Course Summary June 2, 2005 Programming Workshop Overview of course (presentation) Protein modeling, part 2 Instructor evaluations.

Slides:

Advertisements

Similar presentations

Alignment methods Introduction to global and local sequence alignment methods Global : Needleman-Wunch Local : Smith-Waterman Database Search BLAST FASTA.

Advertisements

1 Genome information GenBank (Entrez nucleotide) Species-specific databases Protein sequence GenBank (Entrez protein) UniProtKB (SwissProt) Protein structure.

NCBI data, sliding window programs and dot plots Sept. 25, 2012 Learning objectives-Become familiar with OMIM and PubMed. Understand the difference between.

© Wiley Publishing All Rights Reserved. How Most People Use Bioinformatics.

On line (DNA and amino acid) Sequence Information Lecture 7.

Welcome to Chem 434 Bioinformatics Sept 20, 2012 Review of course prerequisites Review of syllabus Review of CSULA Bioinformatics Course website.

Prediction to Protein Structure Fall 2005 CSC 487/687 Computing for Bioinformatics.

Structural bioinformatics

Intro to Bioinformatics Summary. What did we learn Pairwise alignment – Local and Global Alignments When? How ? Tools : for local blast2seq, for global.

Southern California Bioinformatics Summer Institute Wendie Johnston, Beverly Krilowicz, Jamil Momand, Sandra Sharp, Nancy Warter- Perez.

Sequence Similarity Searching Class 4 March 2010.

Archives and Information Retrieval

Heuristic alignment algorithms and cost matrices

Southern California Bioinformatics Summer Institute Wendie Johnston, Beverly Krilowicz, Jamil Momand, Sandra Sharp, Nancy Warter-Perez.

Expect value Expect value (E-value) Expected number of hits, of equivalent or better score, found by random chance in a database of the size.

Overview of sequence database searching techniques and multiple alignment May 1, 2001 Quiz on May 3-Dynamic programming- Needleman-Wunsch method Learning.

Welcome to Chem 434 Bioinformatics March 25, 2008 Review of course prerequisites Review of syllabus Review of Bioinformatics Course website Course objectives.

Alignment methods and database searching April 14, 2005 Quiz#1 today Learning objectives- Finish Dotter Program analysis. Understand how to use the program.

Southern California Bioinformatics Summer Institute Wendie Johnston, Beverly Krilowicz, Jamil Momand, Sandra Sharp, Nancy Warter-Perez.

Introduction to Bioinformatics - Tutorial no. 2 Global Alignment Local Alignment FASTA BLAST.

Sequence Alignment III CIS 667 February 10, 2004.

Sequence comparisons June 23, 2009 Learning objectives-Understand the concept of sliding window programs. Understand difference between identity, similarity.

BLOSUM Information Resources Algorithms in Computational Biology Spring 2006 Created by Itai Sharon.

Signaling Pathways and Summary June 30, 2005 Signaling lecture Course summary Tomorrow Next Week Friday, 7/8/05 Morning presentation of writing assignments.

Detecting the Domain Structure of Proteins from Sequence Information Niranjan Nagarajan and Golan Yona Department of Computer Science Cornell University.

Alignment methods II April 24, 2007 Learning objectives- 1) Understand how Global alignment program works using the longest common subsequence method.

Protein Structures.

Presented by Liu Qi An introduction to Bioinformatics Algorithms Qi Liu

On line (DNA and amino acid) Sequence Information

Pairwise Alignment How do we tell whether two sequences are similar? BIO520 BioinformaticsJim Lund Assigned reading: Ch , Ch 5.1, get what you can.

Wellcome Trust Workshop Working with Pathogen Genomes Module 3 Sequence and Protein Analysis (Using web-based tools)

Bioinformatics.

Sequence Alignment Techniques. In this presentation…… Part 1 – Searching for Sequence Similarity Part 2 – Multiple Sequence Alignment.

Doug Raiford Lesson 3.  More and more sequence data is being generated every day  Useless if not made available to other researchers.

Basic Overview of Bioinformatics Tools and Biocomputing Applications I Dr Tan Tin Wee Director Bioinformatics Centre.

Scoring Matrices April 23, 2009 Learning objectives- 1) Last word on Global Alignment 2) Understand how the Smith-Waterman algorithm can be applied to.

Module 3 Sequence and Protein Analysis (Using web-based tools) Working with Pathogen Genomes - Uruguay 2008.

Sequence Based Analysis Tutorial NIH Proteomics Workshop Lai-Su Yeh, Ph.D. Protein Information Resource at Georgetown University Medical Center.

Local alignment, BLAST and Psi-BLAST October 25, 2012 Local alignment Quiz 2 Learning objectives-Learn the basics of BLAST and Psi-BLAST Workshop-Use BLAST2.

NCBI resources II: web-based tools and ftp resources Yanbin Yin Fall 2014 Most materials are downloaded from ftp://ftp.ncbi.nih.gov/pub/education/ 1.

Construction of Substitution Matrices

Function preserves sequences Christophe Roos - MediCel ltd Similarity is a tool in understanding the information in a sequence.

