An Introduction to Programming for Bioscientists: A Python-based Primer

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a 'variable', the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.Comment: 65 pages total, including 45 pages text, 3 figures, 4 tables, numerous exercises, and 19 pages of Supporting Information; currently in press at PLOS Computational Biolog

Using ICT to support public and private community memories: case studies and lessons learned

Information communication technologies (ICTs) enable the development of memories across a variety of communities. We identify a spectrum of deployment from private through to open public spaces. As we move along this spectrum key variables change including mechanisms of trust and accountability and the definition of ownership, authorship and readership. Some challenges however, remain constant such as designing for sustainability and the need to align research and community goals. Private spaces can be created to enhance existing interactions, develop bonding capital and build shared memory. Such spaces allow a defined membership the opportunity to explore new ideas away from the public gaze, using language which may not be intelligible to outsiders. ICTs may be used to bridge internal and external audiences, repurposing content for a wider public. The original content may require alternative presentation, organisation or navigation methods to support its effective use by an external audience. Increasingly, community memories are being developed using social software within the public sphere, however this raises issues of authority, reputation management, and conflict resolution. Unexpected innovation may occur, and issues of sustainability must be addressed. In our analysis we will draw on three ICT initiatives in which we have participated: Bletchley Park Guides’ Forum, Bletchley Park Text and Milton Keynes Open Guide

BioMeRSA: The Biology media repository with semantic augmentation

With computers now capable of easily handling all kinds of multimedia files in vast quantity, and with the Internet now well-suited to exchange these files, we are faced with the challenge of organizing this data in such a way so as to make the information most useful and accessible. This holds true as well for media pertaining to the field of biology, where multimedia is particularly useful in education, as well as in research. To help address this, a software system with a Web-based interface has been developed for improving the accuracy and specificity of multimedia searching and browsing by integrating semantic data pertaining to the field of biology from the Unified Medical Language System (UMLS). Using the Biology Media Repository with Semantic Augmentation (BioMeRSA) system, users who are considered to be `experts\u27 can associate concepts from UMLS with multimedia files submitted by other users to provide semantic context for the files. These annotations are used to retrieve relevant files in the searching and browsing interfaces. A wide variety of image files are currently supported, with some limited support for video and audio files

WIZ-dynamic web-based course presentation system

Ankara : The Department of Computer Engineering and Information Science and Institute of Engineering and Science of Bilkent University, 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 93-94The educational potential of the World-Wide-Web is clear. It provides not only a means of communication, but, just as importantly, a means for storing and conveniently accessing a massive amount of information. Such characteristics make it an ideal platform for distance education. One limitation however is the fi.xed nature of the web itself, making guidance and individualized presentation difficult. This thesis presents a project, the WIZ s3'stem, aimed at overcoming this problem. The WIZ system is a dynamic hypermedia system that presents interactive courses over the Internet. It monitors the progress of each student in order to provide a presentation that best matches the individual. Students have the freedom to browse the course material but can return back to the guided presentation by simply clicking on a button. In addition, the WIZ s\'stem exploits the communication (newsgroup and email) facilities of the Internet in order to provide a collaborative discussion environment for courses. WIZ employs sound educational design and software engineering principles to generate affordable, individualized, interactive distance education, independent of time and location.Özhan, OzanM.S

Teaching machine translation and translation technology: a contrastive study

The Machine Translation course at Dublin City University is taught to undergraduate students in Applied Computational Linguistics, while Computer-Assisted Translation is taught on two translator-training programmes, one undergraduate and one postgraduate. Given the differing backgrounds of these sets of students, the course material, methods of teaching and assessment all differ. We report here on our experiences of teaching these courses over a number of years, which we hope will be of interest to lecturers of similar existing courses, as well as providing a reference point for others who may be considering the introduction of such material

A client-server software application for statistical analysis of fMRI data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.Includes bibliographical references (leaves 63-66).Statistical analysis methods used for interrogating functional magnetic resonance imaging (fMRI) data are complex and continually evolving. There exist a scarcity of educational material for fMRI. Thus, an instructional based software application was developed for teaching the fundamentals of statistical analysis in fMRI. For wider accessibility, the application was designed with a client/server architecture. The Java client has a layered design for flexibility and a nice Graphical User Interface (GUI) for user interaction. The application client can be deployed to multiple platforms in heterogeneous and distributed network. The future possibility of adding real-time data processing capabilities in the server led us to choose CGI/Perl/C as server side technologies. The client and server communicates via a simple protocol through the Apache Web Server. The application provides students with opportunities for hands-on exploration of the key concepts using phantom data as well as sample human fMRI data. The simulation allows students to control relevant parameters and observe intermediate results for each step in the analysis stream (spatial smoothing, motion correction, statistical model parameter selection etc.). Eventually this software tool and the accompanying tutorial will be disseminated to researchers across the globe via Biomedical Informatics Research Network (BIRN) portal.by Vijay Singh Choudhary.S.M

XCBC and XNIT - tools for cluster implementation and management in research and training

