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Bioinformatics at Virginia Tech

Bioinformatics at Virginia Tech. David Bevan (BCHM) Lenwood S. Heath (CS) Ruth Grene (PPWS) Layne Watson (CS) Chris North (CS) Naren Ramakrishnan (CS). August 19, 2002. Overview. Some relevant biology New language of biology Bioinformatics research at Virginia Tech

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Bioinformatics at Virginia Tech

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  1. Bioinformatics at Virginia Tech David Bevan (BCHM) Lenwood S. Heath (CS) Ruth Grene (PPWS) Layne Watson (CS) Chris North (CS) Naren Ramakrishnan (CS) August 19, 2002

  2. Overview • Some relevant biology • New language of biology • Bioinformatics research at Virginia Tech • Getting into bioinformatics at Virginia Tech

  3. Some Molecular Biology • The encoded instruction set for an organism is kept in DNA molecules. • Each DNA molecule contains 100s or 1000s of genes. • A gene is transcribed to an mRNA molecule. • An mRNA molecule is translated to a protein (molecule).

  4. Transcription and Translation Transcription Translation DNA mRNA Protein

  5. DNA Strand A= adenine complements T= thymine C = cytosine complements G=guanine

  6. RNA Strand U=uracil replaces T= thymine

  7. Amino Acids • Protein is a large molecule that is a chain of amino acids (100 to 5000). • There are 20 common amino acids (Alanine, Cysteine, …, Tyrosine) • Three bases --- a codon --- suffice to encode an amino acid, according to the genetic code. • There are also START and STOP codons.

  8. Translation to a Protein Unlike DNA, proteins have three-dimensional structure Protein folds to a three-dimensional shape that minimizes energy

  9. The Language of the New Biology A new language has been created. Words in the language that are useful today. Genomics Functional Genomics Proteomics Global Gene Expression Patterns Networks and Pathways

  10. Genomics • Genome sequencing projects: Drosophila, yeast, human, mouse, Arabidopsis, microbes, … • Identification of genetic sequences: • Sequences that code for proteins; • Sequences that act as regulatory elements.

  11. Functional Genomics • The biological role of individual genes; • Mechanisms underlying the regulation of their expression; • Regulatory interactions among them.

  12. Gene Expression • When a gene is transcribed (copied to mRNA), it is said to be expressed. • The mRNA in a cell can be isolated and examined using microarrays. Its contents give a snapshot of the genes currently being expressed. • Correlating gene expression with conditions gives hints into the dynamic functioning of the cell.

  13. Gene Expression Varies

  14. Networks and Pathways:Glycolysis, Citric Acid Cycle, and Related Metabolic Processes

  15. Bioinformatics at Virginia Tech Computer Science interacts with the life sciences. • Joint research with: plant biologists, microbial biologists, biochemists, cell-cycle biologists, animal scientists, crop scientists, statisticians. • Projects: Expresso; NutriPotato; MURI; Multimodal Networks; Barista; Fusion;Arabidopsis Genome; Cell-Cycle Modeling • Graduate option in bioinformatics

  16. Expresso:A Problem Solving Environment (PSE) for Microarray Experiment Design and Analysis • Integration of design, experimentation, and analysis • Data mining; inductive logic programming (ILP) • Closing the loop • Drought stress experiments with pine trees and Arabidopsis

  17. NutriPotato Microarray technology used to investigate genes responsible for stress resistance and for the production of nutrients in Andean potato varieties.

  18. MURI • Some microorganisms have the ability to survive drying out or intense radiation. • Using microarrays and proteomics, we are attempting to correlate computationally the genes in the genomes with the special traits of the microorganisms.

  19. Other Projects • Multimodal Networks: represent, manipulate, and identify biological networks • Barista: serves software for Expresso, et al. • Fusion: visualization via redescription • Arabidopsis Genome Project: mine the Arabidopsis genome for regulatory sequences

  20. Getting Into Bioinformatics at VT • Learn some biology: genetics, molecular biology, cell biology, biochemistry (2 courses) • Study computational biology: CS 5984 • Get involved with bioinformatics research in interdisciplinary teams • Work with biologists to solve their problems

  21. CS 5984: Algorithms in Bioinformatics • Genetic and physical mapping • Sequence comparison • Sequence alignment • Sequence alignment • Probabilistic models for molecular biology • Fragment assembly • Genome rearrangements • Evolutionary tree (re-)construction

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