Péter Antal Ádám Arany Bence Bolgár András Gézsi Gergely Hajós Gábor Hullám Péter Marx András Millinghoffer László Poppe Péter Sárközy BIOINFORMATICS

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Péter Antal Ádám Arany Bence Bolgár András Gézsi Gergely Hajós Gábor Hullám Péter Marx András Millinghoffer László Poppe Péter Sárközy BIOINFORMATICS"

Transcription

1 Péter Antal Ádám Arany Bence Bolgár András Gézsi Gergely Hajós Gábor Hullám Péter Marx András Millinghoffer László Poppe Péter Sárközy BIOINFORMATICS The Bioinformatics book covers new topics in the rapidly expanding field of bioinformatics, from next-generation sequencing to drug discovery and metagenomics. The first two chapters overviews genetic measurement methods. The next four chapters discuss topics related to the effect of genetic variants from protein modeling to gene regulatory networks. Standard statistical analysis in association studies are discussed in the next two chapters. The systems biology approach is illustrated by discussing a systems-based biomarker analysis method, the graph-based network science, the dynamical systems based approaches and a Bayesian causal inference method in subsequent chapters. The next chapter discusses text-mining methods in biomedicine, especially their application in interpretation and translation. The decision theoretic approach to study design, especially multi-stage, sequential study design is discussed in the next chapter, introducing the concepts of value of information and the expected value of an experiment. Next, the heterogeneity of biomedical big data sources is overviewed, together with data and knowledge fusion methods, and with the discussion of semantic publishing, which can lead to a new unification of biomedicine. Subsequently, bioinformatic workflow methods are summarized. At last, drug discovery methods are overviewed with an outlook for personalized medicine and the final chapter presents the main steps and workflows in metagenomics. Keywords: genotyping, next-generation sequencing methods, protein modeling, gene regulatory networks, omic networks, study design, data and knowledge fusion, worklfow systems, association study, biomarker analysis, medical decision support systems, semantic publishing, similarity based drug discovery, metagenomics. Budapest University of Technology & Economics and Semmelweis University Typotex Kiadó 2014

2 COPYRIGHT: , Péter Antal, Ádám Arany, Bence Bolgár, András Gézsi, Gergely Hajós, Gábor Hullám, Péter Marx, András Millinghoffer, László Poppe, Péter Sárközy, Budapest University of Technology and Economics, Semmelweis University Creative Commons NonCommercial-NoDerivs 3.0 (CC BY-NC-ND 3.0) Terms of use of : This work can be reproduced, circulated, published and performed for non-commercial purposes without restriction by indicating the author s name, but it cannot be modified. Scientific lectors: Viktor Molnár, András Antos ISBN Prepared under the editorship of Typotex Kiadó Responsible manager: Zsuzsa Votisky Prepared within the framework of the project Konzorcium a biotechnológia aktív tanulásáért ( Consortium for the Active Studying of Biotechnology ) Grant No. TÁMOP /A/1-11/

3 Contents 1 DNA recombinant measurement technology, noise and error models Historic overview Clinical aspects of genome sequencing Partial Genetic Association Studies Genome Wide Association Studies First generation automated Sanger sequencing Next generation sequencing technologies Pyrosequencing and ph based sequencing Reversible terminator based sequencing Nanopore based sequencing Error characteristics of Next Generation Sequencing Carry forward/incomplete extension Homopolymer errors Capture technologies PCR capture Emulsion PCR Bridge amplification Targeted resequencing De-novo sequencing Next generation sequencing workflows Filtering Mapping Assembly Variant calling Paired end sequencing Multiplexing samples The post-processing, haplotype reconstruction, and imputation Genome Genotype Single nucleotide polymorphisms Types of point mutation Haplotypes and recombination

4 Contents Linkage Disequilibrium Haplotype reconstruction Imputation Genotyping platforms Sample preparation Regions of interest Primer Design PCR Probe-tag based genotyping Sanger sequencing Real-time qualitative polymerase chain reaction SNP arrays Genotyping vs. gene expression Call rate and accuracy Comparative protein modeling and molecular docking Introduction The protein structure gap Methods of protein modeling Comparative protein modeling Steps of homology modeling Tools for homology modeling Molecular docking Protein-ligand interaction predictions Protein-biomacromolecule interaction predictions Methods of determining structure of proteins and protein structure databases Introduction Protein identification tools Simple protein analyses Levels and problems of protein structure predictions Experimental methods to determine the secondary structure of proteins Protein circular dichroism (CD) Synchrotron radiation circular dichroism (SRCD) Experimental methods to determining atomic structures of proteins Protein X-ray crystallography Protein NMR spectroscopy Protein electron microscopy, electron diffraction and electron crystallography Protein neutron crystallography

5 Contents 5 5 Quantitative models of the functional effects of genetic variants Introduction Variants SNP, indel Alternative splicing Levels of regulation Different regulatory elements microrna mirna development mirna regulatory methods Transcription factors Epigenetics Methylation Histone modifications Mathematical models of gene regulatory networks Introduction Learning networks Representation Types of network learning algorithms TF, mirna, mrna regulatory networks Standard analysis of genetic association studies Introduction Genetic data transformation Filtering Standard test for Hardy Weinberg equilibrium Phenotype data transformation Transformation Discretization Univariate analysis methods Standard association tests Cochran Armitage test for trend Odds ratios Univariate Bayesian methods Multivariate analysis methods Logistic regression Haplotype association Analysis of statistical power Analyzing gene expression studies Introduction Pre-procession

