'Alignment algorithms' diaporamas de présentation

EECS 800 Research Seminar Mining Biological Data

EECS 800 Research Seminar Mining Biological Data. Instructor: Luke Huan Fall, 2006. Mining Sequence Patterns in Biological Data. A brief introduction to biology and b ioinformatics Alignment of biological sequences Hidden Markov model for biological sequence analysis Summary. DNA Structure.

962 views • 77 slides

EECS 800 Research Seminar Mining Biological Data

EECS 800 Research Seminar Mining Biological Data. Instructor: Luke Huan Fall, 2006. Mining Sequence Patterns in Biological Data. A brief introduction to biology and b ioinformatics Alignment of biological sequences Hidden Markov model for biological sequence analysis Summary. DNA Structure.

778 views • 77 slides

Multiple Sequence Alignment

Multiple Sequence Alignment. Terminology. Motif: the biological object one attempts to model - a functional or structural domain, active site, phosphorylation site etc. Pattern: a qualitative motif description based on a regular expression-like syntax

2.51k views • 59 slides

Alignment methods

Alignment methods. Introduction to global and local sequence alignment methods Global : Needleman-Wunch Local : Smith-Waterman Database Search BLAST FASTA. Why search sequence databases?. I have just sequenced something. What is known about the thing I sequenced?

606 views • 32 slides

Proteomics In R

Proteomics In R . Marc Coram University of Chicago FHCRC Summer Visit (2004). Goals for this Talk. Demonstrate R-based proteomics tools Analyze 4-5 mix data Show how to use the tools Explain statistical reasoning Show pros and cons Describe future directions. Why R?.

538 views • 31 slides

Bioinformatics Unit 1: Data Bases and Alignments

469 views • 25 slides

Clustal W and Clustal X version 2.0

Clustal W and Clustal X version 2.0. ??? , ??? , ??? The 9 th Protein Folding Winter School. The Paper. Abstract. The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++

472 views • 22 slides

Schedule

Bioinformatics and Computational Biology: History and Biological Background (JH) 10.10 The Parsimony criterion GKN 13.10 Stochastic Models of Sequence Evolution GKN 17.10 The Likelihood criterion GKN 20.10 Tut: 9-10 11=12 (Friday) Trees in phylogenetics and population genetics GKN 24.10

411 views • 20 slides