PaVESy: Pathway Visualization and Editing System

A data managing system for editing and visualization of biological pathways is presented. The main component of PaVESy (Pathway Visualization and Editing System) is a relational SQL database system. The database design allows storage of biological objects, such as metabolites, proteins, genes and respective relations, which are required to assemble metabolic and regulatory biological interactions. The database model accommodates highly flexible annotation of biological objects by user-defined attributes. In addition, specific roles of objects are derived from these attributes in the context of user-defined interactions, e.g. in the course of pathway generation or during editing of the database content. Furthermore, the user may organize and arrange the database content within a folder structure and is free to group and annotate database objects of interest within customizable subsets. Thus, we allow an individualized view on the database content and facilitate user customization. A JAVA-based class library was developed, which serves as the database programming interface to PaVESy. This API provides classes, which implement the concepts of object persistence in SQL databases, such as entries, interactions, annotations, folders and subsets. We created editing and visualization tools for navigation in and visualization of the database content. User approved pathway assemblies are stored and may be retrieved for continued modification, annotation and export. Data export is interfaced with a range of network visualization programs, such as Pajek or other software allowing import of SBML or GML data format. AVAILABILITY: http://pavsey.mpimp-golm.mpg.de     

Essentialism, history, and biological taxa

de Queiroz (1995), Griffiths (1999) and LaPorte (2004) offer a new version of essentialism called "historical essentialism". According to this version of essentialism, relations of common ancestry are essential features of biological taxa. The main type of argument for this essentialism proposed by Griffiths (1999) and LaPorte (2004) is that the dominant school of classification, cladism, defines biological taxa in terms of common ancestry. The goal of this paper is to show that this argument for historical essentialism is unsatisfactory: cladism does not assume that relations of common ancestry are essential attributes of biological taxa. Therefore, historical essentialism is not justified by cladism.     

Contrasting Patterns in Solitary and Eusocial Bees While Responding to Landscape Features in the Brazilian Cerrado: a Multiscaled Perspective

Landscape structure is an important determinant of biological fluxes and species composition, but species do not respond equally to landscape features or spatial extents. Evaluating “multi-scale” responses of species to landscape structure is an important framework to be considered, allowing insights about habitat requirements for different groups. We evaluated the response of Brazilian Cerrado’s bees (eusocial vs. solitary ones) to both the amount and isolation of remnant vegetation in eight nested multiple-local scales. Response variables included abundance, observed, and estimated species richness, and beta diversity (split into nestedness and turnover resultant dissimilarities). Eusocial species’ abundance responded to landscape structure at narrow scales of fragment isolation (250 m of radius from sampling sites), while solitary species’ abundance responded to broader scales to fragment area (2000 m). Eusocial species nestedness also responded to landscape features in broader scales (1500 m), especially to increasing fragment isolation. However, all the remaining response variables did not respond to any other landscape variables in any spatial scale considered. Such contrasting responses of the abundances of eusocial vs. solitary species are related to the inherent life-history traits of each group. Important attributes in this context are different requirements on food resources, population features, and flight abilities. Species-specific dispersal abilities may be the main determinants of the nested patterns found for eusocial species at 1500 m. Considering these results, we suggest that different bee groups are considered separately in further landscape analyses, especially in other Brazilian biomes, for a better understanding of landscape effects on these organisms.     

Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online)

Background

An adequate and expressive ontological representation of biological organisms and their parts requires formal reasoning mechanisms for their relations of physical aggregation and containment.

Results

We demonstrate that the proposed formalism allows to deal consistently with "role propagation along non-taxonomic hierarchies", a problem which had repeatedly been identified as an intricate reasoning problem in biomedical ontologies.

Conclusion

The proposed approach seems to be suitable for the redesign of compositional hierarchies in (bio)medical terminology systems which are embedded into the framework of the OBO (Open Biological Ontologies) Relation Ontology and are using knowledge representation languages developed by the Semantic Web community.     

