic learning contexts and involve collaborative learning teams. Problem-based learning (PBL) is an instructional model that attempts to create both conditions and may provide every source of information needed for the development of self-efficacy (i.e., mastery experiences, vicarious experiences, verbal persuasion, and physiological states) as postulated by Albert Bandura. The degree to which these sources of self-efficacy are delivered to individuals within a PBL group may depend on how the group members interact and how students perceive the PBL process itself. This study examined the development of biology self-efficacy and attitudes among biology majors in a PBL setting and in a traditional lecture-based setting. Specifically, this project investigated changes in students' biology self-efficacy beliefs, mediating aspects of PBL in self-efficacy development, the relationship between PBL processes and group collective efficacy, the predictive nature of entering self-efficacy levels on attitudes toward PBL and mid-term grades, and changes in student attitudes toward biology. The study design was quasi-experimental and included quantitative pre- and post-surveys, qualitative interviews, and classroom observations. Findings revealed that students enrolled in a PBL class exhibited greater gains in biology self-efficacy and were likely to report more favorable attitudes toward biology compared to students enrolled in a traditional class. The aspects of PBL that most accounted for these findings were students' ownership of the learning process, their
Randler, Christoph; Kummer, Barbara; Wilhelm, Christian
The aim of this study was to assess the outcome of a zoo visit in terms of learning and retention of knowledge concerning the adaptations and behavior of vertebrate species. Basis of the work was the concept of implementing zoo visits as an out-of-school setting for formal, curriculum based learning. Our theoretical framework centers on the self-determination theory, therefore, we used a group-based, hands-on learning environment. To address this questions, we used a treatment—control design (BACI) with different treatments and a control group. Pre-, post- and retention tests were applied. All treatments led to a substantial increase of learning and retention knowledge compared to the control group. Immediately after the zoo visit, the zoo-guide tour provided the highest scores, while after a delay of 6 weeks, the learner-centered environment combined with a teacher-guided summarizing scored best. We suggest incorporating the zoo as an out-of-school environment into formal school learning, and we propose different methods to improve learning in zoo settings.
Roorda, Berend; Joosten, Reinoud
We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary dynamics. For instance, each attractive evolutionarily stable strategy is an attractive evolutionarily stable equilibrium for certain barycentric ray-projection dynamics, and vice versa.
Full Text Available Improving Student’s Interest in Biology lesson by using contextual teaching and learning (CLT methods is n action research study which had an aim to improve student’s interest in biology. The indicator of student’s interest covers the student’s diligence in learning process, active in following teaching and learning process, active in doing a task, the facility and the sources of learning. The result of this researched showed that there were an improvement of students learning interest. The percentage result in cycle I was 39.5%, in cycle 2 was 72.67% and in Cycle 3 was 80.92%. The improvement of students learning interests gave a positive effect toward the students achievement. The students learning achievement in cycle 1 I was 39%, in cycle II was 82% and in cycle III was 93%. In conclusion Contextual Teaching and Learning (CLT can improve the students learning interest in Biology at the Second Grade Students of MTs Negeri Purwokerto. Key words : Improving, Student’s learning interest, Contextual Teaching and Learning (CTL
Halpern, Diane F.
In response to a stimulating article by David C. Geary on the value of understanding the evolutionary basis of learning as a guide to instruction, I raise several objections. When evolutionary theory is used to explain everything from sex differences in math and reading to why children are bored in school, it loses its explanatory power. There is…
Fishman, Michael A
In this paper, I present an analytical framework for polymorphic evolutionary games suitable for explicitly modeling evolutionary processes in diploid populations with sexual reproduction. The principal aspect of the proposed approach is adding diploid genetics cum sexual recombination to a traditional evolutionary game, and switching from phenotypes to haplotypes as the new game׳s pure strategies. Here, the relevant pure strategy׳s payoffs derived by summing the payoffs of all the phenotypes capable of producing gametes containing that particular haplotype weighted by the pertinent probabilities. The resulting game is structurally identical to the familiar Evolutionary Games with non-linear pure strategy payoffs (Hofbauer and Sigmund, 1998. Cambridge University Press), and can be analyzed in terms of an established analytical framework for such games. And these results can be translated into the terms of genotypic, and whence, phenotypic evolutionary stability pertinent to the original game. Copyright © 2016 Elsevier Ltd. All rights reserved.
