PPT-PROTEIN SEQUENCING PRESENTATION OUTLINE

INTRODUCTION PROTEIN SEQUENCING WHY PROTEIN SEQUENCING MATTERS HISTORY STRATEGY SEQUENCING METHODS APPLICATIONS INTRODUCTION PROTEIN Proteins are polymers of amino acid Proteins structure amp function depends upon amino acid sequence. Adam . Kutz. Kern . Walster. The task of sequencing genomes produces massive amounts of data. Traditional data transmission is becoming a bottleneck. Researchers storing data on Hard drives and shipping via . From Swab to Publication. Madison I. Dunitz. 1. , David A. Coil. 1. , Jenna M. Lang. 1. , Guillaume Jospin. 1. , Aaron E. Darling. 2. , Jonathan A. Eisen. 1. UC Davis Genome Center. 1. University of California, Davis; . Learning Objectives. Recap how DNA probes and DNA hybridisation is used to locate specific genes.. Learn how the exact order of nucleotides on a strand of DNA can be determined.. Learn how restriction mapping can be used to determine nucleotide sequences.. Dan . Russell. Overview. Prologue: Assembly and Finishing. The Past: Sanger. The Present: Next-Gen (454, . Illumina. , …). The Future: ? (. Nanopore. , . MinION. , Single-molecule). Overview. Prologue: Assembly and Finishing. Assembly, and Alignment Methods . Andy Nagar. Agenda. Background. Next Generation Sequencing. Sequence Assembly. Sequence Alignment. Traditional Alignment Algorithms. Next Generation Alignment Algorithms. Stefano . Lise. Bioinformatics & Statistical Genetics (BSG) Core. The . Wellcome. Trust Centre for Human Genetics (WTCHG), Oxford. Email: stefano@well.ox.ac.uk. Outline. Human genetic variation in health and disease. :. informatics & software aspects. Gabor T. Marth. Boston College Biology . Department. BI543 Fall 2013. January 29, 2013. Traditional DNA sequencing. Genetics of living organisms. DNA. Chromosomes. INTRODUCTION . The most commonly used technology until a few years ago – BAC. WHOLE GENOME SEQUENCING. ADVANTAGES OF WGS. Utility of next – gen sequence reads . The next-generation platforms are effecting a complete paradigm shift, not only in the organization of large-scale data production, but also in the downstream bioinformatics, IT, and LIMS support required for high data utility and correct interpretation.. Mayo/UIUC Summer . C. ourse in Computational Biology. Session Outline. Genome sequencing. Schematic overview of genome assembly. (a) DNA is collected from the biological sample and sequenced. (b) The output from the sequencer consists of many billions of short, unordered DNA fragments from random positions in the genome. (c) The short fragments are compared with each other to discover how they overlap. (d) The overlap relationships are captured in a large assembly graph shown as nodes representing . A I . Bhat. Indian Institute of Spices Research. Calicut. DNA sequencing. Chain termination method . (. Sangers. . et a. l., 1977): In this method, the sequence of a single stranded DNA molecule is determined by enzymatic synthesis of complementary polynucleotide chains, these chains terminating at specific nucleotide positions.. Ion . Mandoiu. Computer Science and Engineering Department. University of Connecticut. Outline. Background on high-throughput sequencing. Identification of tumor-specific . epitopes. Estimation of gene and . Making . Your Applications Virtual . Chris Green. Program Manager. Microsoft Corporation. SESSION CODE: . VIR320. Required Slide. Session Objectives And Takeaways. Understand the sequencing process. See best practices for . (very) large datasets. 5/24/18. Goals for the course. Understand how next-generation sequencing technologies are used in biomedical research. Learn how to use publicly available databases/websites to find specific information about genes. How we obtain the sequence of nucleotides of a species. …ACGTGACTGAGGACCGTG. CGACTGAGACTGACTGGGT. CTAGCTAGACTACGTTTTA. TATATATATACGTCGTCGT. ACTGATGACTAGATTACAG. ACTGATTTAGATACCTGAC. TGATTTTAAAAAAATATT….