'Genbank' diaporamas de présentation

Learning Science/Mathematics by Doing Science/Mathematics

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Lecture 7

Bioinformatics. Lecture 7. Types of databases. Principles of organizations and functioning. Sequence formats. Conversion of one sequence format to another. Database search. FASTA, BLAST. . Protein and DNA/RNA Databases.

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Robert Hanner, PhD Database Working Group Chair, CBOL Global Campaign Coordinator, FISH-BOL Associate Director, Canadian

Potencials of DNA Barcoding in South America 19-20 March 2007. Robert Hanner, PhD Database Working Group Chair, CBOL Global Campaign Coordinator, FISH-BOL Associate Director, Canadian Barcode of Life Network Biodiversity Institute of Ontario, University of Guelph, Canada.

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Chapter 7 Bioinformatics

Chapter 7 Bioinformatics. ????????. 1990 ?? : ??????? 1982 ? : ??????? (NIH) ??? GenBank 1988 ? : ?? NCBI (National Center for Biotechnology Information). Definition of Bioinformatics.

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Using Escherichia coli and Saccharomyces cerevisiae as Model Systems for Teaching Genomics to Undergraduates

Using Escherichia coli and Saccharomyces cerevisiae as Model Systems for Teaching Genomics to Undergraduates. Breaking the silence: researching the SIR2 gene family. Dr. Myra K. Derbyshire and undergraduate students Mount Saint Mary's College, Emmitsburg, Maryland.

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Reading the blueprint of life

Reading the blueprint of life. DNA sequencing . Introduction. The blueprint of life is contained in the DNA in the nuclei of eukaryotic cells and simply within prokaryotic cells.

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What does mathematics contribute to bioinformatics?

What does mathematics contribute to bioinformatics?. Winfried Just Department of Mathematics Ohio University. A new microscope and a new physics. In 2004 PLoS Biology published a paper by Joel E. Cohen Mathematics Is Biology's Nex t Microscope , Only Better;

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Linking Data from ScienceDirect Articles

Linking Data from ScienceDirect Articles. Presented by: IJsbrand Jan Aalbersberg Hannover, DataCite Meeting Date: June 8, 2010. Linking to & from Data from & to ScienceDirect Articles. Presented by: IJsbrand Jan Aalbersberg Hannover, DataCite Meeting Date: June 8, 2010.

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The Cloning of Atrolysin A from Crotalus atrox

The Cloning of Atrolysin A from Crotalus atrox. By AJ Goos & Kayla Ohrt. Atrolysin A. C omes from Crotalus atrox which is the Western Diamondback Rattlesnake. We have attained a tissue sample from the Kentucky Reptile Zoo.

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Introduction to the Dryad Digital Repository

Introduction to the Dryad Digital Repository. A nonprofit repository for data underlying the international scientific and medical literature. April 2013. 1. The End To make data archiving and reuse standard within scientific communication. The Means

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Researchers and Funders: Tales of Challenges and Change

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BLAST & GenBank

BLAST & GenBank. Jeremy Badgett. Using computers for Genomic reference and research. Computers offer Biologist a tool to use in their ever expanding kit of Molecular techniques

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Virtual Bioinformatics

Martti Tolvanen & Bairong Shen University of Tampere. Virtual Bioinformatics. Methods to analyse, store, search, retrieve and represent biological data by computers /in computers massive amounts of data: databases extracting information and knowledge from "raw" data

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Bioinformatics Chem 434

Bioinformatics Chem 434. Dr. Nancy Warter-Perez Computer Engineering Dr. Jamil Momand Chemistry & Biochemistry. What is Bioinformatics?. Fredj Tekaia at the Institut Pasteur offers this definition of bioinformatics:

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DNA PROFILING

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Mycoplasma Genitalium

Mycoplasma Genitalium. Genome Project. Sharndeep Kaur. Genome. Name: Mycoplasma genitalium G-37 Kingdom: Bacteria Intermediate 1. Firmicutes 2. Bacillus/Clostridium group 3. Mollicutes 4.Mycoplasmataceae Genus: Mycoplasma Species: genitalium Strain G-37.

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Bioinformatics

Bioinformatics. Ayesha M. Khan 20/2/12. Introduction to databases. If we are to derive the maximum benefit from the deluge of sequence information, we must deal with it in a concerted way by doing the following: Establish Maintain Disseminate ? the information contained in databases.

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( kD )

OsAPXs-IR29. M. 1. 1. 1. 2. 2. 2. ( kD ). 75. 50. 37. 25. 20. 15. Fig. A1 Verification of specificities of polyclonal antibodies between OsAPX1-IR29 and OsAPX2-IR29. Coomassie. anti-APX1. anti-APX2. 0. 1. 2. 3 (kb). OsAPX1. (3,015 bp ). 20 bp. OsAPX1-IR29.

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Data Mining Tools for Curation of the Human Metabolome Database

Building the MetaboCards.

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