Fedyk, Mark; Kushnir, Tamar
Our conscious abilities are learned in environments that have evolved to support them. This insight provides an alternative way of framing Huang & Bargh's (H&B's) provocative hypothesis. To understand the conflict between unconscious goals and consciousness, we can study the emergence of conscious thought and control in childhood. These developmental processes are also central to the best available current evolutionary theories.
Douglas L. Brutlag Nancy Ryan Gray
This Gordon conference will cover the areas of structural, functional and evolutionary genomics. It will take a systematic approach to genomics, examining the evolution of proteins, protein functional sites, protein-protein interactions, regulatory networks, and metabolic networks. Emphasis will be placed on what we can learn from comparative genomics and entire genomes and proteomes.
Nicholson, Michael; Xiao, Sarah Hong
This article locates consumer behavior analysis within the modern neo-Darwinian synthesis, seeking to establish an interface between the ultimate-level theorizing of human evolutionary psychology and the proximate level of inquiry typically favored by operant learning theorists. Following an initial overview of the central tenets of neo-Darwinism,…
Sebesta, Amanda J; Bray Speth, Elena
In college introductory science courses, students are challenged with mastering large amounts of disciplinary content while developing as autonomous and effective learners. Self-regulated learning (SRL) is the process of setting learning goals, monitoring progress toward them, and applying appropriate study strategies. SRL characterizes successful, "expert" learners, and develops with time and practice. In a large, undergraduate introductory biology course, we investigated: 1) what SRL strategies students reported using the most when studying for exams, 2) which strategies were associated with higher achievement and with grade improvement on exams, and 3) what study approaches students proposed to use for future exams. Higher-achieving students, and students whose exam grades improved in the first half of the semester, reported using specific cognitive and metacognitive strategies significantly more frequently than their lower-achieving peers. Lower-achieving students more frequently reported that they did not implement their planned strategies or, if they did, still did not improve their outcomes. These results suggest that many students entering introductory biology have limited knowledge of SRL strategies and/or limited ability to implement them, which can impact their achievement. Course-specific interventions that promote SRL development should be considered as integral pedagogical tools, aimed at fostering development of students' lifelong learning skills. © 2017 A. J. Sebesta and E. Bray Speth. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Biel, Rachel; Brame, Cynthia J.
Online courses are a large and growing part of the undergraduate education landscape, but many biology instructors are skeptical about the effectiveness of online instruction. We reviewed studies comparing the effectiveness of online and face-to-face (F2F) undergraduate biology courses. Five studies compared student performance in multiple course sections at community colleges, while eight were smaller scale and compared student performance in particular biology courses at a variety of types ...
Nägele, Andreas; Dejori, Mathäus; Stetter, Martin
Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.
Tibell, Lena A. E.; Harms, Ute
Modern evolutionary theory is both a central theory and an integrative framework of the life sciences. This is reflected in the common references to evolution in modern science education curricula and contexts. In fact, evolution is a core idea that is supposed to support biology learning by facilitating the organization of relevant knowledge. In…
Lockard, Meghan A; Ebert, Margaret S; Bargmann, Cornelia I
The molecular and functional conservation of oxytocin-related neuropeptides in behavior is striking. In animals separated by at least 600 million years of evolution, from roundworms to humans, oxytocin homologs play critical roles in the modulation of reproductive behavior and other biological functions. Here, we review the roles of oxytocin in invertebrate behavior from an evolutionary perspective. We begin by tracing the evolution of oxytocin through the invertebrate animal lineages, and then describe common themes in invertebrate behaviors that are mediated by oxytocin-related peptides, including reproductive behavior, learning and memory, food arousal, and predator/prey relationships. Finally, we discuss interesting future directions that have recently become experimentally tractable. Studying oxytocin in invertebrates offers precise insights into the activity of neuropeptides on well-defined neural circuits; the principles that emerge may also be represented in the more complex vertebrate brain. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 128-142, 2017. © 2016 Wiley Periodicals, Inc.
