The origins of bioinformatics

Bioinformatics is often described as being in its infancy, but computers emerged as important tools in molecular biology during the early 1960s. A decade before DNA sequencing became feasible, computational biologists focused on the rapidly accumulating data from protein biochemistry. Without the benefits of super computers or computer networks, these scientists laid important conceptual and technical foundations for bioinformatics today.     

Omiga™: A PC-based sequence analysis tool

Computer-based sequence analysis, notation, and manipulation are a necessity for all molecular biologists working with any but the most simple DNA sequences. As sequence data become increasingly available, tools that can be used to manipulate and annotate individual sequences and sequence elements will become an even more vital implement in the molecular biologist's arsenal. The Omiga DNA and Protein Sequence Analysis Software tool, version 2.0 provides an effective and comprehensive tool for the analysis of both nucleic acid and protein sequences that runs on a standard PC available in every molecular biology laboratory. Omiga allows the import of sequences in several common formats. Upon importing sequences and assigning them to various projects, Omiga allows the user to produce, analyze, and edit sequence alignments. Sequences may also be queried for the presence of restriction sites, sequence motifs, and other sequence features, all of which can be added into the notations accompanying each sequence. This newest version of Omiga also allows for sequencing and polymerase chain reaction (PCR) primer prediction, a functionality missing in earlier versions. Finally, Omiga allows rapid searches for putative coding regions, and Basic Local Alignment Search Tool (BLAST) queries against public databases at the National Center for Biotechnology Information (NCBI).     

Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.     

Investigating the feeding behaviour of brine shrimps

Genomics and proteomics projects have produced a huge amount of raw biological data including DNA and protein sequences. Although these data have been stored in data banks, their evaluation is strictly dependent on bioinformatics tools. These tools have been developed by multidisciplinary experts for fast and robust analysis of biological data. However, there is a gap in the development of educational materials in the bioinformatics area for undergraduate students in bioscience departments. A sample in silico laboratory manual on the prediction of N-glycosylation sites in phosphoethanolamine transferases is presented in this study. The method proposed in this study is simple to apply in laboratory courses and is dependent on the use of internet-based bioinformatics tools such as ProtParam, ClustalW2 and NetNGlyc. In conclusion, this application can stimulate the interest of undergraduate students in bioscience departments and may also contribute to the development of bioinformatics.     

"Plasmo2D": an ancillary proteomic tool to aid identification of proteins from Plasmodium falciparum

Bioinformatics tools to aid gene and protein sequence analysis have become an integral part of biology in the post-genomic era. Release of the Plasmodium falciparum genome sequence has allowed biologists to define the gene and the predicted protein content as well as their sequences in the parasite. Using pI and molecular weight as characteristics unique to each protein, we have developed a bioinformatics tool to aid identification of proteins from Plasmodium falciparum. The tool makes use of a Virtual 2-DE generated by plotting all of the proteins from the Plasmodium database on a pI versus molecular weight scale. Proteins are identified by comparing the position of migration of desired protein spots from an experimental 2-DE and that on a virtual 2-DE. The procedure has been automated in the form of user-friendly software called "Plasmo2D". The tool can be downloaded from http://144.16.89.25/Plasmo2D.zip.     

SS-Wrapper: a package of wrapper applications for similarity searches on Linux clusters

Background  

Large-scale sequence comparison is a powerful tool for biological inference in modern molecular biology. Comparing new sequences to those in annotated databases is a useful source of functional and structural information about these sequences. Using software such as the basic local alignment search tool (BLAST) or HMMPFAM to identify statistically significant matches between newly sequenced segments of genetic material and those in databases is an important task for most molecular biologists. Searching algorithms are intrinsically slow and data-intensive, especially in light of the rapid growth of biological sequence databases due to the emergence of high throughput DNA sequencing techniques. Thus, traditional bioinformatics tools are impractical on PCs and even on dedicated UNIX servers. To take advantage of larger databases and more reliable methods, high performance computation becomes necessary.     

Databases, models, and algorithms for functional genomics

A variety of patterns have been observed on the DNA and protein sequences that serve as control points for gene expression and cellular functions. Owing to the vital role of such patterns discovered on biological sequences, they are generally cataloged and maintained within internationally shared databases. Furthermore,the variability in a family of observed patterns is often represented using computational models in order to facilitate their search within an uncharacterized biological sequence. As the biological data is comprised of a mosaic of sequence-levels motifs, it is significant to unravel the synergies of macromolecular coordination utilized in cell-specific differential synthesis of proteins. This article provides an overview of the various pattern representation methodologies and the surveys the pattern databases available for use to the molecular biologists. Our aim is to describe the principles behind the computational modeling and analysis techniques utilized in bioinformatics research, with the objective of providing insight necessary to better understand and effectively utilize the available databases and analysis tools. We also provide a detailed review of DNA sequence level patterns responsible for structural conformations within the Scaffold or Matrix Attachment Regions (S/MARs).     

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.     