6 Contents Background correction Normalization Summarization Filtering Data analysis Clustering Differential expression Biological interpretation of results Biomarker analysis 115 Notation Introduction Background Bayesian multilevel analysis of relevance Multivariate scalability: k-mbs and k-mbg features A knowledge-rich aggregation of input features Interaction, redundancy based on posterior decomposition Relevance for multiple targets Conditional and contextual relevance Posteriors for the predictive power of input features Algorithmic aspects and applications Summary Network biology Introduction Biological networks Basics of graph theory Network analysis Network topology Network models and dynamics Assortativity, degree distribution and scale-free networks Tasks and challenges An application to drug discovery Dynamic modeling in cell biology Biochemical concepts and their computational representations Modeling with ordinary differential equations Stochastic modeling Hybrid methods Reaction diffusion systems Model fitting Whole-cell simulation Overview

7 Contents 7 12 Causal inference in biomedicine 152 Notation Introduction Representing independence and causal relations by Bayesian networks Constraint based inference of causal relations and models Learning complete causal domain models Bayesian inference of causal features Edges: direct pairwise dependencies Pairwise causal relations MBG subnetworks Ordering of the variables Effect modifiers Text mining methods in bioinformatics Introduction Biomedical text mining Constructing the corpus Constructing the vocabulary Text mining tasks Basic techniques Pattern matching Document representation Methods for named entity recognition Methods for relation extraction Lexicalized probabilistic context-free grammars Difficulties in biomedical text mining Text mining and knowledge management Experimental design: from the basics to active learning extensions Introduction The elements of experimental design Phases of biomedical DOE Types of biological experiments A decision theoretic approach to DoE Expected value of an experiment Adaptive designs and budgeted learning A Bayesian treatment of sequential decision processes Approaches to target variable selection Gene Prioritization Active learning Other practical tasks relying on bioinformatics

8 Contents 8 15 Big data in biomedicine Introduction The first wave of biomedical big data Post-genomic big data: the second wave The common big data The health-related common big data in biomedicine Bioinformatic challenges of common big data Analysis of heterogeneous biomedical data through information fusion Introduction Information fusion and data fusion Types of data fusion Early fusion Intermediate fusion Late fusion Similarity-based data fusion The Bayesian Encyclopedia Introduction The three worlds of data, knowledge and computation From fragmentation problems to workflow for unification Data repositories with semantic technologies Semantic publishing for the literature world Causal Bayesian network-based data analytic knowledge bases Examples for links between worlds Prospects for the Bayesian Encyclopedia Bioinformatical workflow systems case study Overview of tasks Data model and representation Use cases and architecture Implementation details of the server Postprocessing steps Computational aspects of pharmaceutical research Overview of the process Chemoinformatical background Screening criteria Method Fragment-based design Drug repositioning

9 Contents 9 20 Metagenomics Introduction Metagenome analysis Community profiling Functional metagenomics Metagenomics step by step Sampling Sequencing Assembly Binning Gene calling and functional inference

Data Mining and Applications in Genomics

Data Mining and Applications in Genomics Data Mining and Applications in Genomics Lecture Notes in Electrical Engineering Volume 25 For other titles published in this series, go to www.springer.com/series/7818 Sio-Iong Ao Data Mining and Applications

More information

GREG GIBSON SPENCER V. MUSE

GREG GIBSON SPENCER V. MUSE A Primer of Genome Science ience THIRD EDITION TAGCACCTAGAATCATGGAGAGATAATTCGGTGAGAATTAAATGGAGAGTTGCATAGAGAACTGCGAACTG GREG GIBSON SPENCER V. MUSE North Carolina State University Sinauer Associates, Inc.

More information

Welcome to the NGS webinar series

Welcome to the NGS webinar series Welcome to the NGS webinar series Webinar 1 NGS: Introduction to technology, and applications NGS Technology Webinar 2 Targeted NGS for Cancer Research NGS in cancer Webinar 3 NGS: Data analysis for genetic

More information

Introduction to RNA-Seq. David Wood Winter School in Mathematics and Computational Biology July 1, 2013

Introduction to RNA-Seq. David Wood Winter School in Mathematics and Computational Biology July 1, 2013 Introduction to RNA-Seq David Wood Winter School in Mathematics and Computational Biology July 1, 2013 Abundance RNA is... Diverse Dynamic Central DNA rrna Epigenetics trna RNA mrna Time Protein Abundance

More information

CS273B: Deep Learning in Genomics and Biomedicine. Recitation 1 30/9/2016

CS273B: Deep Learning in Genomics and Biomedicine. Recitation 1 30/9/2016 CS273B: Deep Learning in Genomics and Biomedicine. Recitation 1 30/9/2016 Topics Genetic variation Population structure Linkage disequilibrium Natural disease variants Genome Wide Association Studies Gene

More information

ALGORITHMS IN BIO INFORMATICS. Chapman & Hall/CRC Mathematical and Computational Biology Series A PRACTICAL INTRODUCTION. CRC Press WING-KIN SUNG

ALGORITHMS IN BIO INFORMATICS. Chapman & Hall/CRC Mathematical and Computational Biology Series A PRACTICAL INTRODUCTION. CRC Press WING-KIN SUNG Chapman & Hall/CRC Mathematical and Computational Biology Series ALGORITHMS IN BIO INFORMATICS A PRACTICAL INTRODUCTION WING-KIN SUNG CRC Press Taylor & Francis Group Boca Raton London New York CRC Press

More information

Types of Databases - By Scope

Types of Databases - By Scope Biological Databases Bioinformatics Workshop 2009 Chi-Cheng Lin, Ph.D. Department of Computer Science Winona State University clin@winona.edu Biological Databases Data Domains - By Scope - By Level of

More information

TECHNOLOGIES, PRODUCTS & SERVICES for MOLECULAR DIAGNOSTICS, MDx ABA 298

TECHNOLOGIES, PRODUCTS & SERVICES for MOLECULAR DIAGNOSTICS, MDx ABA 298 DIAGNOSTICS BUSINESS ANALYSIS SERIES: TECHNOLOGIES, PRODUCTS & SERVICES for MOLECULAR DIAGNOSTICS, MDx ABA 298 By ADAMS BUSINESS ASSOCIATES March 2017. March 2017 ABA 298 1 Technologies, Products & Services