Quillin, Kim; Thomas, Stephen
The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report's Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. © 2015 K. Quillin and S. Thomas. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Weber, K Scott; Jensen, Jamie L; Johnson, Steven M
An important discussion at colleges is centered on determining more effective models for teaching undergraduates. As personalized genomics has become more common, we hypothesized it could be a valuable tool to make science education more hands on, personal, and engaging for college undergraduates. We hypothesized that providing students with personal genome testing kits would enhance the learning experience of students in two undergraduate courses at Brigham Young University: Advanced Molecular Biology and Genomics. These courses have an emphasis on personal genomics the last two weeks of the semester. Students taking these courses were given the option to receive personal genomics kits in 2014, whereas in 2015 they were not. Students sent their personal genomics samples in on their own and received the data after the course ended. We surveyed students in these courses before and after the two-week emphasis on personal genomics to collect data on whether anticipation of obtaining their own personal genomic data impacted undergraduate student learning. We also tested to see if specific personal genomic assignments improved the learning experience by analyzing the data from the undergraduate students who completed both the pre- and post-course surveys. Anticipation of personal genomic data significantly enhanced student interest and the learning environment based on the time students spent researching personal genomic material and their self-reported attitudes compared to those who did not anticipate getting their own data. Personal genomics homework assignments significantly enhanced the undergraduate student interest and learning based on the same criteria and a personal genomics quiz. We found that for the undergraduate students in both molecular biology and genomics courses, incorporation of personal genomic testing can be an effective educational tool in undergraduate science education.
The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.
Betten, A.W.; Roelofsen, A.; Broerse, J.E.W.
The emerging field of synthetic biology has the potential to improve global health. For example, synthetic biology could contribute to efforts at vaccine development in a context in which vaccines and immunization have been identified by the international community as being crucial to international
Designing experimental approaches is a major cognitive skill in molecular biology research, and building models, including quantitative ones, is a cognitive skill which is rapidly gaining importance. Since molecular biology education at university level is aimed at educating future researchers, we
Quillin, Kim; Thomas, Stephen
The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094
Jarrett, Kevin; Williams, Mary; Horn, Spencer; Radford, David; Wyss, J Michael
"Sickle cell anemia: tracking down a mutation" is a full-day, inquiry-based, biology experience for high school students enrolled in genetics or advanced biology courses. In the experience, students use restriction endonuclease digestion, cellulose acetate gel electrophoresis, and microscopy to discover which of three putative patients have the sickle cell genotype/phenotype using DNA and blood samples from wild-type and transgenic mice that carry a sickle cell mutation. The inquiry-based, problem-solving approach facilitates the students' understanding of the basic concepts of genetics and cellular and molecular biology and provides experience with contemporary tools of biotechnology. It also leads to students' appreciation of the causes and consequences of this genetic disease, which is relatively common in individuals of African descent, and increases their understanding of the first principles of genetics. This protocol provides optimal learning when led by well-trained facilitators (including the classroom teacher) and carried out in small groups (6:1 student-to-teacher ratio). This high-quality experience can be offered to a large number of students at a relatively low cost, and it is especially effective in collaboration with a local science museum and/or university. Over the past 15 yr, >12,000 students have completed this inquiry-based learning experience and demonstrated a consistent, substantial increase in their understanding of the disease and genetics in general. Copyright © 2016 The American Physiological Society.
Full Text Available The main objective of this study was to evaluate the impact of cooperative learning methods on students’ academic achievement and laboratory proficiency in biology subject. Quasi-experimental control group interrupted time series design was employed. Data pertaining to these variables were collected from 369 students and 18 biology teachers in three schools. A series of biological tests and semistructured questionnaire were used to collect data. Multivariate analysis (two-way ANOVA was used to analyze the test scores exposed by teaching methods, and semistructured questionnaire was administered to comprehend factors that hamper the successive execution of CL. Hence, multivariate analysis revealed that there was no significant (P>0.05 difference in the pretest score of the learner academic performance; however, there were significant differences (P<0.01 in the posttest results by teaching methods, but not by schools. Correspondingly, there were significant differences in the pretest P<0.05 and posttest (P<0.01 results of the students’ laboratory proficiency by teaching methods. The results exemplify that there was significant learning gain obtained via CLAD followed by cooperative discussion group (CDG. The result from the questionnaire survey showed that the number of students, lack of laboratory equipment, and so on hamper consecutive execution of CL.
Dohn, Niels Bonderup; Dohn, Nina Bonderup
The sciences are often perceived by students as irrelevant as they do not see the content of science as related to their daily lives. Web 2.0-mediated activities are characterized by user-driven content production, collaboration, and multi-way communication. It has been proposed that employing Web 2.0 in educational activities will promote richer opportunities for making learning personally meaningful, collaborative, and socially relevant. Since Facebook is already in use among youths, it potentially provides a communicative link between educational content and students' lives. The present study was conducted as a case study to provide an inductive, explorative investigation of whether and how the integration of Facebook into upper secondary biology can affect interest in biology and participation in learning communication. The results indicate that the coupling of formal and informal communication practices on Facebook serves to maintain interest and open up new learning possibilities while at the same time creating barriers to communication. These barriers are due to distractions, ethical issues, and a certain depreciation of the activities ensuing from the everydayness of Facebook as a communication platform. In conclusion, use of Facebook as an educational platform is not clearly good or bad.