Towards teaching for an integrated understanding of trait formation: an analysis of genetics tasks in high school biology textbooks

ABSTRACT

This paper reports on findings from an analysis of trait-formation tasks in the genetic sections of high school biology textbooks. Drawing on studies exploring a range of problems in students’ explanations of trait formation, we investigated trait-formation tasks and analysed their potential for knowledge integration and multi-level mechanistic reasoning. Among the 216 trait-formation tasks, 39 tasks (18%) were classified as integrative tasks addressing the relationships between genes, proteins and traits. The remaining 177 tasks (82%) were non-integrative tasks addressing selected aspects of the relationship between genes and proteins alone, respectively the relationship between proteins and traits alone. Among the non-integrative tasks, 64% addressed the molecular level alone and thus did not encourage students to address the higher levels of biological organisation. 13% of the non-integrative tasks (n = 23) and 5% of the integrative tasks (n = 2) addressed the role of the environment in trait formation. The findings are related to three main arguments from the genetics literature, concerning knowledge integration and multi-level mechanistic reasoning. As educational implications, we recommend that biology educators make use of integrative tasks to foster students’ understanding of trait formation from an integrated model connecting genes, proteins, environmental factors and traits to overcome gene-centred and gene-deterministic beliefs.     

An integrated rule- and case-based approach to AIDS initial assessment

The traditional approach to the development of knowledge-based systems (KBS) has been rule-based, where heuristic knowledge is encoded in a set of production rules. A rule-based reasoning (RBR) system needs a well constructed domain theory as its reasoning basis, and it does not make substantial use of the knowledge embedded in previous cases. An RBR system performs relatively well in a knowledge-rich application environment. Although its capability may be limited when previous experiences are not a good representation of the whole population, a case-based reasoning (CBR) system is capable of using past experiences as problem solving tools, therefore, it is appropriate for an experience-rich domain. In recent years, both RBR and CBR have emerged as important and complementary reasoning methodologies in artificial intelligence. For problem solving in AIDS intervention and prevention, it is useful to integrate RBR and CBR. In this paper, a hybrid KBS which integrates a deductive RBR system and an inductive CRB system is proposed to assess AIDS-risky behaviors.     

Procedures for Studying the Mechanism of Speech Development

Special education and special psychology deal with children whose development shows certain aberrations. To organize remedial measures, it is important to determine the specific features of these aberrations; but this is possible only if we have knowledge of the laws of development under normal conditions. This knowledge is necessary for specialists in abnormal development for other purposes as well. It is necessary in itself. As a number of studies have shown, the main tendency of development in various types of anomalies, with a range of distinctive features, is the same as that under normal conditions. The general laws of development of human functions under normal and pathological conditions are also similar under a variety of different influences.     

小鼠腺苷脱氨酶mRNA特异Ribozyme计算机设计

小鼠腺苷脱氨酶mRNA经计算机分析,包括:ribozyme切点位置选择,二级结构预测,基因生物学功能和基因同源性分析,筛选出四个锤头结构ribozyme.结果表明上述ribozyme底物切点两翼碱基形成发夹结构,切点位于单链环区,切点所在基因片段位于该基因生物功能区内,并同已知小鼠其它基因不同源.     

On predictions and laws in biological evolution: Is biology able to formulate general laws and develop inductive predictions as in physics or chemistry?

Biology has so far had difficulties formulating general laws akin to physics and chemistry. Evolution and its propensity to reduce entropy could become a start for such laws in biology. Subject Categories: Evolution & Ecology, History & Philosophy of Science

Science uses evidence‐based inductive reasoning to build theories, principles, and laws. A common type of inductive reasoning is generalization, that is, projecting conclusions drawn from one or a few case studies onto a broader context. The reliability of generalizations depends upon the representativeness and the formal validation of the selected case studies, which is usually performed by hypothesis testing. Another usual type of inductive reasoning is prediction, which uses observations to develop general principles and laws that can predict or anticipate future outcomes. The reliability of these predictions is confirmed by the accomplishment of the anticipated situation. It is interesting to note that generalizations are based on the analysis of empirical evidence, whereas predictions are formulated before the desired empirical evidence, which is actually the target of the prediction, is available.

… generalizations are based on the analysis of empirical evidence, whereas predictions are formulated before the desired empirical evidence, which is actually the target of the prediction, is available.

