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Presenter: Bradley Green.  What is Bioinformatics?  Brief History of Bioinformatics  Development  Computer Science and Bioinformatics  Current Applications.

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Presentation on theme: "Presenter: Bradley Green.  What is Bioinformatics?  Brief History of Bioinformatics  Development  Computer Science and Bioinformatics  Current Applications."— Presentation transcript:

1 Presenter: Bradley Green

2  What is Bioinformatics?  Brief History of Bioinformatics  Development  Computer Science and Bioinformatics  Current Applications  What the future holds

3  Original Definition – “Study of information processes in biotic systems”  Retrieve, Organize, Analyze  New and ever changing field  Bioinformatics is a field supported by ◦ Computer Science ◦ Engineering ◦ Mathematics  Develop software Tools ◦ Generate biological data and knowledge

4  Alvin Kabat (1978) ◦ Led research in biological sequence analysis  Was strictly used as an organizational tool  Assisted in the development of nucleotide sequence data bases and software  Increase understanding of biological processes  Apply computational techniques

5  Post 1980’s ◦ The application of computer science to the analysis of biological data  Impact ◦ Genome Research ◦ DNA Sequencing  Bioinformatics as a Computer Scientist ◦ Creation and advancement of databases and algorithms ◦ Computational methods to solve practical problems ◦ 3D generation of various biological systems ◦ Develop software used to discover and analyze biological networks

6  Analyzing biological information involves the application of: ◦ Algorithms in AI ◦ Soft Computing ◦ Data mining ◦ Image system theory ◦ Information theory ◦ Statistics  Tools Used ◦ Java, XML, Perl, C, C++, Ruby, Python, R, SQL, CUDA, MATLAB, and spread sheet applications

7  Computer scientists responsible for mass advancements ◦ Developed technologies ◦ Diagnosis ◦ Applications and devices  Drastic changes in biomedicine ◦ Captured information stored in biotic systems ◦ Develop into applicable technology and data  Research Methods ◦ Able to research at cellular levels ◦ Predictive and diagnostic methods ◦ Complex biological systems ◦ Interactions in Biotics

8  Command-line tools and scripts to complex and advanced graphical programs ◦ Developed using common programming languages  Bioinformatics software ◦ BioConducter, BioRuby, BioPython, BioJava, EMBOSS, Taverna workbench ◦ Limited to machines installed with software  Some capabilities ◦ Analyzing biotic sequences ◦ Modeling cells ◦ Testing methods  Organizations: Open Bioinformatics Foundation and EBI ◦ Annual Bioinformatics Open Source Conference

9  Web services ◦ Not always open source ◦ Browser based applications ◦ Superior to local software in certain cases  Allows user to share mass quantities of data ◦ Promotes synthesis of research and applications ◦ Not limited to accessing data from one location  Ensures multiple parties are updated consistently  SOAP and REST ◦ Sequence Search Services, Multiple Sequence Alignment, Biological Sequence Analysis ◦ Bioinformatics workflow management systems

10  Research in progress: ◦ Amino-acid sequencing ◦ DNA sequencing ◦ Genome research  Diagnose and treat illness far in advance  Understand unknown concepts of the brain and high level functioning  Advancement of technology and capabilities ◦ Medical Research ◦ Clinical Research  Simulate virus and infection  Origin of the gene  Further the concept of the cell  Promote computer scientists

11  Bioinformatics." Wikipedia. Wikimedia Foundation, 25 Feb. 2013. Web. 25 Feb. 2013  Neuman, Joseph A., Ofer Isakov, and Noam Shomron. "Briefings in Bioinformatics." Analysis of Insertion–deletion from Deep-sequencing Data: Software Evaluation for Optimal Detection. Oxford Journals, n.d. Web. 25 Feb. 2013.  Cohen, Jacques. "Bioinformatics- An Introduction for Computer Scientists." ACM Computing Surveys 36.2 (2004): 123-56. Cse.spsu.edu. Web.


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