lec02 - CSE 427 Computational Biology Gene Prediction A...

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CSE 427 Computational Biology Gene Prediction
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3 A statistical interlude: Fair or biased? H H H H T H H T T H
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4 More likely fair or biased? H H H H T H H T T H
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5 More likely H0 or H1? H H H H T H H T T H H0: .5 – .5 H1: .9 – .1
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6 Quantify likelihood: H 0 vs H 1 H H H H T H H T T H H0: .5 – .5 .5^10 H1: .9 – .1 .9^7 * .1^3 Likelihood ratio: (.5^10)/(.9^7 * .1^3) = .4898 (I.e., odds favor “biased” by about 2:1)
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7 Gene Finding: Motivation Sequence data flooding into Genbank What does it mean? protein genes, RNA genes, mitochondria, chloroplast, regulation, replication, structure, repeats, transposons, unknown stuff, …
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8 Protein Coding Nuclear DNA Focus of this lecture Goal: Automated annotation of new sequence data State of the Art: In Eukaryotes: predictions ~ 60% similar to real proteins ~80% if database similarity used Prokaryotes better, but still imperfect lab verification still needed, still expensive
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Biological Basics Central Dogma: DNA transcription RNA translation
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This note was uploaded on 04/22/2008 for the course CSC 427 taught by Professor Ruzzo during the Winter '08 term at University of Washington.

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lec02 - CSE 427 Computational Biology Gene Prediction A...

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