Grammatical equivalents of Palaeolithic tools: a hypothesis

In this article, language is considered as a behavioural trait evolving by means of natural selection, in co-evolution with the Palaeolithic tool industries. This perspective enables an analysis of the grammatical and syntactic equivalents of the multiple abilities and effects of lithic tools across the successive modes of their development and consider their influence in intra-group communication and the social biology of the hominine species concerned. The hypothesis is that grammatical equivalents inherent to stone tool work guide the evolution of language.     

Tools for loading MEDLINE into a local relational database

Background  

Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.     

A scenario-based approach to modeling development: a prototype model of C. elegans vulval fate specification

Studies of developmental biology are often facilitated by diagram “models” that summarize the current understanding of underlying mechanisms. The increasing complexity of our understanding of development necessitates computational models that can extend these representations to include their dynamic behavior. Here we present a prototype model of Caenorhabditis elegans vulval precursor cell fate specification that represents many processes crucial for this developmental event but that are hard to integrate using other modeling methodologies. We demonstrate the integrative capabilities of our methodology by comprehensively incorporating the contents of three seminal papers, showing that this methodology can lead to comprehensive models of developmental biology. The prototype computational model was built and is run using a language (Live Sequence Charts) and tool (the Play-Engine) that facilitate the same conceptual processes biologists use to construct and probe diagram-type models. We demonstrate that this modeling approach permits rigorous tests of mutual consistency between experimental data and mechanistic hypotheses and can identify specific conflicting results, providing a useful approach to probe developmental systems.     

Response by H. H. Pattee to Jon Umerez’s Paper: “Where Does Pattee’s “How Does a Molecule Become a Message?” Belong in the History of Biosemiotics?”

Umerez’s analysis made me aware of the fundamental differences in the culture of physics and molecular biology and the culture of semiotics from which the new field of biosemiotics arose. These cultures also view histories differently. Considering the evolutionary span and the many hierarchical levels of organization that their models must cover, models at different levels will require different observables and different meanings for common words, like symbol, interpretation, and language. These models as well as their histories should be viewed as complementary rather than competitive. The relation of genetic language and human language is the central issue. They are separated by 4 billion years and require entirely different models. Nevertheless, these languages have in common a unique unlimited expressive power that allows open-ended evolution and creative thought. Understanding the nature of this expressive power and how it arises remains a basic unsolved problem of biosemiotics.     

Ndumba Folk Biology and General Principles of Ethnobotanical Classification and Nomenclature

Brent Berlin's proposed "general principles of classification and nomenclature" are examined as they apply to folk biology in Ndumba, a Papua New Guinea highlands society. Focusing on Ndumba folk zoology, supplemented with a previous analysis of their folk botany, Berlin's analytical schema for ethnobiological classification is supported, but principles of nomenclature in ethnobiology appear to be in need of reconsideration. [ethnosemantics, folk biology, language universals, Papua New Guinea]     

Bio-Ontology and text: bridging the modeling gap

MOTIVATION: Natural language processing (NLP) techniques are increasingly being used in biology to automate the capture of new biological discoveries in text, which are being reported at a rapid rate. Yet, information represented in NLP data structures is classically very different from information organized with ontologies as found in model organisms or genetic databases. To facilitate the computational reuse and integration of information buried in unstructured text with that of genetic databases, we propose and evaluate a translational schema that represents a comprehensive set of phenotypic and genetic entities, as well as their closely related biomedical entities and relations as expressed in natural language. In addition, the schema connects different scales of biological information, and provides mappings from the textual information to existing ontologies, which are essential in biology for integration, organization, dissemination and knowledge management of heterogeneous phenotypic information. A common comprehensive representation for otherwise heterogeneous phenotypic and genetic datasets, such as the one proposed, is critical for advancing systems biology because it enables acquisition and reuse of unprecedented volumes of diverse types of knowledge and information from text. RESULTS: A novel representational schema, PGschema, was developed that enables translation of phenotypic, genetic and their closely related information found in textual narratives to a well-defined data structure comprising phenotypic and genetic concepts from established ontologies along with modifiers and relationships. Evaluation for coverage of a selected set of entities showed that 90% of the information could be represented (95% confidence interval: 86-93%; n = 268). Moreover, PGschema can be expressed automatically in an XML format using natural language techniques to process the text. To our knowledge, we are providing the first evaluation of a translational schema for NLP that contains declarative knowledge about genes and their associated biomedical data (e.g. phenotypes). AVAILABILITY: http://zellig.cpmc.columbia.edu/PGschema     

Applications of a formal approach to decipher discrete genetic networks

Background  

A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language.     

THE CLASSIFICATION OF PROBOSCIDEA: HOW MANY CLADISTIC CLASSIFICATIONS?

Abstract— Hennig conceived a method to build a "phylogenetic system", with the stipulation that a "properly drawn phylogenetic tree must be directly translatable into the language of phylogenetic systematics". Consequently, this system could be the general reference system of biology. A review of the classificatory technical improvements, conventions and rules which have been proposed for the past twenty years together with their application to the classification of the Proboscidea, leads to the conclusion that more than one formal system can be built upon one given cladogram. As words are used more frequently for communication than diagrams, schemes or graphs, the "general reference system of biology1' remains somewhere in Utopia. The "phylogenetic system" is rather more synonymous with a cladogram than with a written classification.     

Benchmarking natural-language parsers for biological applications using dependency graphs

Background  

Interest is growing in the application of syntactic parsers to natural language processing problems in biology, but assessing their performance is difficult because differences in linguistic convention can falsely appear to be errors. We present a method for evaluating their accuracy using an intermediate representation based on dependency graphs, in which the semantic relationships important in most information extraction tasks are closer to the surface. We also demonstrate how this method can be easily tailored to various application-driven criteria.     

