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Introduction to BioInformatics GCB/CIS535

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Presentation on theme: "Introduction to BioInformatics GCB/CIS535"— Presentation transcript:

1 Introduction to BioInformatics GCB/CIS535

2 Course Overview Sequence alignment Gene prediction Gene expression
Dynamic programming Blast and its variants statistical significance Motif and promoter prediction Gene prediction Homology and HMMs Gene expression Experiment design Interpretation: clustering Proteomics Use of mass spectrometry

3 Sequence Alignment Choices Motif finding nucleotide vs. amino acid
global vs. local repeat masking Motif finding Position weight matrices PAM, BLOSUM CONSENSUS EM and Gibbs sampling methods

4 Promoter Finding CpG islands Transcription Factor Binding sites
TATA, GC, and CAAT boxes Transfac and Jasper libraries FirstExon

5 Gene Finding Homology Hidden Markov Models (HMMs) Regression Future
Conservation between species Hidden Markov Models (HMMs) Acceptors & donors Coding & non-coding Frame shifts Regression Linear regression Artificial neural networks Future Conditional Random Fields (CRFs)

6 Gene Expression

7 Gene Expression Uses Technology Experimental design Analysis
Finding Differentially Expressed Genes Gene List Annotation Technology Spotted array (two color) and Affimetrics (one color) Experiment Execution (Process Control) Experimental design Replicates Matched experiments Controls / reference samples Analysis Probes to Genes Normalization Sample Quality Control Statistical Significance of Over Representation

8 Clustering Clustering methods Key decisions Dimension reduction
Hierarchical K-means Key decisions Standardize data? How many clusters? Dimension reduction PCA - Principal Components Analysis SOM - Self Organizing Maps Assessment Cluster purity

9 Methods for protein identification
Proteomics Methods for protein identification

10 Proteomics Uses Mass spectrometry Toxicology
Compare diseased vs. normal cells Alternative splicing Post-translational modifications Together with genomics Mass spectrometry Mass fingerprinting Sequence tags Cross correlation with simulated mass spectra E.g. Sequest and mascot Problem with introns Y-ions and b-ions Tandem mass spec

11 Future Directions Regulatory mechanisms Binding between
Transcription (“gene expression”) Translation (“protein production”) Acetylation (of lycine) Phosphorylation, Other protein, RNA and DNA modification Binding between DNA, RNA, Protein Comparison across species Systems biology Metabolic modeling Combining data

12 Gene Regulatory Network
Sea urchin development

13 Metabolic Networks

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