Genetics, Bioinformatics, and Biomedical Research

Fiji: an open-source platform for biological-image analysis

Bioconductor: open software development for computational biology and bioinformatics

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.

Current protocols in molecular biology

Biopython: freely available Python tools for computational molecular biology and bioinformatics

Abstract Summary: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Availability: Biopython is freely available, with documentation and source code at www.biopython.org under the Biopython license. Contact: All queries should be directed to the Biopython mailing lists, see www.biopython.org/wiki/_Mailing_listspeter.cock@scri.ac.uk.

Molecular Biology of the Cell

As the amount of information in biology expands dramatically, it becomes increasingly important for textbooks to distill the vast amount of scientific knowledge into concise principles and enduring concepts.As with previous editions, Molecular Biology of the Cell, Sixth Edition accomplishes this goal with clear writing and beautiful illustrations. The Sixth Edition has been extensively revised and updated with the latest research in the field of cell biology, and it provides an exceptional framework for teaching and learning. The entire illustration program has been greatly enhanced.Protein structures better illustrate structure–function relationships, icons are simpler and more consistent within and between chapters, and micrographs have been refreshed and updated with newer, clearer, or better images. As a new feature, each chapter now contains intriguing openended questions highlighting “What We Don’t Know,” introducing students to challenging areas of future research. Updated end-of-chapter problems reflect new research discussed in the text, and these problems have been expanded to all chapters by adding questions on developmental biology, tissues and stem cells, pathogens, and the immune system.

Current protocols in molecular biology

Brock Biology of Microorganisms

Samenvatting:The book for introductory microbiology, Brock's Biology of Microorganismscontinues its long tradition of impeccable scholarship, outstanding art,and accuracy. It balances the most current coverage with the majorclassical concepts essential for understanding the science. A six-partpresentation covers principles of microbiology; evolutionary microbiologyand microbial diversity; metabolic diversity and microbial ecology;immunology, pathogenicity, and host responses; microbial diseases; andmicroorganisms as tools for industry and research. For researchers, groupleaders, senior scientists in pharmaceuticals, chemicals and biochemicalbiotechnology companies, and public health laboratories.

Molecular Cell Biology

Molecular cell biology , Molecular cell biology , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

Molecular Biology of the Cell

For nearly a quarter century Molecular Biology of the Cell has been the leading cell biology textbook. This tradition continues with the new Fifth Edition, which has been completely revised and updated to describe our current, rapidly advancing understanding of cell biology. To list but a few examples, a large amount of new material is presented on epigenetics; stem cells; RNAi; comparative genomics; the latest cancer therapies; apoptosis (now its own separate chapter); and cell cycle control and the mechanics of M phase (now integrated into one chapter). The hallmark features of Molecular Biology of the Cell have been retained, such as its consistent and comprehensive art program, clear concept headings, and succinct section summaries. Additionally, in response to extensive feedback from readers, the Fifth Edition now includes several new features. It is now more portable. Chapters 1-20 are printed and Chapters 21-25, covering multicellular systems, are provided as PDF files on the free Media DVD-ROM which accompanies the book.* And for the first time, Molecular Biology of the Cell now contains end-of-chapter questions. These problems, written by John Wilson and Tim Hunt, emphasize a quantitative approach and the art of reasoning from experiments, and they will help students review and extend their knowledge derived from reading the textbook. The Media DVD-ROM, which is packaged with every copy of the book, contains PowerPoint® presentations with all of the figures, tables and micrographs from the text (available as JPEGs too). Also included is the Media Player, which plays over 125 movies—animations, videos, and molecular models—all with voice-over narration. A new reader-friendly feature is the integration of media codes throughout the text that link directly to relevant videos and animations. The Media DVD-ROM holds the multicellular systems chapters (21-25) of the text as well. By skillfully extracting the fundamental concepts from this enormous and ever-growing field, the authors tell the story of cell biology, and thereby create a coherent framework through which readers may approach and enjoy this subject that is so central to all of biology. * There is also a reference edition of Molecular Biology of the Cell, Fifth Edition (ISBN 978-0-8153-4111-6) that contains Chapters 1-25 entirely in printed format.

Randomization, Bootstrap and Monte Carlo Methods in Biology

Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications. This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals.New to the Third EditionUpdated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statisticsReferences that reflect recent developments in methodology and computing techniquesAdditional references on new applications of computer-intensive methods in biologyProviding comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.

Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Mathematical Biology

Opportunities and obstacles for deep learning in biology and medicine

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.

Mathematical Biology

Cause and Effect in Biology

Foundations for engineering biology

Computer Science Curricula 2013: Curriculum Guidelines for Undergraduate Degree Programs in Computer Science

White S and Vafopoulos M Web Science: Expanding the Notion of Computer Science, SSRN Electronic Journal, 10.2139/ssrn.1919393

Computational Biology and Bioinformatics in Nigeria

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

An investigation into senior high school (shs3) physics students understanding of data processing of length and time of scientific measurement in the Volta region of Ghana

Serious doubt have been raised in the Physics Chief Examiner's report of the West African Examination Council of Ghana of both physics-1 (theory) and physics-2 (practical) as to whether science students really understand measurement of physical quantities. In view of this, the researcher use a mixed designed method to gather data from SHS3 physics students' on their understanding of data processing of length and time. A population of 422 SHS3 physics students were sampled and a three item questionnaire on distance and time administered in order to find out whether the problem enumerated by the Chief Examiners' of Physics concerning physics students exist and were either with the set paradigm or the point paradigm concept. Also twenty SHS3 physics were purposively selected and interviewed in order to validate students' written responses. The study revealed that students do not have an understanding of using repeat in data set, anomaly in data set and straight line graph of data by the set paradigm concept i.e. all the three items on data processing of students (i.e. UR, AN, and SLG) were in line with the point paradigm concept of measurement. Also students seemed to have difficulty in plotting straight line graph by the use of lines of best fit.

University physics in Africa