More information

Microbial Metabolism Systems Microbiology

Microbial Metabolism Systems Microbiology 1 Microbial Metabolism Systems Microbiology Ching-Tsan Huang ( 黃慶璨 ) Office: Agronomy Hall, Room 111 Tel: (02) 33664454 E-mail: cthuang@ntu.edu.tw MIT OCW Systems Microbiology aims to integrate basic biological

More information

AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE

AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE ACCELERATING PROGRESS IS IN OUR GENES AGILENT S BIOINFORMATICS ANALYSIS SOFTWARE GENESPRING GENE EXPRESSION (GX) MASS PROFILER PROFESSIONAL (MPP) PATHWAY ARCHITECT (PA) See Deeper. Reach Further. BIOINFORMATICS

More information

Introductie en Toepassingen van Next-Generation Sequencing in de Klinische Virologie. Sander van Boheemen Medical Microbiology

Introductie en Toepassingen van Next-Generation Sequencing in de Klinische Virologie. Sander van Boheemen Medical Microbiology Introductie en Toepassingen van Next-Generation Sequencing in de Klinische Virologie Sander van Boheemen Medical Microbiology Next-generation sequencing Next-generation sequencing (NGS), also known as

More information

resequencing storage SNP ncrna metagenomics private trio de novo exome ncrna RNA DNA bioinformatics RNA-seq comparative genomics

resequencing storage SNP ncrna metagenomics private trio de novo exome ncrna RNA DNA bioinformatics RNA-seq comparative genomics RNA Sequencing T TM variation genetics validation SNP ncrna metagenomics private trio de novo exome mendelian ChIP-seq RNA DNA bioinformatics custom target high-throughput resequencing storage ncrna comparative

More information

Contact us for more information and a quotation

Contact us for more information and a quotation GenePool Information Sheet #1 Installed Sequencing Technologies in the GenePool The GenePool offers sequencing service on three platforms: Sanger (dideoxy) sequencing on ABI 3730 instruments Illumina SOLEXA

More information

Sequencing technologies. Jose Blanca COMAV institute bioinf.comav.upv.es

Sequencing technologies. Jose Blanca COMAV institute bioinf.comav.upv.es Sequencing technologies Jose Blanca COMAV institute bioinf.comav.upv.es Outline Sequencing technologies: Sanger 2nd generation sequencing: 3er generation sequencing: 454 Illumina SOLiD Ion Torrent PacBio

More information

Sequencing technologies. Jose Blanca COMAV institute bioinf.comav.upv.es

Sequencing technologies. Jose Blanca COMAV institute bioinf.comav.upv.es Sequencing technologies Jose Blanca COMAV institute bioinf.comav.upv.es Outline Sequencing technologies: Sanger 2nd generation sequencing: 3er generation sequencing: 454 Illumina SOLiD Ion Torrent PacBio

More information

Introduction to Bioinformatics and Gene Expression Technologies

Introduction to Bioinformatics and Gene Expression Technologies Introduction to Bioinformatics and Gene Expression Technologies Utah State University Fall 2017 Statistical Bioinformatics (Biomedical Big Data) Notes 1 1 Vocabulary Gene: hereditary DNA sequence at a

More information

Introduction to Bioinformatics and Gene Expression Technology

Introduction to Bioinformatics and Gene Expression Technology Vocabulary Introduction to Bioinformatics and Gene Expression Technology Utah State University Spring 2014 STAT 5570: Statistical Bioinformatics Notes 1.1 Gene: Genetics: Genome: Genomics: hereditary DNA

More information

Smart India Hackathon

Smart India Hackathon TM Persistent and Hackathons Smart India Hackathon 2017 i4c www.i4c.co.in Digital Transformation 25% of India between age of 16-25 Our country needs audacious digital transformation to reach its potential

More information

Lecture #1. Introduction to microarray technology

Lecture #1. Introduction to microarray technology Lecture #1 Introduction to microarray technology Outline General purpose Microarray assay concept Basic microarray experimental process cdna/two channel arrays Oligonucleotide arrays Exon arrays Comparing

More information

2/23/16. Protein-Protein Interactions. Protein Interactions. Protein-Protein Interactions: The Interactome

2/23/16. Protein-Protein Interactions. Protein Interactions. Protein-Protein Interactions: The Interactome Protein-Protein Interactions Protein Interactions A Protein may interact with: Other proteins Nucleic Acids Small molecules Protein-Protein Interactions: The Interactome Experimental methods: Mass Spec,

More information

Genome-Wide Association Studies (GWAS): Computational Them

Genome-Wide Association Studies (GWAS): Computational Them Genome-Wide Association Studies (GWAS): Computational Themes and Caveats October 14, 2014 Many issues in Genomewide Association Studies We show that even for the simplest analysis, there is little consensus

More information

Sequence Variations. Baxevanis and Ouellette, Chapter 7 - Sequence Polymorphisms. NCBI SNP Primer:

Sequence Variations. Baxevanis and Ouellette, Chapter 7 - Sequence Polymorphisms. NCBI SNP Primer: Sequence Variations Baxevanis and Ouellette, Chapter 7 - Sequence Polymorphisms NCBI SNP Primer: http://www.ncbi.nlm.nih.gov/about/primer/snps.html Overview Mutation and Alleles Linkage Genetic variation

More information

Agilent GeneSpring GX 10: Beyond. Pam Tangvoranuntakul Product Manager, GeneSpring October 1, 2008

Agilent GeneSpring GX 10: Beyond. Pam Tangvoranuntakul Product Manager, GeneSpring October 1, 2008 Agilent GeneSpring GX 10: Gene Expression and Beyond Pam Tangvoranuntakul Product Manager, GeneSpring October 1, 2008 GeneSpring GX 10 in the News Our Goals for GeneSpring GX 10 Goal 1: Bring back GeneSpring