This paper discusses the problem of anticipation from an evolutionary and systems-theoretical perspective, developed in the context of Russian/Soviet evolutionary biological and neurophysiological schools in the early and mid-twentieth century. On this background, an outline is given of the epigenetic interpretation of anticipatory capacities formulated and substantiated by the eminent Russian neurophysiologist academician Peter K. Anokhin in the framework of functional systems theory. It is considered that several key positions of this theory are well confirmed by recent evidence on anticipation as an evolutionarily basic adaptive capacity, possibly inherent to the organization of life. In the field of neuroscience, the theory of functional systems may potentially facilitate future studies at the intersection of learning, development and evolution by representing an integrative approach to the problem of anticipation.
Telli, S.; Cakiroglu, J.; den Brok, P.
The domain of learning environments research has produced many promising findings, leading to an enhancement of the teaching and learning process in many countries. However, there have been a limited number of studies in this field in Turkey. For that reason, the purpose of the present study was to
Chatila, Hanadi; Al Husseiny, Fatima
Recent research findings have shown that cooperative learning improves students' thinking skills as it allows them to communicate actively with each other (Johnson, Johnson and Smith, 2014). Therefore, cooperative learning has been proposed by many educators to be implemented in classrooms to produce lifelong learners and critical thinkers…
Grillo, Kelly J.; Dieker, Lisa A.
An essential element of science instruction is content literacy. In order to improve literacy specific to science, vocabulary must be addressed. As Jitendra et al. (2004) pointed out, "because learning vocabulary during independent reading is very inefficient for students with reading difficulties, vocabulary and word learning skills must be…
Ellefson, Michelle R.; Brinker, Rebecca A.; Vernacchio, Vincent J.; Schunn, Christian D.
Gene expression is a difficult topic for students to learn and comprehend, at least partially because it involves various biochemical structures and processes occurring at the microscopic level. Designer Bacteria, a design-based learning (DBL) unit for high-school students, applies principles of DBL to the teaching of gene expression. Throughout…
Telli, S.; Cakiroglu, J.; Brok, den P.J.; Fisher, D. L.; Khine, M. S.
The domain of learning environments research has produced many promising findings, leading to an enhancement of the teaching and learning process in many countries. However, there have been a limited number of studies in this field in Turkey. For that reason, the purpose of the present study was to
Ah-King, Malin; Nylin, S?ren
It is common to refer to all sorts of clear-cut differences between the sexes as something that is biologically almost inevitable. Although this does not reflect the status of evolutionary theory on sex determination and sexual dimorphism, it is probably a common view among evolutionary biologists as well, because of the impact of sexual selection theory. To get away from thinking about biological sex and traits associated with a particular sex as something static, it should be recognized tha...
to determine the student logical thinking abilityandlearningoutcomesingeneralbiologycoursesthroughthelearningblendedlearningbased scaffolding. This research was conducted by descriptive method. Stages of research include the preparationofanevaluationinstrument,implementationoftheproductintheformofblendedlearning ingeneralbiologylectures,measurementoflogicalthinkingabilityofstudentsandlearningoutcomes evaluation stage. The results showed that there is an improvement of student logical thinking ability fromtheconcretelevelintoaformallevel.Variablecontrolingarethehighestlogicalthingkingability aspect with a percentage 81,9. The students learning outcomes also increased from lowest criteria into very good criteria with percentage29,6%.Key words : General Biology, logical thinking, learning outcomes, blended learning, scaffolding <
Corkin, Danya M.; Horn, Catherine; Pattison, Donna
This study examined differences in students' classroom motivational climate perceptions and motivational beliefs between those enrolled in undergraduate Biology courses that implemented an innovative, active learning intervention and those enrolled in traditional Biology courses (control group). This study also sought to determine whether…
Bockholt, Susanne M.; West, J. Paige; Bollenbacher, Walter E.
Multimedia has the potential of providing bioscience education novel learning environments and pedagogy applications to foster student interest, involve students in the research process, advance critical thinking/problem-solving skills, and develop conceptual understanding of biological topics. "Cancer Cell Biology," an interactive, multimedia,…
Ratnayaka, Harish H.
