What is the subject of science "bioinformatics"?

The paper is concerned with some problems of terminology, in particular the term "bioinformatics". In the last few years, the term "bioinformatics" has been intensively used among molecular biologists to indicate a subject that is only a constituent of genomics and is considered to involve a computer-assisted analysis of all data on nucleotide sequences of DNA. However, a wide circle of scientists, including biologists, physicists, mathematicians, and specialists in the field of cybernetics, informatics, and other disciplines have accepted and accept, as a rule, the "bioinformatics" as a synonym of science cybernetics and as a successor of this science. In this case, the subject of science "bioinformatics" should embrace not only genomics but practically all sections of the biological science. It should involve a study of information processes (storage, transfer, and processing of information, etc.) participating in the regulation and control at all levels of living systems, from macromolecules to the brain of higher animals and human.     

Fluorescent color factor calculation using dBASE-II

A software system utilizing dBASE-II operating on a dual-driveApple II+ computer is described. Color factors and retentiontimes for 15 amino acids and -(-glutamyl)lysine dipeptide arecalculated following high performance liquid chromatography.The software package produces a listing of acceptable limitsfor these parameters calculated as plus and minus 2 standarddeviations of the mean. The code is distributed in source form. ; accepted on March 10, 1986     

Gbrowse Moby: a Web-based browser for BioMoby Services

Background  

The BioMoby project aims to identify and deploy standards and conventions that aid in the discovery, execution, and pipelining of distributed bioinformatics Web Services. As of August, 2006, approximately 680 bioinformatics resources were available through the BioMoby interoperability platform. There are a variety of clients that can interact with BioMoby-style services. Here we describe a Web-based browser-style client – Gbrowse Moby – that allows users to discover and "surf" from one bioinformatics service to the next using a semantically-aided browsing interface.     

Estimation of restriction maps with known site order using a generalized linear model

The publishers wish to apologise for typesetting errors thatappeared in two equations, on pages 541 and 547, of the abovepaper. The correct versions are presented below.      

生物信息学跨学科研究

目的:研究生物信息学起源、发展趋势,与其他学科相互交叉渗透关系的发展及强度。方法:利用美国《科学引文索引》(SCI)数据库web of science,运用文献计量学方法对8种权威生物信息学期刊2001年至2010年于2011年1月15日之前上传至webof science的全部文献进行统计及分析。通过研究生物信息学相关论文的主题分类,被引情况及施引文献的分类,寻找其跨学科的趋势及相关研究领域的进展情况、主要内容。结果:生物信息学的相关文献数在2001-2010间逐年增加,在2009-2010年达到高峰。跨学科领域广泛,并以生物化学、分子生物学、计算生物学、微生物学、数学、统计学等学科为主要交叉学科。各交叉学科与生物信息学之间跨学科研究的文献数也呈逐年递增趋势。结论:生物信息学的跨学科范围广泛,发展迅速。     

Maximum likelihood of phylogenetic networks

Bioinformatics (2006) 22(21), 2604–2611 The authors would like to apologize for errors of graph misplacementin Figures 4–6, and an     

A new tool for prioritization of sequence variants from whole exome sequencing data

Background

Whole exome sequencing (WES) has provided a means for researchers to gain access to a highly enriched subset of the human genome in which to search for variants that are likely to be pathogenic and possibly provide important insights into disease mechanisms. In developing countries, bioinformatics capacity and expertise is severely limited and wet bench scientists are required to take on the challenging task of understanding and implementing the barrage of bioinformatics tools that are available to them.

Results

We designed a novel method for the filtration of WES data called TAPER? (Tool for Automated selection and Prioritization for Efficient Retrieval of sequence variants).

Conclusions

TAPER? implements a set of logical steps by which to prioritize candidate variants that could be associated with disease and this is aimed for implementation in biomedical laboratories with limited bioinformatics capacity. TAPER? is free, can be setup on a Windows operating system (from Windows 7 and above) and does not require any programming knowledge. In summary, we have developed a freely available tool that simplifies variant prioritization from WES data in order to facilitate discovery of disease-causing genes.

     

Scanning protein sequence databanks using a distributed processing workstation network

The programme pscan has been developed to distribute proteindatabank scans over a network of computers that share a commonfilesystem. pscan may be used in conjunction with most conventionalsequence comparison programmes with few modifications. In testruns using the Smith — Waterman dynamic programming algorithm,the time required to scan a 6858 sequence databank using a querysequence 740 residues long was reduced from 50 min for a singleprocessor, to 11 minutes for five processors. Accordingly, pscanprovides a low-cost, portable alternative to dedicated parallelprocessing computers. Received on August 27, 1990; accepted on September 25, 1990     

ArrayOU: A Web Application for Microarray Data Analysis and Visualization

A web-based microarray data analysis tool, ArrayOU (freely available at www.bioinformatics.plantbio.ohiou.edu.), has been developed at the Ohio University Genomics Facility for the research and education community to analyze Agilent microarray data. Agilent''s microarray pipeline has gained in popularity as a result of its ease of use and low cost of customized arrays. The current version of the ArrayOU pipeline allows users to visualize, analyze, and annotate microarray data from commercially available and customized Agilent expression arrays and is extendable for further implementations.     