More information

BIOINFORMATICS AND SYSTEM BIOLOGY (INTERNATIONAL PROGRAM)

BIOINFORMATICS AND SYSTEM BIOLOGY (INTERNATIONAL PROGRAM) BIOINFORMATICS AND SYSTEM BIOLOGY (INTERNATIONAL PROGRAM) PROGRAM TITLE DEGREE TITLE Master of Science Program in Bioinformatics and System Biology (International Program) Master of Science (Bioinformatics

More information

SNPs - GWAS - eqtls. Sebastian Schmeier

SNPs - GWAS - eqtls. Sebastian Schmeier SNPs - GWAS - eqtls s.schmeier@gmail.com http://sschmeier.github.io/bioinf-workshop/ 17.08.2015 Overview Single nucleotide polymorphism (refresh) SNPs effect on genes (refresh) Genome-wide association

More information

Functional Genomics Overview RORY STARK PRINCIPAL BIOINFORMATICS ANALYST CRUK CAMBRIDGE INSTITUTE 18 SEPTEMBER 2017

Functional Genomics Overview RORY STARK PRINCIPAL BIOINFORMATICS ANALYST CRUK CAMBRIDGE INSTITUTE 18 SEPTEMBER 2017 Functional Genomics Overview RORY STARK PRINCIPAL BIOINFORMATICS ANALYST CRUK CAMBRIDGE INSTITUTE 18 SEPTEMBER 2017 Agenda What is Functional Genomics? RNA Transcription/Gene Expression Measuring Gene

More information

Machine learning applications in genomics: practical issues & challenges. Yuzhen Ye School of Informatics and Computing, Indiana University

Machine learning applications in genomics: practical issues & challenges. Yuzhen Ye School of Informatics and Computing, Indiana University Machine learning applications in genomics: practical issues & challenges Yuzhen Ye School of Informatics and Computing, Indiana University Reference Machine learning applications in genetics and genomics

More information

Unit 6: Molecular Genetics & DNA Technology Guided Reading Questions (100 pts total)

Unit 6: Molecular Genetics & DNA Technology Guided Reading Questions (100 pts total) Name: AP Biology Biology, Campbell and Reece, 7th Edition Adapted from chapter reading guides originally created by Lynn Miriello Chapter 16 The Molecular Basis of Inheritance Unit 6: Molecular Genetics

More information

Chapter 6 - Molecular Genetic Techniques

Chapter 6 - Molecular Genetic Techniques Chapter 6 - Molecular Genetic Techniques Two objects of molecular & genetic technologies For analysis For generation Molecular genetic technologies! For analysis DNA gel electrophoresis Southern blotting

More information

Midterm 1 Results. Midterm 1 Akey/ Fields Median Number of Students. Exam Score

Midterm 1 Results. Midterm 1 Akey/ Fields Median Number of Students. Exam Score Midterm 1 Results 10 Midterm 1 Akey/ Fields Median - 69 8 Number of Students 6 4 2 0 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 Exam Score Quick review of where we left off Parental type: the

More information

Human genetic variation

Human genetic variation Human genetic variation CHEW Fook Tim Human Genetic Variation Variants contribute to rare and common diseases Variants can be used to trace human origins Human Genetic Variation What types of variants

More information

Gene Environment Interaction Analysis. Methods in Bioinformatics and Computational Biology. edited by. Sumiko Anno

Gene Environment Interaction Analysis. Methods in Bioinformatics and Computational Biology. edited by. Sumiko Anno Gene Environment Interaction Analysis Methods in Bioinformatics and Computational Biology edited by Sumiko Anno Gene Environment Interaction Analysis Gene Environment Interaction Analysis Methods in

More information

Outline and learning objectives. From Proteomics to Systems Biology. Integration of omics - information

Outline and learning objectives. From Proteomics to Systems Biology. Integration of omics - information From to Systems Biology Outline and learning objectives Omics science provides global analysis tools to study entire systems How to obtain omics - What can we learn Limitations Integration of omics - In-class

More information

QIAGEN s NGS Solutions for Biomarkers NGS & Bioinformatics team QIAGEN (Suzhou) Translational Medicine Co.,Ltd

QIAGEN s NGS Solutions for Biomarkers NGS & Bioinformatics team QIAGEN (Suzhou) Translational Medicine Co.,Ltd QIAGEN s NGS Solutions for Biomarkers NGS & Bioinformatics team QIAGEN (Suzhou) Translational Medicine Co.,Ltd 1 Our current NGS & Bioinformatics Platform 2 Our NGS workflow and applications 3 QIAGEN s

More information

The first and only fully-integrated microarray instrument for hands-free array processing

The first and only fully-integrated microarray instrument for hands-free array processing The first and only fully-integrated microarray instrument for hands-free array processing GeneTitan Instrument Transform your lab with a GeneTitan Instrument and experience the unparalleled power of streamlining

More information

Network System Inference

Network System Inference Network System Inference Francis J. Doyle III University of California, Santa Barbara Douglas Lauffenburger Massachusetts Institute of Technology WTEC Systems Biology Final Workshop March 11, 2005 What

More information

The Integrated Biomedical Sciences Graduate Program

The Integrated Biomedical Sciences Graduate Program The Integrated Biomedical Sciences Graduate Program at the university of notre dame Cutting-edge biomedical research and training that transcends traditional departmental and disciplinary boundaries to

More information

Bioinformatics Advice on Experimental Design

Bioinformatics Advice on Experimental Design Bioinformatics Advice on Experimental Design Where do I start? Please refer to the following guide to better plan your experiments for good statistical analysis, best suited for your research needs. Statistics