羊流产嗜衣原体ompA基因克隆及生物信息学分析

分析羊流产嗜衣原体ompA基因结构并预测其编码蛋白的结构和功能。采用DNA Star、DNA MAN、vector NTI suite11.5序列分析软件和在线网站ExPASy分析该基因的结构和预测其编码蛋白的理化性质、亚细胞定位、一级结构修饰位点、二级结构特征及三维空间构象、潜在抗原表位等。结果显示,该基因全长1 170 bp,可编码389个氨基酸,编码蛋白理化性质较稳定,无各种亚细胞定位序列,含有多个能被其他酶修饰的位点,该蛋白以无规则卷曲为主,大部分氨基酸残基包埋在分子内部,含5个跨膜区,3个亲水性较强的抗原表位。ompA基因生物信息学分析结果为ompA蛋白功能的深入研究和新型多价疫苗的开发提供了基础数据。     

基于WWW与UNIX的核酸序列分析实用软件的开发

讨论了计算机序列分析的工作,介绍了基于WWW和UNIX的核酸序列分析实用软件,其特点是快速,易用,提高了工作效率。     

Purification and characterization of the R64 shufflon-specific recombinase

The shufflon, a multiple DNA inversion system in plasmid R64, consists of four invertible DNA segments which are separated and flanked by seven 19-bp repeat sequences. The product of a site-specific recombinase gene, rci, promotes site-specific recombination between any two of the inverted 19-bp repeat sequences of the shufflon. To analyze the molecular mechanism of this recombination reaction, Rci protein was overproduced and purified. The purified Rci protein promoted the in vitro recombination reaction between the inverted 19-bp repeats of supercoiled DNA of a plasmid carrying segment A of the R64 shufflon. The recombination reaction was enhanced by the bacterial host factor HU. Gel electrophoretic analysis indicated that the Rci protein specifically binds to the DNA segments carrying the 19-bp sequences. The binding affinity of the Rci protein to the four shufflon segments as well as four synthetic 19-bp sequences differed greatly: among the four 19-bp repeat sequences, the repeat-a and -d sequences displayed higher affinity to Rci protein. These results suggest that the differences in the affinity of Rci protein for the 19-bp repeat sequences determine the inversion frequencies of the four segments.     

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.     

木质素合成酶C3H基因的生物信息学分析

应用生物信息学的方法对GenBank中拟南芥、火炬松、胡麻、紫花罗兰等植物香豆酸-3-羟基化酶（c3h）基因以及本实验室克隆的欧美杨107的c3h基因（AM920690）核苷酸序列以及翻译的氨基酸序列的组成成分、导肽、跨膜结构域、疏水性／亲水性、蛋白质二级结构及功能域等进行了初步分析预测。分析表明欧美杨107的C3H氨基酸序列不存在导肽,无跨膜结构域,肽链表现为亲水性;二级结构域与P450高度匹配,其高级结构中含有由含铁血红素和半胱氨酸组成的活性中心,并构建了c3h进化树,对其分子进化进行了探讨。     

ProteoMix: an integrated and flexible system for interactively analyzing large numbers of protein sequences

ProteoMix is a suite of JAVA programs for identifying, annotating and predicting regions of interest in large sets of amino acid sequences, according to systematic and consistent criteria. It is based on two concepts (1) the integration of results from different sequence analysis tools increases the prediction reliability; and (2) the integration protocol is critical and needs to be easily adaptable in a case-by-case manner. ProteoMix was designed to analyze simultaneously multiple protein sequences using several bioinformatics tools, merge the results of the analyses using logical functions and display them on an integrated viewer. In addition, new sequences can be added seamlessly to an analysis performed on an initial set of sequences. ProteoMix has a modular design, and bioinformatics tools are run on remote servers accessed using the Internet Simple Object Access Protocol (SOAP), ensuring the swift implementation of additional tools. ProteoMix has a user-friendly interactive graphical user interface environment and runs on PCs with Microsoft OS. AVAILABILITY: ProteoMix is freely available for academic users at http://bio.gsc.riken.jp/ProteoMix/     

BMT: Bioinformatics mini toolbox for comprehensive DNA and protein analysis

BackgroundBioinformatics tools are of great significance and are used in different spheres of life sciences. There are wide variety of tools available to perform primary analysis of DNA and protein but most of them are available on different platforms and many remain undetected. Accessing these tools separately to perform individual task is uneconomical and inefficient.ObjectiveOur aim is to bring different bioinformatics models on a single platform to ameliorate scientific research. Hence, our objective is to make a tool for comprehensive DNA and protein analysis.MethodsTo develop a reliable, straight-forward and standalone desktop application we used state of the art python packages and libraries. Bioinformatics Mini Toolbox (BMT) is combination of seven tools including FastqTrimmer, Gene Prediction, DNA Analysis, Translation, Protein analysis and Pairwise and Multiple alignment.ResultsFastqTrimmer assists in quality assurance of NGS data. Gene prediction predicts the genes by homology from novel genome on the basis of reference sequence. Protein analysis and DNA analysis calculates physiochemical properties of nucleotide and protein sequences, respectively. Translation translates the DNA sequence into six open reading frames. Pairwise alignment performs pairwise global and local alignment of DNA and protein sequences on the basis or multiple matrices. Multiple alignment aligns multiple sequences and generates a phylogenetic tree.ConclusionWe developed a tool for comprehensive DNA and protein analysis. The link to download BMT is https://github.com/nasiriqbal012/BMT_SETUP.git     

Finding regulatory sequences

DNA regulatory sequences control gene expression by forming DNA-protein complex with specific DNA binding protein. A major task of studies of gene regulation is to identify DNA regulatory sequences in genome-wide. Especially with the rapid pace of genome project, the function of DNA regulatory sequences becomes one of the focuses in functional genome era. Several approaches for screening and characterizing DNA regulatory sequences emerged one by one, from initial low-throughput methods to high-throughput strategies. Even though at present bioinformatics tools facilitate the process of screening regulatory fragments, the most reliable results will come from experimental test. This article highlights some experimental methods for the identification of regulatory sequences. A brief review of the history and procedures for selection methods are provided. Tendency as well as limitation and extension of these methods are also presented.