Protein Secondary Structure, Bioinformatics Tools, and Multiple Sequence Alignments Finding Similar Sequences Predicting Secondary Structures Predicting.

REMINDERS 2 nd Exam on Nov.17 Coverage: Central Dogma of DNA Replication Transcription Translation Cell structure and function Recombinant DNA technology.

Protein Sequence Analysis - Overview - NIH Proteomics Workshop 2007 Raja Mazumder Scientific Coordinator, PIR Research Assistant Professor, Department.

BLAST Slides adapted & edited from a set by Cheryl A. Kerfeld (UC Berkeley/JGI) & Kathleen M. Scott (U South Florida) Kerfeld CA, Scott KM (2011) Using.

BIOLOGICAL DATABASES. BIOLOGICAL DATA Bioinformatics is the science of Storing, Extracting, Organizing, Analyzing, and Interpreting information in biological.

An overview of Bioinformatics. Cell and Central Dogma.

Sequence Based Analysis Tutorial March 26, 2004 NIH Proteomics Workshop Lai-Su L. Yeh, Ph.D. Protein Science Team Lead Protein Information Resource at.

341- INTRODUCTION TO BIOINFORMATICS Overview of the Course Material 1.

Point Specific Alignment Methods PSI – BLAST & PHI – BLAST.

Doug Raiford Lesson 5.  Dynamic programming methods  Needleman-Wunsch (global alignment)  Smith-Waterman (local alignment)  BLAST Fixed: best Linear:

Sequence Alignment.

Construction of Substitution matrices

Bioinformatics Computing 1 CMP 807 – Day 2 Kevin Galens.

Bioinformatics Chem 434 Dr. Nancy Warter-Perez Computer Engineering Dr. Jamil Momand Chemistry & Biochemistry.

Copyright OpenHelix. No use or reproduction without express written consent1.

Information retrieval and sliding window programs April 5, 2011 Hand in Homework #1. Homework #2 due Tuesday, April 12. Learning objectives- Understand.

Introduction to Bioinformatics Summary Thomas Nordahl Petersen.

Welcome to the Protein Database Tutorial. This tutorial will describe how to navigate the section of Gramene that provides collective information on proteins.

Techniques for Protein Sequence Alignment and Database Searching G P S Raghava Scientist & Head Bioinformatics Centre, Institute of Microbial Technology,

Using BLAST To Teach ‘E-value-tionary’ Concepts Cheryl A. Kerfeld 1, 2 and Kathleen M. Scott 3 1.Department of Energy-Joint Genome Institute, Walnut Creek,

DNA SEQUENCE ALIGNMENT FOR PROTEIN SIMILARITY ANALYSIS CARL EBERLE, DANIEL MARTINEZ, MENGDI TAO.

Computer Applications and Bioinformatics

Bioinformatics Biological Data Computer Calculations +

Sequence Based Analysis Tutorial

Protein Structures.

Basic Local Alignment Search Tool (BLAST)

BLAST Slides adapted & edited from a set by

BLAST Slides adapted & edited from a set by

Presentation transcript:

Course Summary June 2, 2005 Programming Workshop Overview of course (presentation) Protein modeling, part 2 Instructor evaluations

Course Summary Course Learning Objectives (from course syllabus): Retrieve gene sequence information from GenBank Use BLAST program to conduct gene similarity searches Predict protein functional motifs with BLIMPs Write algorithms that will perform a simple search of gene sequences stored in a database Understand the statistics used in scoring aligned sequences in common programs. Display and compare 3-D structures of proteins

List of software programs you should be familiar with PubMed Dotter Needleman-Wunsch global alignment Smith-Waterman local alignment BLAST PSI-BLAST FASTA Chou-Fasman Kyte-Doolittle (hydrophobicity) GOR BLIMP PSIPRED DeepView (Swiss PDB viewer)

List of databases that we studied Online Mendelian Inheritance of Man MedLine GenBank SWISSPROT Protein Information Resource ProSite BLOCKS Protein Data Bank (PDB)

Concepts in bioinformatics ENTREZ-Suite of connected programs that allow for analysis of genes and proteins Modular nature of proteins Sliding window Alignment methods (Local vs. Global) Dynamic programming Statistics (E-value, Counting principle)

Concepts in bioinformatics II Primary and secondary databases Similarity vs. identical amino acids Scoring matrices (PAM, BLOSUM, PSSM) Neural networks Protein structure prediction Create software program that aligns sequences based on scoring matrices

Future of bioinformatics Traditionally divided into two camps-users and developers CSULA students should have an advantage over the typical applicant to graduate school or industry position Online Journal of Bioinformatics Bio InformBio Inform-a newsletter for bioinformaticists

Extra Questions for Evaluation Extra questions to add to the evaluation (Place on Prof. Momand’s evaluation form) Question 12: This course will help you further your career. Question 14: The programming component increased your understanding of the field of bioinformatics. Question 15: The course workload, compared to other 4 unit science classes, was (a) too heavy, (b) too light, (c) just right. Aside from specific comments on Prof. Momand please use part D of the evaluation form to comment on each of the following topics: 1) What prerequisite courses would help you increase your performance in this course? 2) What components of the bioinformatics field would you like to see expanded into a second, more advanced, course?