More information

Genomic region (ENCODE) Gene definitions

Genomic region (ENCODE) Gene definitions DNA From genes to proteins Bioinformatics Methods RNA PROMOTER ELEMENTS TRANSCRIPTION Iosif Vaisman mrna SPLICE SITES SPLICING Email: ivaisman@gmu.edu START CODON STOP CODON TRANSLATION PROTEIN From genes

More information

ACCELERATING GENOMIC ANALYSIS ON THE CLOUD. Enabling the PanCancer Analysis of Whole Genomes (PCAWG) consortia to analyze thousands of genomes

ACCELERATING GENOMIC ANALYSIS ON THE CLOUD. Enabling the PanCancer Analysis of Whole Genomes (PCAWG) consortia to analyze thousands of genomes ACCELERATING GENOMIC ANALYSIS ON THE CLOUD Enabling the PanCancer Analysis of Whole Genomes (PCAWG) consortia to analyze thousands of genomes Enabling the PanCancer Analysis of Whole Genomes (PCAWG) consortia

More information

Axiom mydesign Custom Array design guide for human genotyping applications

Axiom mydesign Custom Array design guide for human genotyping applications TECHNICAL NOTE Axiom mydesign Custom Genotyping Arrays Axiom mydesign Custom Array design guide for human genotyping applications Overview In the past, custom genotyping arrays were expensive, required

More information

Multi-omics in biology: integration of omics techniques

Multi-omics in biology: integration of omics techniques 31/07/17 Летняя школа по биоинформатике 2017 Multi-omics in biology: integration of omics techniques Konstantin Okonechnikov Division of Pediatric Neurooncology German Cancer Research Center (DKFZ) 2 Short

More information

Ontologies - Useful tools in Life Sciences and Forensics

Ontologies - Useful tools in Life Sciences and Forensics Ontologies - Useful tools in Life Sciences and Forensics How today's Life Science Technologies can shape the Crime Sciences of tomorrow 04.07.2015 Dirk Labudde Mittweida Mittweida 2 Watson vs Watson Dr.

More information

Microarray Gene Expression Analysis at CNIO

Microarray Gene Expression Analysis at CNIO Microarray Gene Expression Analysis at CNIO Orlando Domínguez Genomics Unit Biotechnology Program, CNIO 8 May 2013 Workflow, from samples to Gene Expression data Experimental design user/gu/ubio Samples

More information

BENG 183 Trey Ideker. Genome Assembly and Physical Mapping

BENG 183 Trey Ideker. Genome Assembly and Physical Mapping BENG 183 Trey Ideker Genome Assembly and Physical Mapping Reasons for sequencing Complete genome sequencing!!! Resequencing (Confirmatory) E.g., short regions containing single nucleotide polymorphisms

More information

Introduction to Next Generation Sequencing (NGS)

Introduction to Next Generation Sequencing (NGS) Introduction to Next eneration Sequencing (NS) Simon Rasmussen Assistant Professor enter for Biological Sequence analysis Technical University of Denmark 2012 Today 9.00-9.45: Introduction to NS, How it

More information

Genome Sequencing Technologies. Jutta Marzillier, Ph.D. Lehigh University Department of Biological Sciences Iacocca Hall

Genome Sequencing Technologies. Jutta Marzillier, Ph.D. Lehigh University Department of Biological Sciences Iacocca Hall Genome Sequencing Technologies Jutta Marzillier, Ph.D. Lehigh University Department of Biological Sciences Iacocca Hall Sciences start with Observation Sciences start with Observation and flourish with

More information

Biotechnology and Genomics in Public Health. Sharon S. Krag, PhD Johns Hopkins University

Biotechnology and Genomics in Public Health. Sharon S. Krag, PhD Johns Hopkins University This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this

More information

Chapter 15 Gene Technologies and Human Applications

Chapter 15 Gene Technologies and Human Applications Chapter Outline Chapter 15 Gene Technologies and Human Applications Section 1: The Human Genome KEY IDEAS > Why is the Human Genome Project so important? > How do genomics and gene technologies affect

More information

CMPS 3110 : Bioinformatics. High-Throughput Sequencing and Applications

CMPS 3110 : Bioinformatics. High-Throughput Sequencing and Applications CMPS 3110 : Bioinformatics High-Throughput Sequencing and Applications Sanger (1982) introduced chaintermination sequencing. Main idea: Obtain fragments of all possible lengths, ending in A, C, T, G. Using

More information

Molecular Cell Biology - Problem Drill 11: Recombinant DNA

Molecular Cell Biology - Problem Drill 11: Recombinant DNA Molecular Cell Biology - Problem Drill 11: Recombinant DNA Question No. 1 of 10 1. Which of the following statements about the sources of DNA used for molecular cloning is correct? Question #1 (A) cdna

More information

SIMS2003. Instructors:Rus Yukhananov, Alex Loguinov BWH, Harvard Medical School. Introduction to Microarray Technology.

SIMS2003. Instructors:Rus Yukhananov, Alex Loguinov BWH, Harvard Medical School. Introduction to Microarray Technology. SIMS2003 Instructors:Rus Yukhananov, Alex Loguinov BWH, Harvard Medical School Introduction to Microarray Technology. Lecture 1 I. EXPERIMENTAL DETAILS II. ARRAY CONSTRUCTION III. IMAGE ANALYSIS Lecture

More information

Corporate Medical Policy

Corporate Medical Policy Corporate Medical Policy Proteogenomic Testing for Patients with Cancer (GPS Cancer Test) File Name: Origination: Last CAP Review: Next CAP Review: Last Review: proteogenomic_testing_for_patients_with_cancer_gps_cancer_test

