Lyle Ungar, University of Pennsylvania

Introduction to Introduction to BioInformaticsBioInformatics

GCB/CIS535GCB/CIS535

2Lyle H Ungar, University of Pennsylvania

Course OverviewCourse OverviewCourse OverviewCourse Overview

Sequence alignment 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

3Lyle H Ungar, University of Pennsylvania

Sequence AlignmentSequence AlignmentSequence AlignmentSequence Alignment

Choices nucleotide vs. amino acid global vs. local repeat masking

Motif finding Position weight matrices

PAM, BLOSUM CONSENSUS EM and Gibbs sampling methods

4Lyle H Ungar, University of Pennsylvania

Promoter FindingPromoter FindingPromoter FindingPromoter Finding

CpG islands Transcription Factor Binding sites

TATA, GC, and CAAT boxes Transfac and Jasper libraries

FirstExon

5Lyle H Ungar, University of Pennsylvania

Gene FindingGene FindingGene FindingGene Finding

Homology 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)

6Lyle H Ungar, University of Pennsylvania

Gene ExpressionGene ExpressionGene ExpressionGene Expression

7Lyle H Ungar, University of Pennsylvania

Gene ExpressionGene ExpressionGene ExpressionGene Expression Uses

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

8Lyle H Ungar, University of Pennsylvania

ClusteringClusteringClusteringClustering

Clustering methods Hierarchical K-means

Key decisions Standardize data? How many clusters?

Dimension reduction PCA - Principal Components Analysis SOM - Self Organizing Maps

Assessment Cluster purity

9Lyle H Ungar, University of Pennsylvania

Methods for protein

identification

ProteomicsProteomicsProteomicsProteomics

10Lyle H Ungar, University of Pennsylvania

ProteomicsProteomicsProteomicsProteomics

Uses 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

11Lyle H Ungar, University of Pennsylvania

Future DirectionsFuture DirectionsFuture DirectionsFuture Directions

Regulatory mechanisms 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

12Lyle H Ungar, University of Pennsylvania

Gene Regulatory NetworkGene Regulatory NetworkGene Regulatory NetworkGene Regulatory Network

Sea urchin development

13Lyle H Ungar, University of Pennsylvania

Metabolic NetworksMetabolic NetworksMetabolic NetworksMetabolic Networks