The American philosopher of science Peter Lipton (2005) commented that we are commonly more impressed by predictions than by accommodations, as he called hypothesis testing. To illustrate this, Lipton used the discovery of Halley''s Comet. In 1705, the British astronomer Edmond Halley proposed that the comets observed in 1531, 1607, and 1682 were actually the same comet with a periodic elliptical orbit. Back then, his hypothesis did not have much impact within the scientific community. However, when Halley''s prediction was confirmed in 1758 by the return of the comet, the intellectual world in Europe widely accepted the existence of a single comet, which was subsequently named Halley''s Comet. Halley''s prediction may seem straightforward, even trivial, considering the characteristic periodicity of 75 years in previous observations. Yet, it was the predictive success, rather than prior observations, that convinced the scientific community of his conclusion.Physics is considered one of the strongest branches of science—along with chemistry and mathematics—in regard to the generality and accuracy of its predictions. Biology seems still to be in its infancy, and the search for regularities that could lend to potential generalizations is the most common approach (Dodds, 2009). This is due in part to the high level of complexity of the living world, its evolutionary change over time, and its relationships with the environment. As emphasized by the German evolutionary biologist Ernst Mayr (2004), these intrinsic and unique features of living beings, which are intimately associated with the genetic code, clearly differentiate biology from other natural sciences and make the fundamental laws of physics and chemistry insufficient to understand the living world.The main aim of this essay is to discuss whether biological research is able to develop inductive predictions similar to physics or chemistry. First, I present some classical examples of physical and chemical discoveries based on inductive predictions, such as the Higgs boson, interstellar dark matter, and the periodic table of elements. As all these advances are based on the previous existence of fundamental laws, the question arises whether similar laws exist in biology to support physics‐like inductive predictions. I suggest that, if these laws exist, they should emerge from the evolutionary process, which is the main biological singularity. Thus, it should be possible to make inductive predictions based on the fossil record, which is the fundamental evolutionary evidence. Indeed, it seems that the lack of evolutionary laws is the main drawback for inductive prediction in studying evolution, which cannot escape to Lipton’s accommodation procedures, that is, hypothesis testing and generalization.

Physics is considered one of the strongest branches of science – along with chemistry and mathematics – in regard to the generality and accuracy of its predictions.

     

基于二叉分类推理的昆虫分类辅助鉴定多媒体专家系统通用平台TaxoKeys的设计与开发

本文详细介绍了基于二叉式分类推理的昆虫分类辅助鉴定多媒体专家系统通用平台TaxoKeys的设计与开发,及其所具备的主要特点。该研究根据昆虫分类学的特点,将昆虫分类的两项式检索表用数据库表示成系统知识库,利用计算机数据结构中二叉树结构的分枝结点搜索技术来实现其推理过程,进行昆虫分类的辅助鉴定,为昆虫分类专家提供一个通用专家系统平台。该系统具有可扩充性好、设计简单、操作方便等特点,同时也适用于一般性生物分类鉴定。另外,本文还就本系统功能的进一步扩展与应用研究等进行了探讨。     

Spatial and temporal relation rule acquisition of eutrophication in Da’ning River based on rough set theory

Since the mechanisms of eutrophication are complicated and many other factors affect these mechanisms, methods such as quantitative statistics and numerical simulation, have their limitations in analyzing the spatiotemporal relations of eutrophication. The rough set theory (RST) was used to describe the spatiotemporal relations of eutrophication in Da’ning River without any of other prior knowledge. Rules of relations in time and space affecting eutrophication in the Da’ning River backwater area were extracted by taking representation of relations in time and space among eutrophication at a long river section of Da’ning River backwater area, by taking nine sets of encrypted monitoring data in 2003 as example, and by making season, area and eutrophication level as the decision attributes, respectively, to represent specific features of the eutrophication phenomenon in the Da’ning River backwater area from the points of view of time, space, and level by analysis of spatiotemporal relationship rules. This study result shows that the temporal and spatial differences between eutrophication phenomena in the long river section of the Da’ning River backwater area are significant. Eutrophication for each section is less serious in autumn, more in spring and most in summer. Eutrophication degree gradually decreases from estuary to upstream, which is in conformity with reality. The RST of eutrophication in Da’ning River may inform environmental decision-makers and assist them in making more cost-effective decisions.     