More information

The 150+ Tomato Genome (re-)sequence Project; Lessons Learned and Potential

The 150+ Tomato Genome (re-)sequence Project; Lessons Learned and Potential The 150+ Tomato Genome (re-)sequence Project; Lessons Learned and Potential Applications Richard Finkers Researcher Plant Breeding, Wageningen UR Plant Breeding, P.O. Box 16, 6700 AA, Wageningen, The Netherlands,

More information

Human SNP haplotypes. Statistics 246, Spring 2002 Week 15, Lecture 1

Human SNP haplotypes. Statistics 246, Spring 2002 Week 15, Lecture 1 Human SNP haplotypes Statistics 246, Spring 2002 Week 15, Lecture 1 Human single nucleotide polymorphisms The majority of human sequence variation is due to substitutions that have occurred once in the

More information

Next-Generation Sequencing. Technologies

Next-Generation Sequencing. Technologies Next-Generation Next-Generation Sequencing Technologies Sequencing Technologies Nicholas E. Navin, Ph.D. MD Anderson Cancer Center Dept. Genetics Dept. Bioinformatics Introduction to Bioinformatics GS011062

More information

Target Enrichment Strategies for Next Generation Sequencing

Target Enrichment Strategies for Next Generation Sequencing Target Enrichment Strategies for Next Generation Sequencing Anuj Gupta, PhD Agilent Technologies, New Delhi Genotypic Conference, Sept 2014 NGS Timeline Information burst Nearly 30,000 human genomes sequenced

More information

Engineering Genetic Circuits

Engineering Genetic Circuits Engineering Genetic Circuits I use the book and slides of Chris J. Myers Lecture 0: Preface Chris J. Myers (Lecture 0: Preface) Engineering Genetic Circuits 1 / 19 Samuel Florman Engineering is the art

More information

SNP GENOTYPING WITH iplex REAGENTS AND THE MASSARRAY SYSTEM

SNP GENOTYPING WITH iplex REAGENTS AND THE MASSARRAY SYSTEM SNP GENOTYPING Accurate, sensitive, flexible MassARRAY System SNP GENOTYPING WITH iplex REAGENTS AND THE MASSARRAY SYSTEM Biomarker validation Routine genetic testing Somatic mutation profiling Up to 400

More information

Sequencing the Human Genome

Sequencing the Human Genome The Biotechnology 339 EDVO-Kit # Sequencing the Human Genome Experiment Objective: In this experiment, DNA sequences obtained from automated sequencers will be submitted to Data bank searches using the

More information

Christoph Bock ICPerMed First Research Workshop Milano, 26 June 2017

Christoph Bock ICPerMed First Research Workshop Milano, 26 June 2017 New Tools for Personalized Medicine *Tools = Assays, Devices, Software Christoph Bock ICPerMed First Research Workshop Milano, 26 June 2017 http://epigenomics.cemm.oeaw.ac.at http://biomedical-sequencing.at

More information

Analytics Behind Genomic Testing

Analytics Behind Genomic Testing A Quick Guide to the Analytics Behind Genomic Testing Elaine Gee, PhD Director, Bioinformatics ARUP Laboratories 1 Learning Objectives Catalogue various types of bioinformatics analyses that support clinical

More information

About Strand NGS. Strand Genomics, Inc All rights reserved.

About Strand NGS. Strand Genomics, Inc All rights reserved. About Strand NGS Strand NGS-formerly known as Avadis NGS, is an integrated platform that provides analysis, management and visualization tools for next-generation sequencing data. It supports extensive

More information

Bio-Reagent Services. Custom Gene Services. Gateway to Smooth Molecular Biology! Your Innovation Partner in Drug Discovery!

Bio-Reagent Services. Custom Gene Services. Gateway to Smooth Molecular Biology! Your Innovation Partner in Drug Discovery! Bio-Reagent Services Custom Gene Services Gateway to Smooth Molecular Biology! Gene Synthesis Mutagenesis Mutant Libraries Plasmid Preparation sirna and mirna Services Large-scale DNA Sequencing GenPool

More information

Product Applications for the Sequence Analysis Collection

Product Applications for the Sequence Analysis Collection Product Applications for the Sequence Analysis Collection Pipeline Pilot Contents Introduction... 1 Pipeline Pilot and Bioinformatics... 2 Sequence Searching with Profile HMM...2 Integrating Data in a

More information

Structural variation. Marta Puig Institut de Biotecnologia i Biomedicina Universitat Autònoma de Barcelona

Structural variation. Marta Puig Institut de Biotecnologia i Biomedicina Universitat Autònoma de Barcelona Structural variation Marta Puig Institut de Biotecnologia i Biomedicina Universitat Autònoma de Barcelona Genetic variation How much genetic variation is there between individuals? What type of variants

More information

Fundamentals of Clinical Genomics

Fundamentals of Clinical Genomics Fundamentals of Clinical Genomics Wellcome Genome Campus Hinxton, Cambridge, UK 17-19 January 2018 Lectures and Workshops to be held in the Rosalind Franklin Pavilion Lunch and Dinner to be held in the

More information

Lecture 8: Sequencing and SNP. Sept 15, 2006

Lecture 8: Sequencing and SNP. Sept 15, 2006 Lecture 8: Sequencing and SNP Sept 15, 2006 Announcements Random questioning during literature discussion sessions starts next week for real! Schedule changes Moved QTL lecture up Removed landscape genetics

More information

Next Gen Sequencing. Expansion of sequencing technology. Contents

Next Gen Sequencing. Expansion of sequencing technology. Contents Next Gen Sequencing Contents 1 Expansion of sequencing technology 2 The Next Generation of Sequencing: High-Throughput Technologies 3 High Throughput Sequencing Applied to Genome Sequencing (TEDed CC BY-NC-ND

More information

High Throughput Sequencing Technologies. J Fass UCD Genome Center Bioinformatics Core Monday June 16, 2014

