PPT-Stochastic Context Free Grammars for RNA Structure Modeling

BMICS 776 wwwbiostatwiscedubmi776 Spring 2018 Anthony Gitter gitterbiostatwiscedu These slides excluding thirdparty material are licensed under CC BYNC 40 by Mark Craven Colin . N with state input and process noise linear noise corrupted observations Cx t 0 N is output is measurement noise 8764N 0 X 8764N 0 W 8764N 0 V all independent Linear Quadratic Stochastic Control with Partial State Obser vation 102 br 1. Roger L. Costello. April 12, 2014. Objective. This mini-tutorial will answer these questions:. What is Chomsky Normal Form? . 2. Objective. This mini-tutorial will answer these questions:. What is Chomsky Normal Form?. The Chomsky hierarchy of grammars . Context-free grammars describe languages that regular grammars can’t . Unrestricted. Context-sensitive. Context-free. Regular. Slide after Durbin, . et al. ., 1998. Part I: Multistage problems. Anupam. Gupta. Carnegie Mellon University. stochastic optimization. Question: . How to model uncertainty in the inputs?. data may not yet be available. obtaining exact data is difficult/expensive/time-consuming. Anupam. Gupta. Carnegie Mellon University. stochastic optimization. Question: . How to model uncertainty in the inputs?. data may not yet be available. obtaining exact data is difficult/expensive/time-consuming. Cradle. -to-Cradle . Design. . Douglas H. Fisher . Vanderbilt University. douglas.h.fisher@. vanderbilt.edu. Mary Lou Maher . University of Maryland, College Park. marylou.maher@. gmail.com. Presentation to the . Stryer. Short course. Chapter 33. Nucleic Acid Structure. Nucleobase. Nucleoside. Nucleotide. Nucleic acid. Chromatin. Chromosome. Polymeric Structure. Polymer ideal for informational molecule. Ribose and deoxyribose. Monte Carlo Tree Search. Minimax. search fails for games with deep trees, large branching factor, and no simple heuristics. Go: branching factor . 361 (19x19 board). Monte Carlo Tree Search. Instead . Processes:. An Overview. Math 182 2. nd. . sem. ay 2016-2017. Stochastic Process. Suppose. we have an index set . . We usually call this “time”. where . is a stochastic or random process . 2.6 Structure of DNA & RNA. Understandings:. The nucleic acids DNA & RNA are polymers of nucleotides.. DNA differs from RNA in the # of strands normally present, the base composition & type of pentose.. Attributes can have any type, but often they are trees. Example:. context-free grammar rule: . A ::= B C. attribute grammar rules:. A ::= B C . { . Plus($1. , $. 2. ) . }. or, . e.g.. A ::= B. 02 - 710 Computational Genomics Seyoung Kim Outline • RNA folding • Dynamic programming for RNA secondary structure prediction • Covariance model for RNA structure prediction RNA Basics • RN Cognitive Psychology. Notes 11. Where We Are. We. ’. re continuing with higher cognition. We still have:. Language—Structure. Language—Meaning. Reasoning/Decision making. Human factors. Plan of Attack. CSE 5403: Stochastic Process Cr. 3.00. Course Leaner: 2. nd. semester of MS 2015-16. Course Teacher: A H M Kamal. Stochastic Process for MS. Sample:. The sample mean is the average value of all the observations in the data set. Usually,.