Cellular nucleic acid binding protein binds G-rich single-stranded nucleic acids and may function as a nucleic acid chaperone

Cellular nucleic acid binding protein (CNBP) is a small single-stranded nucleic acid binding protein made of seven Zn knuckles and an Arg-Gly rich box. CNBP is strikingly conserved among vertebrates and was reported to play broad-spectrum functions in eukaryotic cells biology. Neither its biological function nor its mechanisms of action were elucidated yet. The main goal of this work was to gain further insights into the CNBP biochemical and molecular features. We studied Bufo arenarum CNBP (bCNBP) binding to single-stranded nucleic acid probes representing the main reported CNBP putative targets. We report that, although bCNBP is able to bind RNA and single-stranded DNA (ssDNA) probes in vitro, it binds RNA as a preformed dimer whereas both monomer and dimer are able to bind to ssDNA. A systematic analysis of variant probes shows that the preferred bCNBP targets contain unpaired guanosine-rich stretches. These data expand the knowledge about CNBP binding stoichiometry and begins to dissect the main features of CNBP nucleic acid targets. Besides, we show that bCNBP presents a highly disordered predicted structure and promotes the annealing and melting of nucleic acids in vitro. These features are typical of proteins that function as nucleic acid chaperones. Based on these data, we propose that CNBP may function as a nucleic acid chaperone through binding, remodeling, and stabilizing nucleic acids secondary structures. This novel CNBP biochemical activity broadens the field of study about its biological function and may be the basis to understand the diverse ways in which CNBP controls gene expression.     

Mutation-absorption model of the enzyme

Gradual changes in function of proteins in response to single changes in primary structure are often observed to occur and are a necessary condition for evolution by variation and natural selection at the protein level. A probabilistic (entropy theory_ analysis of the effect of changes in primary structure on three-dimensional shape and function shows that such gradualism is based on the presence of a control system in the molecule involving a definite general form of structure-function degeneracy. The assumptions of the analysis are that primary structure determines tertiary structure (or a thermal distribution of tertiary configurations and allosteric forms), tertiary structure determines function (characterized by rate and other parameters), and that certain features of tertiary structure may be specialized for particular functions. The main conclusion is that embodied in the molecule is a subsystem which serves as a buffer, absorbing mutation or other forms of genetic variation and expressing these as graceful variations in features of the shape critical for function. This buffer system may be realized by numerical redundancy of amino acids or other mechanisms which increase the redundancy of weak interactions responsible for folding, utilization of amino acids having a greater number of analogs with redundant features, or local and global structural formats which allow for more effective utilization of redundancy. The mutation-absorption model has implications for the interpretation of structure-function relations in biology, the topology of the adaptive landscape, the interpretation of isoenzymes and allozymes, the relationship between selection and neutralism in evolution, and the relation between the complexity of and energy required by biological systems and the effectiveness of evolutionary optimization.     

A probabilistic methodology for integrating knowledge and experiments on biological networks.

Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed experiments. Modern experimental techniques provide massive data on the global behavior of biological systems, and systematically using these large datasets for refining existing knowledge is a major challenge. Here we introduce an extended computational framework that combines formalization of existing qualitative models, probabilistic modeling, and integration of high-throughput experimental data. Using our methods, it is possible to interpret genomewide measurements in the context of prior knowledge on the system, to assign statistical meaning to the accuracy of such knowledge, and to learn refined models with improved fit to the experiments. Our model is represented as a probabilistic factor graph, and the framework accommodates partial measurements of diverse biological elements. We study the performance of several probabilistic inference algorithms and show that hidden model variables can be reliably inferred even in the presence of feedback loops and complex logic. We show how to refine prior knowledge on combinatorial regulatory relations using hypothesis testing and derive p-values for learned model features. We test our methodology and algorithms on a simulated model and on two real yeast models. In particular, we use our method to explore uncharacterized relations among regulators in the yeast response to hyper-osmotic shock and in the yeast lysine biosynthesis system. Our integrative approach to the analysis of biological regulation is demonstrated to synergistically combine qualitative and quantitative evidence into concrete biological predictions.     

