If you use any content written by Writing-Services.org, it should be referenced accordingly. It is a crossover of biology, computer science, statistics and mathematics which are not the usual disciplines that are studied together. This enables a detailed analysis of evolutionary, structural, and functional aspect of natural products production based on the comparison of molecular sequences, molecular modeling, and simulation. The choice of a topic should depend solely on your background knowledge and understanding of various bioinformatics issues. Bioinformatics can be also defined as an umbrella concept dealing with all the applications of information technology to the field of molecular biology. Two examples of applications that use the caBIG network to create a virtual bioinformatics platform are summarized in the following paragraphs. A recent study has found that the interest of researchers in these topics plateaued over after the early 2000s [1]. The chapter also attempts to provide some details on the various problems and solution in bioinformatics that current-day scientists face while concentrating on second-generation sequencing strategies. There are a number of good topics in computer science for project, thesis, and research for M.Tech and Ph.D. students. The main components of bioinformatics are (1) the development of software tools and algorithms and (2) the analysis and interpretation of biological data by using a variety of software tools and particular algorithms. Actually what constitutes bioinformatics is not entirely clear and arguably varies depending on who tries to define it. We believe that there has simply not been enough time for this to happen. As others have said, the list of interesting topics is unbounded. The efficiency of data mining algorithms. Every month something happens – the machines become more powerful, the new languages of programming are invented and the new possibilities are opened before computer … The languages used to tackle bioinformatics problems and related analysis are, for example, R, a statistical programming language, scripting languages such as Perl and Python, and compiled languages such as C, C++, and Java. Bioinformatics has also been referred to as ‘computational biology’. Among these, R is becoming one of the most widely used software tools for bioinformatics. This is due to the discovery of ‘silent’ or ‘cryptic’ secondary metabolite gene clusters that encode the production of additional, unidentified compounds. The first, the cancer Translational Research Informatics Platform, caTRIP is a framework developed by Duke University to query and mine clinical, pathology, gene expression, and proteomics data. These include the caArray data resource and the GenePattern analytic engine described in the preceding sections. Its goal is to enable the discovery of new biological insights and unifying principles that create a global perspective in biology. The Computing Research Association (CRA) is a leading computer science advocacy organization whose mission is to unite industry, academia, and government. We mentioned repeatedly that the field is just emerging. It is a discipline that combines the studies of living systems with computer science and maths. Bioinformatics started in Switzerland in the early 1980s, when very few people were yet aware of the importance that this new field would assume. This chapter discusses the current state of play of bioinformatics related to genomics and transcriptomics, briefs metagenomics that finds use in infectious disease research as well as the random sequencing of genomes from a variety of organisms. We expect such successes to be reported within the next decade. These successes cannot be attributed to a specific computational method. It is generally recognized, particularly in systems responsible for the synthesis of diverse antibiotics, that, for example, nonribosomal peptide synthesis occurs within a molecular complex composed of modules or subunits grouping peptide synthetase modules and associated enzymatic activities. Cloud computing, big data, Hadoop; Machine learning; Artificial intelligence; Functional genomics This question is hard to answer; also, we have not undertaken a comprehensive survey of successes that can already be reported. To our knowledge, there is no integrated computational approach that covers all of these aspects, to date. Yi-Ping Phoebe Chen, ... Paolo Carloni, in Comprehensive Natural Products II, 2010. Filter Results . It leverages the distributed nature of caBIG, permitting the use of data and services distributed nationwide. Infrastructure, applications, and data resources that adhere to a common set of standards constitute a services- oriented architecture (SOA). For this purpose, research papers are assigned to them in this field of computer science. Clear search. In order to manage various bioinformatics applications, different programs have been written by using various available computing languages. However, strictly speaking, computational biology deals mainly with modeling of biological systems. Copyright © 2020 Elsevier B.V. or its licensors or contributors. Training in data science skills can unlock the potential of biomedical Big Data. Anyway, we suppose there is not much you can do about the situation, and your research paper on bioinformatics should be finished anyway. Top 10 Hottest Research Topics in Computer Science. What this means is that your research paper on bioinformatics can also make some useful contribution, at least, if you are good at this discipline. We know of no case in which a protein target has been identified with substantial bioinformatics support and, for this protein, a drug developed and put on the market, successfully. Swiss bioinformaticians created software for the comparison of DNA sequences, developed programs for the analysis of experimental protein data, invented tools for modeling the three-dimensional structures of proteins, and built databases containing key information about protein sequences. Formulate the main point of your research paper on bioinformatics. The cancer community has created such a next-generation World Wide Web, the Cancer Biomedical Informatics Grid (caBIG). Installation and use of caGrid SOA “middleware” infrastructure (specialized software that connect data and applications) requires bioinformatics technical expertise. The most promising areas to move into with a computer science background at the moment is probably analysis of the massive amounts of DNA sequences produced by new sequencing technologies. In general, we are well aware that the quest for unraveling the molecular processes of a disease to an extent that affords the effective development and selection of drug therapies is a great challenge. Of these, Margaret Dayhoff’s contributions stood out the most and she is often credited as being the pioneer in bioinformatics for her varied contributions, including developing the first amino-acid substitution matrix for studying protein evolution. Interestingly, a key factor in the creation of the Internet was to facilitate scientists working in the United State's national laboratories to share data and computer infrastructure. Recent examination of massive sequencing (metagenomics) approaches to analyze the composition of bacterial communities of complex milieu including sea water,38 provide an abundant source of molecular sequence data for analysis. ScienceDirect ® is a registered trademark of Elsevier B.V. ScienceDirect ® is a registered trademark of Elsevier B.V. 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Paolo Carloni, in, The Molecular Basis of Cancer (Third Edition), http://gforge.nci.nih.gov/projects/cagrid-1-0, Computing Languages for Bioinformatics: R, Encyclopedia of Bioinformatics and Computational Biology, Encyclopedia of Applied Ethics (Second Edition), Omics, Bioinformatics, and Infectious Disease Research, Konrad H. Paszkiewicz, Mark van der Giezen, in, Genetics and Evolution of Infectious Disease, Next-Generation Sequencing, Bioinformatics, and Infectious Diseases, Genetics and Evolution of Infectious Diseases (Second Edition), Biochemical and Biophysical Research Communications. Within the next decade numerous successes to find some essential and long-lasting topics writing! The ongoing success of this approach community has created such a next-generation world Web. Suitable for drug design target, computational biology, but I picked a different path has already numerous! 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