'Biological sequence analysis' presentation slideshows

RNA folding & ncRNA discovery

I519 Introduction to Bioinformatics, Fall, 2012. RNA folding & ncRNA discovery. Adapted from Haixu Tang. Contents. Non-coding RNAs and their functions RNA structures RNA folding Nussinov algorithm Energy minimization methods microRNA target identification. RNAs have diverse functions.

1.18k views • 97 slides

Biological Sequence Analysis

Biological Sequence Analysis. Lecture 26, Statistics 246 April 27, 2004. Synopsis. Some biological background A progression of models Acknowledgements References. The objects of our study. DNA, RNA and proteins: macromolecules which are unbranched polymers built up from smaller units.

1.13k views • 66 slides

Welcome to CS262: Computational Genomics

Welcome to CS262: Computational Genomics. Instructor : Serafim Batzoglou TAs: Eugene Davydov Christina Pop email : cs262.win09@gmail.com Monday & Wednesday 11:50-1:05 James H Clark Center S361 http://cs262.stanford.edu. Goals of this course.

628 views • 52 slides

Biological Sequence Analysis

1: Introduction. Biological Sequence Analysis. Spring 2008. 1: Introduction. Administration. Teachers: Nimrod Rubinstein rubi@post.tau.ac.il Dudu Burstein davidbur@post.tau.ac.il Tel: 03-640-9245 Reception hours: by appointment. Course website:.

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PHYLOGENETIC TREES

PHYLOGENETIC TREES. Introduction to Computational Biology CIS 786 With Dr. Barry Cohen Tuesday, May 7, 2001 Paul Wood Yanchun Song Chaowei Sun. Introduction. Paul Wood. Chaowei Sun. Yanchun Song. What is a Phylogenetic Tree?.

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CS 598SS Probabilistic Methods in Biological Sequence Analysis

CS 598SS Probabilistic Methods in Biological Sequence Analysis. Saurabh Sinha. What is the course about?. Bioinformatics / Computational Biology Tools for analyzing genomes Probabilistic methods. What is the course format?. Research course Lectures by instructor

507 views • 41 slides

CS 598SS Probabilistic Methods in Biological Sequence Analysis

CS 598SS Probabilistic Methods in Biological Sequence Analysis. Saurabh Sinha. What is the course about?. Bioinformatics / Computational Biology Tools for analyzing genomes Probabilistic methods. What is the course format?. Research course Lectures by instructor

546 views • 41 slides

Protein structure

545 views • 37 slides

Sushmita Roy sroy@ biostat.wisc biostat.wisc/bmi576/

Introduction to Bioinformatics Biostatistics & Medical Informatics 576 Computer Sciences 576 Fall 2013. Sushmita Roy sroy@ biostat.wisc.edu www.biostat.wisc.edu/bmi576/. Sep 3 rd 2013. Goals for today. Administrivia Course Topics Short survey of interests/background.

558 views • 32 slides

Transcriptome analysis of the TnrA regulon in Bacillus subtilis

Transcriptome analysis of the TnrA regulon in Bacillus subtilis. Hanne Jarmer Center for Biological Sequence analysis Technical University of Denmark. Bacillus subtilis.

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The Pfam and MEROPS databases

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Transcriptome analysis of the TnrA regulon in Bacillus subtilis

Transcriptome analysis of the TnrA regulon in Bacillus subtilis. Hanne Jarmer Center for Biological Sequence analysis Technical University of Denmark. Bacillus subtilis.

488 views • 27 slides

Profile Hidden Markov Models

Profile Hidden Markov Models . Bioinformatics Fall-2004 Dr Webb Miller and Dr Claude Depamphilis Dhiraj Joshi Department of Computer Science and Engineering The Pennsylvania State University. Outline. Introduction to HMMs Profile HMMs

550 views • 23 slides

Profile Hidden Markov Models

Profile Hidden Markov Models . Bioinformatics Fall-2004 Dr Webb Miller and Dr Claude Depamphilis Dhiraj Joshi Department of Computer Science and Engineering The Pennsylvania State University. Outline. Introduction to HMMs Profile HMMs

395 views • 23 slides

Algorithms for Biological Sequence Analysis

Algorithms for Biological Sequence Analysis. Kun-Mao Chao ( ??? ) Department of Computer Science and Information Engineering National Taiwan University, Taiwan Date: September 19, 2006 E-mail: kmchao@csie.ntu.edu.tw WWW: http://www.csie.ntu.edu.tw/~kmchao. About this course.

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Brief Introduction to the Theory of Evolution

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AIMS

GEO, TCGA. Raw data n= 5,032. Clinical data. Quality control Normalization Combination of platforms. Analysis at www.kmplot.com. Remaining n=4,323. Filtering for gene expression. PostgreSQL database. Real time computation in R. Graphical feedback

169 views • 1 slides