Organisms as Functional Machines: A Connectivity Explanation

Living organisms exist as a complex set of levels of organizationarranged in a pattern of strong ordering with none of theselevels being more important than others for a full understandingof life. Central to biological strong ordering is the organismallevel. Individual organisms are of special interest to biologistsbecause they are relevant to all biological processes regardlessof the operational level of the process. This is especiallytrue for investigations of the morphological-physiological propertiesof organisms. For such studies, living organisms must be consideredas complex machines with all of the sophisticated integrationand multifarious interactions of component parts typical ofcomplex systems. Understanding of the properties of any individualfeature in an organism depends as much, or possibly even more,on an appreciation of its connections and interactions withother features of that organism than on an understanding ofits intrinsic attributes. Learning the connectivity skills,including the modes of thinking, needed to comprehend the integrationof diverse components of any complex system requires a differenttraining than that needed to determine the detailed attributesof individual parts; both are necessary, however, to achieveproper advances in biological knowledge. Case studies of severalvertebrate features will be used to illustrate types of interactionswhich exist between structural/functional attributes, and howtheir recognition can lead to new and interesting questions.This "feeling for the organism" may be the major factor separatingthose biologists who are able to make important discoveriesfrom those who will only provide the subsequent, less excitingdetails of normal science.     

土族生物资源利用相关的传统知识多样性

生物资源利用相关的传统知识是对生物资源进行识别和利用的传统知识系统。随着现代生物技术的发展, 这类传统知识显示出其在科学、经济、文化乃至粮食安全战略方面的价值。本研究根据《生物多样性相关传统知识分类、调查与编目技术规定(试行)》, 对我国青海省土族聚集区的土族生物资源利用相关的传统知识进行了系统调查与编目, 并借鉴生物多样性测度方法, 创建了传统知识多样性指数计算方法, 对土族生物资源利用相关传统知识多样性进行分析。结果如下: (1)编目现存的土族生物资源利用相关的传统知识词条共424条; (2)土族传统知识的α多样性指数D_TK = 0.67, 表明其传统知识多样性较高; 土族传统知识的β_wtk多样性指数在不同的县域差异较大, 表明其在县域之间存在差异, 在空间上分布不连续、不均匀。本研究利用生物多样性指数验证了传统知识的定量研究方法, 说明传统知识多样性指数不仅可用于定量研究表征区域传统知识的多样性, 揭示不同空间区域内的分布特征, 还可为未来构建传统知识的定量研究体系提供重要的参考依据。     

Reasoning in uncertainties. An analysis of five strategies and their suitability in pathology

In reasoning systems, uncertainty plays a crucial part, especially for those fields in which judgements are essential, as in pathology. Uncertainty has several aspects, such as prevalence of diseases, occurrence of findings and the sensitivity and predictive value of findings. For the functioning of a reasoning system, two aspects are crucial: (1) the internal representation of the uncertainty and (2) the way in which the uncertainty is propagated in the reasoning process when combining formal statements. Five well-known reasoning strategies (Bayes' probability theory, MYCIN's certainty factor model, fuzzy set theory, the theory of Dempster-Shafer and Pathfinder's scoring mechanism) are compared, with particular attention to: (1) Under what conditions will the model function? In particular, what information is to be specified a priori to the system? (2) Can the different aspects of uncertainty be dealt with as separate entities? (3) How are unknown uncertainties dealt with? (4) How is evidence in favor of a hypothesis combined with evidence against it? (5) How does the model treat the simultaneous occurrence of more than one disorder, that is, how does the model support reasoning with compound hypotheses? It is preliminarily concluded that the different aspects of uncertainty are expressed as separate entities only in Pathfinder and probability theory. Hence, the other models do not accurately represent uncertain knowledge. Also, such theoretically attractive models as the Bayes, MYCIN and Dempster-Shafer theory can only function properly under the tight condition of mutual exclusiveness of hypotheses, which is not always suited for broader areas of pathology. They may, however, be suited for smaller areas, with a limited number of defined diseases and a limited number of features. All models but the Bayes model lack a predictable performance since there is no (or only a partial) underlying theory to guarantee minimization of the overall error.