Topic 2 Adam Godzik. JCSG approach: no model archives, building models “on the fly”

Slides:

Advertisements

Similar presentations

Predicting Kinase Binding Affinity Using Homology Models in CCORPS

Advertisements

Composition of functions constructing a function from 2 functions (g o f) = g[f(x)] –for all x in domain of f such that f(x) is in domain of g –f is applied.

Protein – Protein Interactions Lisa Chargualaf Simon Kanaan Keefe Roedersheimer Others: Dr. Izaguirre, Dr. Chen, Dr. Wuchty, ChengBang Huang.

Blast to Psi-Blast Blast makes use of Scoring Matrix derived from large number of proteins. What if you want to find homologs based upon a specific gene.

Pfam(Protein families )

Segmenting G-Protein Coupled Receptors using Language Models Betty Yee Man Cheng Language Technologies Institute, CMU Advisors:Judith Klein-Seetharaman.

Bioinformatics for biomedicine Seminar: Sequence analysis of a favourite gene Lecture 5, Per Kraulis

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

Structural bioinformatics

Protein Fold recognition Morten Nielsen, Thomas Nordahl CBS, BioCentrum, DTU.

Workshop on Biological Macromolecular Structure Models RCSB PDB Piscataway, NJ November 19-20, 2005 Topic 3: Structural Genomics and Models Contributors:

Summary Protein design seeks to find amino acid sequences which stably fold into specific 3-D structures. Modeling the inherent flexibility of the protein.

Protein Structure Prediction II

Bioinformatics for biomedicine Protein domains and 3D structure Lecture 4, Per Kraulis

Homology Modeling David Shiuan Department of Life Science and Institute of Biotechnology National Dong Hwa University.

Development of Bioinformatics and its application on Biotechnology

Protein domains. Protein domains are structural units (average 160 aa) that share: Function Folding Evolution Proteins normally are multidomain (average.

Practical session 2b Introduction to 3D Modelling and threading 9:30am-10:00am 3D modeling and threading 10:00am-10:30am Analysis of mutations in MYH6.

COMPARATIVE or HOMOLOGY MODELING

Lecture 10 – protein structure prediction. A protein sequence.

Fast Search Protein Structure Prediction Algorithm for Almost Perfect Matches1 By Jayakumar Rudhrasenan S Primary Supervisor: Prof. Heiko Schroder.

Sequence analysis: Macromolecular motif recognition Sylvia Nagl.

Multiple Alignment and Phylogenetic Trees Csc 487/687 Computing for Bioinformatics.

1 P9 Extra Discussion Slides. Sequence-Structure-Function Relationships Proteins of similar sequences fold into similar structures and perform similar.

Protein Folding Programs By Asım OKUR CSE 549 November 14, 2002.

Functional Annotation of Proteins via the CAFA Challenge Lee Tien Duncan Renfrow-Symon Shilpa Nadimpalli Mengfei Cao COMP150PBT | Fall 2010.

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

Structural proteomics

Take out you homework ( Page 12 from WB ) this will be one of the few times you need to separate a page out of your WB Write an equation to represent.

Bioinformatics how to … use publicly available free tools to predict protein structure by comparative modeling.

Protein structure prediction Anttu Kurttio Ville Pietiläinen.

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

November 18, 2000ICTCM 2000 Introductory Biological Sequence Analysis Through Spreadsheets Stephen J. Merrill Sandra E. Merrill Marquette University Milwaukee,

Protein Structure Prediction: Homology Modeling & Threading/Fold Recognition D. Mohanty NII, New Delhi.

Using structure in protein function annotation: predicting protein interactions Donald Petrey, Cliff Qiangfeng Zhang, Raquel Norel, Barry Honig Howard.

The Tree of Life How do we select a gene sequence for comparison?

Classification of protein and domain families Sequence to function Protein Family Resources and Protocols for Structural and Functional Annotation of Genome.

Structural proteomics Handouts. Proteomics section from book already assigned.

Protein Structure Database for Structural Genomics Group Jessica Lau December 13, 2004 M.S. Thesis Defense.

Exercises Pairwise alignment Homology search (BLAST) Multiple alignment (CLUSTAL W) Iterative Profile Search: Profile Search –Pfam –Prosite –PSI-BLAST.

Modelling proteomes Ram Samudrala University of Washington How does the genome of an organism specify its behaviour and characteristics?

BMC Bioinformatics 2005, 6(Suppl 4):S3 Protein Structure Prediction not a trivial matter Strict relation between protein function and structure Gap between.

Guidelines for sequence reports. Outline Summary Results & Discussion –Sequence identification –Function assignment –Fold assignment –Identification of.

Modelling proteomes: Application to understanding HIV disease progression Ram Samudrala Department of Microbiology University of Washington How does the.

HomologyIf twp proteins are homologous, they have a common fold and a common ancestor If two proteins have >25% identity across their entire length, they.

The Biologist’s Wishlist A complete and accurate set of all genes and their genomic positions A set of all the transcripts produced by each gene The location.

Considerations for multi-omics data integration Michael Tress CNIO,

With Mr. Adams $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500 $100 $200 $300 $400 $500.

Protein domains Miguel Andrade Mainz, Germany Faculty of Biology,

Anne Brown Josh Fitzgerald Jieqing Ping

Functional manual annotation including GO

Prediction of Regulatory Elements for Non-Model Organisms Rachita Sharma, Patricia.

Bioinformatics how to …

Algebraic Sequences.

Predicting Active Site Residue Annotations in the Pfam Database

Target selection strategies for the mouse genome

פחת ורווח הון סוגיות מיוחדות תהילה ששון עו"ד (רו"ח) ספטמבר 2015

Prediction of protein function from sequence analysis

Molecular Modeling By Rashmi Shrivastava Lecturer

Figure S4 Chr1 : CNAG_00378 CNAG_07950* CNAG_07358* CNAG_00383

SIFGD: Setaria italica Functional Genomics Database

Genome Pool Strategy for Structural Coverage of Protein Families

Novel p53 target genes identified by RNA-Seq, pSILAC and ChIP-Seq.

(A) Schematic of the TGGT1_254250/TgPRELID gene, mRNA, and predicted protein. (A) Schematic of the TGGT1_254250/TgPRELID gene, mRNA, and predicted protein.

Evidence for Evolution

Schematic representation of a transcriptomic evaluation approach.

Sequence Analysis Alan Christoffels

Suvobrata Chakravarty, Roberto Sanchez Structure

Presentation transcript:

Topic 2 Adam Godzik

JCSG approach: no model archives, building models “on the fly”

Modeling used in target selection with MR component Sequence of a potential target : >MELGIRDKGVLVAASRGIGRAVADVLSQEGAEVTICCARM >30% Seq id to a known structure yes Not a PSI target no Fold can be predicted no SelMet expression What is the Quality of the model bad Potential MR target good

In development Models for construct design –Tested for SARS targets –“computational DXMS” Models for planning of point mutations –Testing on several difficult targets

What is real impact of PSI - are new folds most important ? TM0875 from t.maritima new fold no homologs – an “orphan” no corresponding Pfam family from n.punctiforme two domains of known folds but no recognizable sequence similarity to known structures C-terminal domain provides the first structural template for Pfam family of over 500 sequences (PF00877)