High Throughput Sequencing Technologies. J Fass UCD Genome Center Bioinformatics Core Monday June 16, 2014 High Throughput Sequencing Technologies J Fass UCD Genome Center Bioinformatics Core Monday June 16, 2014 Sequencing Explosion www.genome.gov/sequencingcosts http://t.co/ka5cvghdqo Sequencing Explosion

More information

Introduction to Bioinformatics

Introduction to Bioinformatics Introduction to Bioinformatics Richard Corbett Canada s Michael Smith Genome Sciences Centre Vancouver, British Columbia June 28, 2017 Our mandate is to advance knowledge about cancer and other diseases

More information

Introduction to BioMEMS & Medical Microdevices DNA Microarrays and Lab-on-a-Chip Methods

Introduction to BioMEMS & Medical Microdevices DNA Microarrays and Lab-on-a-Chip Methods Introduction to BioMEMS & Medical Microdevices DNA Microarrays and Lab-on-a-Chip Methods Companion lecture to the textbook: Fundamentals of BioMEMS and Medical Microdevices, by Prof., http://saliterman.umn.edu/

More information

European Union Reference Laboratory for Genetically Modified Food and Feed (EURL GMFF)

European Union Reference Laboratory for Genetically Modified Food and Feed (EURL GMFF) Guideline for the submission of DNA sequences derived from genetically modified organisms and associated annotations within the framework of Directive 2001/18/EC and Regulation (EC) No 1829/2003 European

More information

Examination Assignments

Examination Assignments Bioinformatics Institute of India H-109, Ground Floor, Sector-63, Noida-201307, UP. INDIA Tel.: 0120-4320801 / 02, M. 09818473366, 09810535368 Email: info@bii.in, Website: www.bii.in INDUSTRY PROGRAM IN

More information

AP Biology Gene Expression/Biotechnology REVIEW

AP Biology Gene Expression/Biotechnology REVIEW AP Biology Gene Expression/Biotechnology REVIEW Multiple Choice Identify the choice that best completes the statement or answers the question. 1. Gene expression can be a. regulated before transcription.

More information

Modern Epigenomics. Histone Code

Modern Epigenomics. Histone Code Modern Epigenomics Histone Code Ting Wang Department of Genetics Center for Genome Sciences and Systems Biology Washington University Dragon Star 2012 Changchun, China July 2, 2012 DNA methylation + Histone

More information

Unit 1 Human cells. 1. Division and differentiation in human cells

Unit 1 Human cells. 1. Division and differentiation in human cells Unit 1 Human cells 1. Division and differentiation in human cells Stem cells Describe the process of differentiation. Explain how differentiation is brought about with reference to genes. Name the two

More information

Introduction to BIOINFORMATICS

Introduction to BIOINFORMATICS Introduction to BIOINFORMATICS Antonella Lisa CABGen Centro di Analisi Bioinformatica per la Genomica Tel. 0382-546361 E-mail: lisa@igm.cnr.it http://www.igm.cnr.it/pagine-personali/lisa-antonella/ What

More information

From Variants to Pathways: Agilent GeneSpring GX s Variant Analysis Workflow

From Variants to Pathways: Agilent GeneSpring GX s Variant Analysis Workflow From Variants to Pathways: Agilent GeneSpring GX s Variant Analysis Workflow Technical Overview Import VCF Introduction Next-generation sequencing (NGS) studies have created unanticipated challenges with

More information

Protein Sequence Analysis. BME 110: CompBio Tools Todd Lowe April 19, 2007 (Slide Presentation: Carol Rohl)

Protein Sequence Analysis. BME 110: CompBio Tools Todd Lowe April 19, 2007 (Slide Presentation: Carol Rohl) Protein Sequence Analysis BME 110: CompBio Tools Todd Lowe April 19, 2007 (Slide Presentation: Carol Rohl) Linear Sequence Analysis What can you learn from a (single) protein sequence? Calculate it s physical

More information

Genetic Engineering & Recombinant DNA

Genetic Engineering & Recombinant DNA Genetic Engineering & Recombinant DNA Chapter 10 Copyright The McGraw-Hill Companies, Inc) Permission required for reproduction or display. Applications of Genetic Engineering Basic science vs. Applied

More information

High Throughput Sequencing Technologies. J Fass UCD Genome Center Bioinformatics Core Monday September 15, 2014

High Throughput Sequencing Technologies. J Fass UCD Genome Center Bioinformatics Core Monday September 15, 2014 High Throughput Sequencing Technologies J Fass UCD Genome Center Bioinformatics Core Monday September 15, 2014 Sequencing Explosion www.genome.gov/sequencingcosts http://t.co/ka5cvghdqo Sequencing Explosion

More information

Genome Assembly Using de Bruijn Graphs. Biostatistics 666

Genome Assembly Using de Bruijn Graphs. Biostatistics 666 Genome Assembly Using de Bruijn Graphs Biostatistics 666 Previously: Reference Based Analyses Individual short reads are aligned to reference Genotypes generated by examining reads overlapping each position

More information

UF Center for Pharmacogenomics. Explanation of Services. UF Center for Pharmacogenomics Services

UF Center for Pharmacogenomics. Explanation of Services. UF Center for Pharmacogenomics Services UF Center for Pharmacogenomics Explanation of Services Services are provided either as a price per sample or price per project, depending on the specific needs of the researcher. Basic a la carte services,

More information

Introduction to NGS Technologies

Introduction to NGS Technologies Introduction to NGS Technologies Ignacio Medina imedina@ebi.ac.uk Project Manager & Senior Software Engineer at EBI Variation European Bioinformatics Institute (EMBL-EBI) European Molecular Biology Laboratory

More information

Bioinformatics. Ingo Ruczinski. Some selected examples... and a bit of an overview

Bioinformatics. Ingo Ruczinski. Some selected examples... and a bit of an overview Bioinformatics Some selected examples... and a bit of an overview Department of Biostatistics Johns Hopkins Bloomberg School of Public Health July 19, 2007 @ EnviroHealth Connections Bioinformatics and

