Bioinformatics at virginia tech
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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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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

Overview

  • Some relevant biology

  • New language of biology

  • Bioinformatics research at Virginia Tech

  • Getting into bioinformatics at Virginia Tech


Some molecular biology

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).


Transcription and translation

Transcription and Translation

Transcription

Translation

DNA

mRNA

Protein


Dna strand

DNA Strand

A= adenine complements T= thymine

C = cytosine complements G=guanine


Rna strand

RNA Strand

U=uracil replaces T= thymine


Amino acids

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.


Translation to a protein

Translation to a Protein

Unlike DNA, proteins have three-dimensional structure

Protein folds to a three-dimensional shape that

minimizes energy


The language of the new biology

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


Genomics

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.


Functional genomics

Functional Genomics

  • The biological role of individual genes;

  • Mechanisms underlying the regulation of their expression;

  • Regulatory interactions among them.


Gene expression

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.


Gene expression varies

Gene Expression Varies


Networks and pathways glycolysis citric acid cycle and related metabolic processes

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


Bioinformatics at virginia tech1

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


Bioinformatics at virginia tech

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


Nutripotato

NutriPotato

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


Bioinformatics at virginia tech

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.


Other projects

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


Getting into bioinformatics at vt

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


Cs 5984 algorithms in bioinformatics

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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