Outdoor, hands-on and experiential learning, as opposed to instruction-based learning in classroom, increases student satisfaction and motivation leading to a deeper understanding of the subject. However, the use of outdoor exercises in undergraduate biology courses is declining due to a variety of constraints. Thus, the goal of this paper is to…
Mar 15, 2014 ... ... of events: 'Entities that were capable of independent replication ... There have been many major evolutionary events that this definition of .... selection at level x to exclusive selection at x – will probably require a multiplicity ...
Lukashov, Vladimir V.; Goudsmit, Jaap
To study the evolutionary relationships among astroviruses, all available sequences for members of the family Astroviridae were collected. Phylogenetic analysis distinguished two deep-rooted groups: one comprising mammalian astroviruses, with ovine astrovirus being an outlier, and the other
Grissom, Elin M; Hawley, Wayne R; Hodges, Kelly S; Fawcett-Patel, Jessica M; Dohanich, Gary P
According to the theory of multiple memory systems, specific brain regions interact to determine how the locations of goals are learned when rodents navigate a spatial environment. A number of factors influence the type of strategy used by rodents to remember the location of a given goal in space, including the biological sex of the learner. We recently found that prior to puberty male rats preferred a striatum-dependent stimulus-response strategy over a hippocampus-dependent place strategy when solving a dual-solution task, while age-matched females showed no strategy preference. Because the cholinergic system has been implicated in learning strategy and is known to be sexually dimorphic prior to puberty, we explored the relationship between learning strategy and muscarinic receptor binding in specific brain regions of prepubertal males and female rats. We confirmed our previous finding that at 28 days of age a significantly higher proportion of prepubertal males preferred a stimulus-response learning strategy than a place strategy to solve a dual-solution visible platform water maze task. Equal proportions of prepubertal females preferred stimulus-response or place strategies. Profiles of muscarinic receptor binding as assessed by autoradiography varied according to strategy preference. Regardless of biological sex, prepubertal rats that preferred stimulus-response strategy exhibited lower ratios of muscarinic receptor binding in the hippocampus relative to the dorsolateral striatum compared to rats that preferred place strategy. Importantly, much of the variance in this ratio was related to differences in the ventral hippocampus to a greater extent than the dorsal hippocampus. The ratios of muscarinic receptors in the hippocampus relative to the basolateral amygdala also were lower in rats that preferred stimulus-response strategy over place strategy. Results confirm that learning strategy preference varies with biological sex in prepubertal rats with males
Silva, Jose A.L. da
Numerous functional biomolecules are associated with metals, i.e. the metallobiomolecules; more specifically, some are dependent on transition metals required for several crucial biological roles. Nevertheless, their names can lead to ambiguous interpretations concerning the properties and performances of this group of biological molecules. Their etymology may be useful by providing a more perceptive insight into their features. However, etymology can lead to incongruous conclusions, requiring an especially careful approach to prevent errors. Examples illustrating these subjects shall be examined (author)
Full Text Available Here we discuss the implementation of a service-learning module in two upper-division biology classes, Medical Microbiology and Cell Biology. This exciting hands-on learning experience provided our students with an opportunity to extend their learning of in-class topics to a real-life scenario. Students were required to volunteer their time (a minimum of 10 hours in a semester at an under-served clinic in Houston, Texas. As they interacted with the personnel at the clinic, they were asked to identify the most prevalent disease (infectious for Medical Microbiology, and cellular-based for Cell seen at the clinic and, working in groups, come up with educational material in the form of a display or brochure to be distributed to patients. The material was meant to educate patients about the disease in general terms, as well as how to recognize (symptoms, prevent and treat it. Students were required to keep a reflective journal in the form of a blog throughout the semester, and present their final materials to the class orally. Students were surveyed about their opinion of the experience at the end of the semester. The vast majority of student participants felt that the project was a positive experience and that it helped them develop additional skills beyond what they learn in the classroom and understand how lecture topics relate to every day life. Here we discuss the implementation of a service-learning module in two upper division biology classes, Medical Microbiology and Cell Biology. This exciting hands-on learning experience provided our students with an opportunity to extend their learning of in-class topics into a real life scenario. Students were required to volunteer their time (a minimum of 10 hours in a semester at an under-served clinic in Houston, Texas. As they interacted with the personnel at the clinic, they were asked to identify the most prevalent disease (infectious for Medical Microbiology, and cellular-based for Cell seen at the