More information

Linguamatics NLP for Electronic Health Records

Linguamatics NLP for Electronic Health Records 1 Linguamatics 2013 Linguamatics NLP for Electronic Health Records 2 Linguamatics 2013 Click Agenda to to edit edit Master Master title style title style Linguamatics and I2E Overview Customer case studies

More information

Predictive and Causal Modeling in the Health Sciences. Sisi Ma MS, MS, PhD. New York University, Center for Health Informatics and Bioinformatics

Predictive and Causal Modeling in the Health Sciences. Sisi Ma MS, MS, PhD. New York University, Center for Health Informatics and Bioinformatics Predictive and Causal Modeling in the Health Sciences Sisi Ma MS, MS, PhD. New York University, Center for Health Informatics and Bioinformatics 1 Exponentially Rapid Data Accumulation Protein Sequencing

More information

CSC Assignment1SequencingReview- 1109_Su N_NEXT_GENERATION_SEQUENCING.docx By Anonymous. Similarity Index

CSC Assignment1SequencingReview- 1109_Su N_NEXT_GENERATION_SEQUENCING.docx By Anonymous. Similarity Index Page 1 of 6 Document Viewer TurnitinUK Originality Report Processed on: 05-Dec-20 10:49 AM GMT ID: 13 Word Count: 1587 Submitted: 1 CSC8313-201 - Assignment1SequencingReview- 1109_Su N_NEXT_GENERATION_SEQUENCING.docx

More information

PCR-based technologies Latest strategies

PCR-based technologies Latest strategies Using molecular marker technology in studies on plant genetic diversity DNA-based technologies PCR-based technologies Latest strategies (DNA sequencing, ESTs, microarrays, DArT, SNPs) Copyright: IPGRI

More information

Introduction to Bioinformatics

Introduction to Bioinformatics Introduction to Bioinformatics Alla L Lapidus, Ph.D. SPbSU St. Petersburg Term Bioinformatics Term Bioinformatics was invented by Paulien Hogeweg (Полина Хогевег) and Ben Hesper in 1970 as "the study of

More information

E2ES to Accelerate Next-Generation Genome Analysis in Clinical Research

E2ES to Accelerate Next-Generation Genome Analysis in Clinical Research www.hcltech.com E2ES to Accelerate Next-Generation Genome Analysis in Clinical Research whitepaper April 2015 TABLE OF CONTENTS Introduction 3 Challenges associated with NGS data analysis 3 HCL s NGS Solution

More information

2. Outline the levels of DNA packing in the eukaryotic nucleus below next to the diagram provided.

2. Outline the levels of DNA packing in the eukaryotic nucleus below next to the diagram provided. AP Biology Reading Packet 6- Molecular Genetics Part 2 Name Chapter 19: Eukaryotic Genomes 1. Define the following terms: a. Euchromatin b. Heterochromatin c. Nucleosome 2. Outline the levels of DNA packing

More information

Exam MOL3007 Functional Genomics

Exam MOL3007 Functional Genomics Faculty of Medicine Department of Cancer Research and Molecular Medicine Exam MOL3007 Functional Genomics Tuesday May 29 th 9.00-13.00 ECTS credits: 7.5 Number of pages (included front-page): 5 Supporting

More information

DNA-Sequencing. Technologies & Devices. Matthias Platzer. Genome Analysis Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)

DNA-Sequencing. Technologies & Devices. Matthias Platzer. Genome Analysis Leibniz Institute on Aging - Fritz Lipmann Institute (FLI) DNA-Sequencing Technologies & Devices Matthias Platzer Genome Analysis Leibniz Institute on Aging - Fritz Lipmann Institute (FLI) Genome analysis DNA sequencing platforms ABI 3730xl 4/2004 & 6/2006 1 Mb/day,

More information

Growing Needs for Practical Molecular Diagnostics: Indonesia s Preparedness for Current Trend

Growing Needs for Practical Molecular Diagnostics: Indonesia s Preparedness for Current Trend Growing Needs for Practical Molecular Diagnostics: Indonesia s Preparedness for Current Trend Dr. dr. Francisca Srioetami Tanoerahardjo, SpPK., MSi Essential Practical Molecular Diagnostics Seminar Hotel

More information

Bioinformatics, in general, deals with the following important biological data:

Bioinformatics, in general, deals with the following important biological data: Pocket K No. 23 Bioinformatics for Plant Biotechnology Introduction As of July 30, 2006, scientists around the world are pursuing a total of 2,126 genome projects. There are 405 published complete genomes,

More information

COURSE OUTLINE. School of Engineering Technology and Applied Science. Biological Technology Industrial Microbiology. Advanced Biotechnology

COURSE OUTLINE. School of Engineering Technology and Applied Science. Biological Technology Industrial Microbiology. Advanced Biotechnology COURSE OUTLINE SCHOOL: School of Engineering Technology and Applied Science DEPARTMENT: Applied Biological and Environmental Science (ABES) PROGRAM: Biological Technology Industrial Microbiology COURSE

More information

Next Generation Sequencing Lecture Saarbrücken, 19. March Sequencing Platforms

Next Generation Sequencing Lecture Saarbrücken, 19. March Sequencing Platforms Next Generation Sequencing Lecture Saarbrücken, 19. March 2012 Sequencing Platforms Contents Introduction Sequencing Workflow Platforms Roche 454 ABI SOLiD Illumina Genome Anlayzer / HiSeq Problems Quality

More information

MRC Stratified Medicine Initiative

MRC Stratified Medicine Initiative MRC Stratified Medicine Initiative Jonathan Pearce Medical Research Council, Translational Programme Manager Pharmacogenetics and Stratified Medicine Network Conference : 14 th January 2015 Stratified

More information