Analyzing the field of bioinformatics with the multi-faceted topic modeling technique

Background

Bioinformatics is an interdisciplinary field at the intersection of molecular biology and computing technology. To characterize the field as convergent domain, researchers have used bibliometrics, augmented with text-mining techniques for content analysis. In previous studies, Latent Dirichlet Allocation (LDA) was the most representative topic modeling technique for identifying topic structure of subject areas. However, as opposed to revealing the topic structure in relation to metadata such as authors, publication date, and journals, LDA only displays the simple topic structure.

Methods

In this paper, we adopt the Tang et al.’s Author-Conference-Topic (ACT) model to study the field of bioinformatics from the perspective of keyphrases, authors, and journals. The ACT model is capable of incorporating the paper, author, and conference into the topic distribution simultaneously. To obtain more meaningful results, we use journals and keyphrases instead of conferences and bag-of-words.. For analysis, we use PubMed to collected forty-six bioinformatics journals from the MEDLINE database. We conducted time series topic analysis over four periods from 1996 to 2015 to further examine the interdisciplinary nature of bioinformatics.

Results

We analyze the ACT Model results in each period. Additionally, for further integrated analysis, we conduct a time series analysis among the top-ranked keyphrases, journals, and authors according to their frequency. We also examine the patterns in the top journals by simultaneously identifying the topical probability in each period, as well as the top authors and keyphrases. The results indicate that in recent years diversified topics have become more prevalent and convergent topics have become more clearly represented.

Conclusion

The results of our analysis implies that overtime the field of bioinformatics becomes more interdisciplinary where there is a steady increase in peripheral fields such as conceptual, mathematical, and system biology. These results are confirmed by integrated analysis of topic distribution as well as top ranked keyphrases, authors, and journals.

     

PyPedia: using the wiki paradigm as crowd sourcing environment for bioinformatics protocols

Background

Today researchers can choose from many bioinformatics protocols for all types of life sciences research, computational environments and coding languages. Although the majority of these are open source, few of them possess all virtues to maximize reuse and promote reproducible science. Wikipedia has proven a great tool to disseminate information and enhance collaboration between users with varying expertise and background to author qualitative content via crowdsourcing. However, it remains an open question whether the wiki paradigm can be applied to bioinformatics protocols.

Results

We piloted PyPedia, a wiki where each article is both implementation and documentation of a bioinformatics computational protocol in the python language. Hyperlinks within the wiki can be used to compose complex workflows and induce reuse. A RESTful API enables code execution outside the wiki. Initial content of PyPedia contains articles for population statistics, bioinformatics format conversions and genotype imputation. Use of the easy to learn wiki syntax effectively lowers the barriers to bring expert programmers and less computer savvy researchers on the same page.

Conclusions

PyPedia demonstrates how wiki can provide a collaborative development, sharing and even execution environment for biologists and bioinformaticians that complement existing resources, useful for local and multi-center research teams.

Availability

PyPedia is available online at: http://www.pypedia.com. The source code and installation instructions are available at: https://github.com/kantale/PyPedia_server. The PyPedia python library is available at: https://github.com/kantale/pypedia. PyPedia is open-source, available under the BSD 2-Clause License.

     

An approach to systematic detection of protein structural motifs

A procedure to detect similar local structures of proteins fromC coordinates is presented. First, the conformations of seven-residuepeptide segments are approximated by a limited number of representatives,each of which is assigned a symbol. Thus, the overall conformationof a protein is represented by a symbol string. The comparisonof these symbol strings using a sequence alignment techniquethen gives pairs of similar local structures. These pairs areconsidered candidates of structural motifs. The applicationof the procedure to the analysis of 93 proteins gave 858 pairsof similar local structures, which included several well-knownstructural motifs such as the nucleotide-binding ßß-unitand the calcium-binding EF hand. The characterization of aminoacid patterns of similar local structures given by the procedureshould be useful for the development of protein structure predictionbased on the acquisition of empirical rules from a large-scaledatabase.     

Comprehensive decision tree models in bioinformatics

Purpose

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible.

Methods

This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree.

Results

The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree.

Conclusions

The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics.     

BreakTrans: uncovering the genomic architecture of gene fusions

Producing gene fusions through genomic structural rearrangements is a major mechanism for tumor evolution. Therefore, accurately detecting gene fusions and the originating rearrangements is of great importance for personalized cancer diagnosis and targeted therapy. We present a tool, BreakTrans, that systematically maps predicted gene fusions to structural rearrangements. Thus, BreakTrans not only validates both types of predictions, but also provides mechanistic interpretations. BreakTrans effectively validates known fusions and discovers novel events in a breast cancer cell line. Applying BreakTrans to 43 breast cancer samples in The Cancer Genome Atlas identifies 90 genomically validated gene fusions. BreakTrans is available at http://bioinformatics.mdanderson.org/main/BreakTrans     

生物信息学本科专业建设现状

随着后基因组时代的到来,生物信息学逐渐进入了黄金发展期。生物信息学教育体系的建立和完善是永葆生物信息学活力的关键。国际和国内的生物信息学本科专业建设情况的分析显示全球生物信息学本科教育均处于起始阶段。深刻剖析了内蒙古自治区生物信息发展的瓶颈问题以及内蒙古科技大学开设生物信息学本科专业的优势和必要性。未来,随着测序技术、计算机技术等的进步,生物信息学将继续蓬勃发展;生物信息学人才的需求将不断扩大。为适应人才市场的需求,预计会有越来越多的高等院校将加入到中国的生物信息学本科教育事业。