Melkikh, Alexey V
One of the most important conditions for replication in early evolution is the de facto elimination of the conformational degrees of freedom of the replicators, the mechanisms of which remain unclear. In addition, realistic evolutionary timescales can be established based only on partially directed evolution, further complicating this issue. A division of the various evolutionary theories into two classes has been proposed based on the presence or absence of a priori information about the evolving system. A priori information plays a key role in solving problems in evolution. Here, a model of partially directed evolution, based on the learning automata theory, which includes a priori information about the fitness space, is proposed. A potential repository of such prior information is the states of biologically important molecules. Thus, the need for extended evolutionary synthesis is discussed. Experiments to test the hypothesis of partially directed evolution are proposed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Investigating the Relationship between Instructors' Use of Active-Learning Strategies and Students' Conceptual Understanding and Affective Changes in Introductory Biology: A Comparison of Two Active-Learning Environments
Cleveland, Lacy M.; Olimpo, Jeffrey T.; DeChenne-Peters, Sue Ellen
In response to calls for reform in undergraduate biology education, we conducted research examining how varying active-learning strategies impacted students' conceptual understanding, attitudes, and motivation in two sections of a large-lecture introductory cell and molecular biology course. Using a quasi-experimental design, we collected…
The Modern Evolutionary Synthesis (MS) forged in the mid-twentieth century was built on a notion of heredity that excluded soft inheritance, the inheritance of the effects of developmental modifications. However, the discovery of molecular mechanisms that generate random and developmentally induced epigenetic variations is leading to a broadening of the notion of biological heredity that has consequences for ideas about evolution. After presenting some old challenges to the MS that were raised, among others, by Karl Popper, I discuss recent research on epigenetic inheritance, which provides experimental and theoretical support for these challenges. There is now good evidence that epigenetic inheritance is ubiquitous and is involved in adaptive evolution and macroevolution. I argue that the many evolutionary consequences of epigenetic inheritance open up new research areas and require the extension of the evolutionary synthesis beyond the current neo-Darwinian model.
Stein, Dan J; Hermesh, Haggai; Eilam, David; Segalas, Cosi; Zohar, Joseph; Menchon, Jose; Nesse, Randolph M
The Modern Synthesis (MS) is the current paradigm in evolutionary biology. It was actually built by expanding on the conceptual foundations laid out by its predecessors, Darwinism and neo-Darwinism. For sometime now there has been talk of a new Extended Evolutionary Synthesis (EES), and this article begins to outline why we may need such an extension, and how it may come about. As philosopher Karl Popper has noticed, the current evolutionary theory is a theory of genes, and we still lack a theory of forms. The field began, in fact, as a theory of forms in Darwin's days, and the major goal that an EES will aim for is a unification of our theories of genes and of forms. This may be achieved through an organic grafting of novel concepts onto the foundational structure of the MS, particularly evolvability, phenotypic plasticity, epigenetic inheritance, complexity theory, and the theory of evolution in highly dimensional adaptive landscapes.
强化学习研究智能体如何从与环境的交互中学习最优的策略，以最大化长期奖赏。由于环境反馈的滞后性，强化学习问题面临巨大的决策空间，进行有效的搜索是获得成功学习的关键。以往的研究从多个角度对策略的搜索进行了探索，在搜索算法方面，研究结果表明基于演化优化的直接策略搜索方法能够获得优于传统方法的性能；在引入外部信息方面，通过加入用户提供的演示，可以有效帮助强化学习提高性能。然而，这两种有效方法的结合却鲜有研究。对用户演示与演化优化的结合进行研究，提出iNEAT+Q算法，尝试将演示数据通过预训练神经网络和引导演化优化的适应值函数的方式与演化强化学习方法结合。初步实验表明，iNEAT+Q较不使用演示数据的演化强化学习方法NEAT+Q有明显的性能改善。%Reinforcement learning aims at learning an optimal policy that maximizes the long term rewards, from interac-tions with the environment. Since the environment feedbacks commonly delay after a sequences of actions, reinforcement learning has to tackle the problem of searching in a huge policy space, and thus an effective search is the key to a success approach. Previous studies explore various ways to achieve effective search methods, one effective way is employing the evolutionary algorithm as the search method, and another direction is introducing user demonstration data to guide the search. In this work, it investigates the combination of the two directions, and proposes the iNEAT+Q approach, which trains a neural network using the demonstration data as well as integrating the demonstration data into the fitness function for the evolutionary algorithm. Preliminary empirical study shows that iNEAT+Q is superior to NEAT+Q, which is an classical evolutionary reinforcement learning approach.
