The top documents tagged [sequences of length]

CMSC 150 RECURSION CS 150: Mon 26 Mar 2012. Motivation : Bioinformatics Example A G A C T A G T T A C C G A G A C G T Want to compare sequences
Documents CMSC 150 RECURSION CS 150: Mon 26 Mar 2012. Motivation : Bioinformatics Example A G A C T A G T T A C C G A G A C G T Want to compare sequences

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OUTLINE Scoring Matrices Probability of matching runs Quality of a database match
Documents OUTLINE Scoring Matrices Probability of matching runs Quality of a database match

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The Evolution of Conventions H. Peyton Young Presented by Na Li and Cory Pender
Documents The Evolution of Conventions H. Peyton Young Presented by Na Li and Cory Pender

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Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data John Lafferty Andrew McCallum Fernando Pereira
Documents Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data John Lafferty Andrew McCallum Fernando Pereira

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Structure-Function Analysis 117 Jan 2006 DNA/Protein structure-function analysis and prediction Protein Folding and energetics: –Introduction to folding
Documents Structure-Function Analysis 117 Jan 2006 DNA/Protein structure-function analysis and prediction Protein Folding and energetics: –Introduction to folding

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CS267 Assignment 3: Parallelize Graph Algorithms for de Novo Genome Assembly Spring 2015
Documents CS267 Assignment 3: Parallelize Graph Algorithms for de Novo Genome Assembly Spring 2015

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1 DNA1: Last week's take-home lessons Types of mutants Mutation, drift, selection Binomial for each Association studies 2 statistic Linked & causative
Documents 1 DNA1: Last week's take-home lessons Types of mutants Mutation, drift, selection Binomial for each Association studies 2 statistic Linked & causative

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Sequence analysis 2005 - lecture 6 Sequence analysis course Lecture 6 Multiple sequence alignment 2 of 3 Multiple alignment methods
Documents Sequence analysis 2005 - lecture 6 Sequence analysis course Lecture 6 Multiple sequence alignment 2 of 3 Multiple alignment methods

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CS 188: Artificial Intelligence Spring 2007 Lecture 29: Post-midterm course review 5/8/2007 Srini Narayanan – ICSI and UC Berkeley
Documents CS 188: Artificial Intelligence Spring 2007 Lecture 29: Post-midterm course review 5/8/2007 Srini Narayanan – ICSI and UC Berkeley

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What you should know by now Concepts: Pairwise alignment Global, semi-global and local alignment Dynamic programming Sequence similarity (Sum-of-Pairs)
Documents What you should know by now Concepts: Pairwise alignment Global, semi-global and local alignment Dynamic programming Sequence similarity (Sum-of-Pairs)

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Aligning Alignments Exactly By John Kececioglu, Dean Starrett CS Dept. Univ. of Arizona Appeared in 8 th ACM RECOME 2004, Presented by Jie Meng
Documents Aligning Alignments Exactly By John Kececioglu, Dean Starrett CS Dept. Univ. of Arizona Appeared in 8 th ACM RECOME 2004, Presented by Jie Meng

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Representation of Strings Background Huffman Encoding
Documents Representation of Strings Background Huffman Encoding

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