The Extreme Science and Engineering Discovery Environment has created a suite of software designed to facilitate the local management of computer clusters for scientific research and integration of such clusters with the US open research national cyberinfrastructure. This suite of software is distributed in two ways. One distribution is called the XSEDE-compatible basic cluster (XCBC), a Rocks Roll that does an “all at once, from scratch” installation of core components. The other distribution is called the XSEDE National Integration Toolkit (XNIT), so that specific tools can be downloaded and installed in portions as appropriate on existing clusters. In this paper, we describe the software included in XCBC and XNIT, and examine the use of XCBC installed on the LittleFe cluster design created by the Earlham College Cluster Computing Group as a teaching tool to show the deployment of XCBC from Rocks. In addition, the demonstration of the commercial Limulus HPC200 Deskside Cluster solution is shown as a viable, off-the-shelf cluster that can be adapted to become an XSEDE-like cluster through the use of the XNIT repository. We demonstrate that both approaches to cluster management – use of SCBC to build clusters from scratch and use of XNIT to expand capabilities of existing clusters – aid cluster administrators in administering clusters that are valuable locally and facilitate integration and interoperability of campus clusters with national cyberinfrastructure. We also demonstrate that very economical clusters can be useful tools in education and research.This document was developed with support from National Science Foundation (NSF) grant OCI-1053575. The LittleFe project has been funded in part by a grant from Intel, Inc. to Charlie Peck as well as NSF grants 1258604 and ACI-1347089. This research has also been supported in part by the Indiana University Pervasive Technology Institute, which was established with a major grant from the Lilly Endowment, Inc

T-CHAT educational framework for teaching cyber-physical system engineering

Cyber-physical systems (CPS) are increasingly used in manufacturing, transportation, health, and other industries. To develop these complex interdisciplinary systems, highly qualified CPS engineers are required who possess sound engineering knowledge and excellent transferable skills. Academic institutions offer a range of modules and curricula to teach CPS engineering. However, the literature reports a gap between expectations of industry and competencies of CPS graduates. To close this gap, this paper introduces and describes a holistic educational framework (T-CHAT) for teaching CPS engineering at the module level. To evaluate this framework, two use cases were analysed by conducting self-perception surveys and semi-structured interviews with students. Descriptive statistics and t-tests were calculated for the survey data. Interviews were coded and analysed using a General Inductive Approach. The analysis results were discussed by the comparison of the T-CHAT implementations in these two use cases

In-silico-Systemanalyse von Biopathways

Chen M. In silico systems analysis of biopathways. Bielefeld (Germany): Bielefeld University; 2004.In the past decade with the advent of high-throughput technologies, biology has migrated from a descriptive science to a predictive one. A vast amount of information on the metabolism have been produced; a number of specific genetic/metabolic databases and computational systems have been developed, which makes it possible for biologists to perform in silico analysis of metabolism. With experimental data from laboratory, biologists wish to systematically conduct their analysis with an easy-to-use computational system. One major task is to implement molecular information systems that will allow to integrate different molecular database systems, and to design analysis tools (e.g. simulators of complex metabolic reactions). Three key problems are involved: 1) Modeling and simulation of biological processes; 2) Reconstruction of metabolic pathways, leading to predictions about the integrated function of the network; and 3) Comparison of metabolism, providing an important way to reveal the functional relationship between a set of metabolic pathways. This dissertation addresses these problems of in silico systems analysis of biopathways. We developed a software system to integrate the access to different databases, and exploited the Petri net methodology to model and simulate metabolic networks in cells. It develops a computer modeling and simulation technique based on Petri net methodology; investigates metabolic networks at a system level; proposes a markup language for biological data interchange among diverse biological simulators and Petri net tools; establishes a web-based information retrieval system for metabolic pathway prediction; presents an algorithm for metabolic pathway alignment; recommends a nomenclature of cellular signal transduction; and attempts to standardize the representation of biological pathways. Hybrid Petri net methodology is exploited to model metabolic networks. Kinetic modeling strategy and Petri net modeling algorithm are applied to perform the processes of elements functioning and model analysis. The proposed methodology can be used for all other metabolic networks or the virtual cell metabolism. Moreover, perspectives of Petri net modeling and simulation of metabolic networks are outlined. A proposal for the Biology Petri Net Markup Language (BioPNML) is presented. The concepts and terminology of the interchange format, as well as its syntax (which is based on XML) are introduced. BioPNML is designed to provide a starting point for the development of a standard interchange format for Bioinformatics and Petri nets. The language makes it possible to exchange biology Petri net diagrams between all supported hardware platforms and versions. It is also designed to associate Petri net models and other known metabolic simulators. A web-based metabolic information retrieval system, PathAligner, is developed in order to predict metabolic pathways from rudimentary elements of pathways. It extracts metabolic information from biological databases via the Internet, and builds metabolic pathways with data sources of genes, sequences, enzymes, metabolites, etc. The system also provides a navigation platform to investigate metabolic related information, and transforms the output data into XML files for further modeling and simulation of the reconstructed pathway. An alignment algorithm to compare the similarity between metabolic pathways is presented. A new definition of the metabolic pathway is proposed. The pathway defined as a linear event sequence is practical for our alignment algorithm. The algorithm is based on strip scoring the similarity of 4-hierarchical EC numbers involved in the pathways. The algorithm described has been implemented and is in current use in the context of the PathAligner system. Furthermore, new methods for the classification and nomenclature of cellular signal transductions are recommended. For each type of characterized signal transduction, a unique ST number is provided. The Signal Transduction Classification Database (STCDB), based on the proposed classification and nomenclature, has been established. By merging the ST numbers with EC numbers, alignments of biopathways are possible. Finally, a detailed model of urea cycle that includes gene regulatory networks, metabolic pathways and signal transduction is demonstrated by using our approaches. A system biological interpretation of the observed behavior of the urea cycle and its related transcriptomics information is proposed to provide new insights for metabolic engineering and medical care