Marisa Laporta Chudo
Full Text Available Objective. To analyze the teach-learning process of high school students, in the scope of Educational Biology. To plan and to develop a methodology with lesson strategies that facilitate the learning. To analyze, in the students vision, the positive and negative points in the process. Method. A research was developed -- of which had participated students of the first semester of the Pedagogy of a high school private institution in São Paulo city -- of the type action-research, with increased qualitative character of quantitative instruments; as a way of data collect, had been used questionnaires and field diary; the results had been converted in charts; after that, the data collected by the questionnaires had been analyzed according to the technique of the collective subject analysis. Results. The results had supplied important information to high school teachers reflection about teach-learning process, showing that the used strategies allowed student envolvement and participation, proximity with personal and professional reality, bigger interaction in the interpersonal relations and critical reflection. Conclusions. The theoretical referencial about adult learning, the active methodologies and the interpersonal relationship between professor and pupils, with the analysis of the students vision about the positive and negative points in the teach-learning process, had provided subsidies to believe a methodology and specific didactic strategies for adults and that must contemplate the teachers motivation and the pedagogical communication, including elements like creativity, up to date technician content and formative content to the future profession, experiences exchange, that allow an affective relationship teacher-student, with interaction and dialogue.
Full Text Available The young nervous system is primed for sensory learning, facilitating the acquisition of language and communication skills. Social and linguistic impoverishment can limit these learning opportunities, eventually leading to language-related challenges such as poor reading. Music training offers a promising auditory learning strategy by directing attention to meaningful acoustic elements in the soundscape. In light of evidence that music training improves auditory skills and their neural substrates, there are increasing efforts to enact community-based programs to provide music instruction to at-risk children. Harmony Project is a community foundation that has provided free music instruction to over 1,000 children from Los Angeles gang-reduction zones over the past decade. We conducted an independent evaluation of biological effects of participating in Harmony Project by following a cohort of children for one year. Here we focus on a comparison between students who actively engaged with sound through instrumental music training vs. students who took music appreciation classes. All children began with an introductory music appreciation class, but midway through the year half of the children transitioned to an instrumental training class. After the year of training, the children who actively engaged with sound through instrumental music training had faster and more robust neural processing of speech than the children who stayed in the music appreciation class, observed in neural responses to a speech sound /d/. The neurophysiological measures found to be enhanced in the instrumentally trained children have been previously linked to reading ability, suggesting a gain in neural processes important for literacy stemming from active auditory learning. These findings speak to the potential of active engagement with sound (i.e., music-making to engender experience-dependent neuroplasticity during trand may inform the development of strategies for auditory
Kraus, Nina; Slater, Jessica; Thompson, Elaine C; Hornickel, Jane; Strait, Dana L; Nicol, Trent; White-Schwoch, Travis
The young nervous system is primed for sensory learning, facilitating the acquisition of language and communication skills. Social and linguistic impoverishment can limit these learning opportunities, eventually leading to language-related challenges such as poor reading. Music training offers a promising auditory learning strategy by directing attention to meaningful acoustic elements of the soundscape. In light of evidence that music training improves auditory skills and their neural substrates, there are increasing efforts to enact community-based programs to provide music instruction to at-risk children. Harmony Project is a community foundation that has provided free music instruction to over 1000 children from Los Angeles gang-reduction zones over the past decade. We conducted an independent evaluation of biological effects of participating in Harmony Project by following a cohort of children for 1 year. Here we focus on a comparison between students who actively engaged with sound through instrumental music training vs. students who took music appreciation classes. All children began with an introductory music appreciation class, but midway through the year half of the children transitioned to the instrumental training. After the year of training, the children who actively engaged with sound through instrumental music training had faster and more robust neural processing of speech than the children who stayed in the music appreciation class, observed in neural responses to a speech sound /d/. The neurophysiological measures found to be enhanced in the instrumentally-trained children have been previously linked to reading ability, suggesting a gain in neural processes important for literacy stemming from active auditory learning. Despite intrinsic constraints on our study imposed by a community setting, these findings speak to the potential of active engagement with sound (i.e., music-making) to engender experience-dependent neuroplasticity and may inform the
Foong May Yeong
Full Text Available The use of class-response systems such as the Clickers to promote active-learning during lectures has been wide-spread. However, the often-used MCQ format in class activities as well as in assessments for large classes might lower students’ expectations and attitudes towards learning. Here, I describe my experience converting MCQs to constructed-response questions for in-class learning activities by removing cues from the MCQs. From the responses submitted, students seemed capable of providing answers without the need for cues. Using class-response systems such as Socrative for such constructed-response questions could be useful to challenge students to express their ideas in their own words. Moreover, by constructing their own answers, mis-conceptions could be revealed and corrected in a timely manner.