MBEToolbox: a Matlab toolbox for sequence data analysis in molecular biology and evolution

Background  

MATLAB is a high-performance language for technical computing, integrating computation, visualization, and programming in an easy-to-use environment. It has been widely used in many areas, such as mathematics and computation, algorithm development, data acquisition, modeling, simulation, and scientific and engineering graphics. However, few functions are freely available in MATLAB to perform the sequence data analyses specifically required for molecular biology and evolution.     

《生物化学》作为通识课的教学实践

生物化学研究生命的化学组成和化学变化等生命基本属性,是阐述生命奥秘的基本语言,是生命科学的基础学科。生物化学能否作为公选课?如果其作为公选课,又应包含哪些生物化学知识,如何讲授这些专业知识?本文从课程内容,教材选取以及授课方式等方面介绍了笔者在向非健康科学专业的学生开设《生物化学》公选课的实践和体会。笔者联系身边的生物化学现象讲解其中的基本生物化学原理,关注疾病发生和临床治疗中涉及的生物化学,整合本校生命和健康相关学科和最前沿的科学进展中涉及到的生物化学知识,极大地增强了学生对生物化学和生命科学的兴趣,有效提高了教学效果;并且为学生理解其它生命科学选修课程打下了良好的基础。这些策略和教学方法对于公选课和通识课,甚至专业课的教学实践,具有一定的参考价值。     

Synthetic biology: building the language for a new science brick by metaphorical brick

Changes in the biosciences and their relations to society over the last decades provide a unique opportunity to examine whether or not such changes leave traces in the language we use to talk about them. In this article we examine metaphors used in English-speaking press coverage to conceptualize a new type of (interdisciplinary) bioscience: synthetic biology. Findings show that three central metaphors were used between 2008 and May 2010. They exploit social and cultural knowledge about books, computers and engines and are linked to knowledge of three revolutions in science and society (the printing, information and industrial revolutions). These three central metaphors are connected to each other through the concepts of reading/writing, designing and mass production and they focus on science as a revolutionary process rather than on the end results or products of science. Overall, we observed the use of a complex bricolage of mixed metaphors and chains of metaphors that root synthetic biology in historical events and achievements, while at the same time extolling its promises for the future.     

The layer-oriented approach to declarative languages for biological modeling

We present a new approach to modeling languages for computational biology, which we call the layer-oriented approach. The approach stems from the observation that many diverse biological phenomena are described using a small set of mathematical formalisms (e.g. differential equations), while at the same time different domains and subdomains of computational biology require that models are structured according to the accepted terminology and classification of that domain. Our approach uses distinct semantic layers to represent the domain-specific biological concepts and the underlying mathematical formalisms. Additional functionality can be transparently added to the language by adding more layers. This approach is specifically concerned with declarative languages, and throughout the paper we note some of the limitations inherent to declarative approaches. The layer-oriented approach is a way to specify explicitly how high-level biological modeling concepts are mapped to a computational representation, while abstracting away details of particular programming languages and simulation environments. To illustrate this process, we define an example language for describing models of ionic currents, and use a general mathematical notation for semantic transformations to show how to generate model simulation code for various simulation environments. We use the example language to describe a Purkinje neuron model and demonstrate how the layer-oriented approach can be used for solving several practical issues of computational neuroscience model development. We discuss the advantages and limitations of the approach in comparison with other modeling language efforts in the domain of computational biology and outline some principles for extensible, flexible modeling language design. We conclude by describing in detail the semantic transformations defined for our language.     

GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles

Systems that extract structured information from natural language passages have been highly successful in specialized domains. The time is opportune for developing analogous applications for molecular biology and genomics. We present a system, GENIES, that extracts and structures information about cellular pathways from the biological literature in accordance with a knowledge model that we developed earlier. We implemented GENIES by modifying an existing medical natural language processing system, MedLEE, and performed a preliminary evaluation study. Our results demonstrate the value of the underlying techniques for the purpose of acquiring valuable knowledge from biological journals.     

Evolving strategies for the incorporation of bioinformatics within the undergraduate cell biology curriculum

Recent advances in genomics and structural biology have resulted in an unprecedented increase in biological data available from Internet-accessible databases. In order to help students effectively use this vast repository of information, undergraduate biology students at Drake University were introduced to bioinformatics software and databases in three courses, beginning with an introductory course in cell biology. The exercises and projects that were used to help students develop literacy in bioinformatics are described. In a recently offered course in bioinformatics, students developed their own simple sequence analysis tool using the Perl programming language. These experiences are described from the point of view of the instructor as well as the students. A preliminary assessment has been made of the degree to which students had developed a working knowledge of bioinformatics concepts and methods. Finally, some conclusions have been drawn from these courses that may be helpful to instructors wishing to introduce bioinformatics within the undergraduate biology curriculum.     

Zsyntax: A Formal Language for Molecular Biology with Projected Applications in Text Mining and Biological Prediction

We propose a formal language that allows for transposing biological information precisely and rigorously into machine-readable information. This language, which we call Zsyntax (where Z stands for the Greek word ζωή, life), is grounded on a particular type of non-classical logic, and it can be used to write algorithms and computer programs. We present it as a first step towards a comprehensive formal language for molecular biology in which any biological process can be written and analyzed as a sort of logical “deduction”. Moreover, we illustrate the potential value of this language, both in the field of text mining and in that of biological prediction.     

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models

MOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/