Sriram, Jayanthi Sanjeevi
Attrition in the STEM disciplines is a national problem and one of the important reasons for this is student experiences in introductory courses. A myriad of factors influence students' experiences in those courses; inadequate student preparation is one of the most cited reasons. Incoming freshmen often lack the learning strategies required to meaningfully learn and succeed in college courses. Unfortunately, the instructors have limited time and/or have little experience in teaching learning strategies. In this paper, the design, implementation, and evaluation of a Supplemental Course (SC) model that emphasizes learning strategies is presented. SC was offered concurrently with the introductory biology courses for four consecutive semesters (fall 2011 to spring 2013); for 10 weeks in fall 2012 and 7 weeks in the other semesters at Miami University. 10 weeks SC began earlier in the semester than the shorter SC. This study evaluated the effects of the SC on students' (1) performance in the introductory biology course, (2) perceived changes in self-regulation and social support, and (3) experiences in the introductory biology course before, during, and after participation in the SC. A mixed methods approach was used to address these goals. A pre-post survey was administered to obtain students' use of self-regulation strategies and social-support data. Quantitative methods were utilized to analyze content exam grades and changes in self-regulation strategies and social-support. To explore the experiences of the students, semi-structured interviews were conducted, followed by analysis using grounded theory. The findings reveal that participants of the longer duration SC (with an earlier start date) significantly improved in content exam performance, perceived use of self-regulation strategies, and social support compared to the non-participants. Participants of the shorter duration SC (with a later start date) did not significantly improve in content exam performance
Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck
This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.
Sastry, Anand; Monk, Jonathan M.; Tegel, Hanna
and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide...... the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. Availability and implementation: We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template...
When the environment in which an organism lives deviates in some essential way from that to which it is adapted, this is described as "evolutionary mismatch," or "evolutionary novelty." The notion of mismatch plays an important role, explicitly or implicitly, in evolution-informed cognitive psychology, clinical psychology, and medicine. The evolutionary novelty of our contemporary environment is thought to have significant implications for our health and well-being. However, scientists have generally been working without a clear definition of mismatch. This paper defines mismatch as deviations in the environment that render biological traits unable, or impaired in their ability, to produce their selected effects (i.e., to perform their proper functions in Neander's sense). The machinery developed by Millikan in connection with her account of proper function, and with her related teleosemantic account of representation, is used to identify four major types, and several subtypes, of evolutionary mismatch. While the taxonomy offered here does not in itself resolve any scientific debates, the hope is that it can be used to better formulate empirical hypotheses concerning the effects of mismatch. To illustrate, it is used to show that the controversial hypothesis that general intelligence evolved as an adaptation to handle evolutionary novelty can, contra some critics, be formulated in a conceptually coherent way.
Gibson, Mhairi A; Lawson, David W
Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. © 2015 Wiley Periodicals, Inc.
Gibson, Mhairi A; Lawson, David W
Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. PMID:25684561
Brown, Gillian R.; Dickins, Thomas E.; Sear, Rebecca; Laland, Kevin N.
Human beings persist in an extraordinary range of ecological settings, in the process exhibiting enormous behavioural diversity, both within and between populations. People vary in their social, mating and parental behaviour and have diverse and elaborate beliefs, traditions, norms and institutions. The aim of this theme issue is to ask whether, and how, evolutionary theory can help us to understand this diversity. In this introductory article, we provide a background to the debate surrounding how best to understand behavioural diversity using evolutionary models of human behaviour. In particular, we examine how diversity has been viewed by the main subdisciplines within the human evolutionary behavioural sciences, focusing in particular on the human behavioural ecology, evolutionary psychology and cultural evolution approaches. In addition to differences in focus and methodology, these subdisciplines have traditionally varied in the emphasis placed on human universals, ecological factors and socially learned behaviour, and on how they have addressed the issue of genetic variation. We reaffirm that evolutionary theory provides an essential framework for understanding behavioural diversity within and between human populations, but argue that greater integration between the subfields is critical to developing a satisfactory understanding of diversity. PMID:21199836