26 nov2013seminar
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This document summarizes information from several genomics and bioinformatics research groups and projects. It discusses: - The ENCODE project and its focus areas including databases, data mining, visualization, transcriptomics, alternative splicing, sequencing pipelines, comparative genomics, epigenomics, and population genomics. - Tools and databases for variant analysis from the 1000 Genomes Project and FORGE Consortium. - The Genome Modeling System from The Genome Institute at Washington University for analyzing TCGA, ICGC, 1000 Genomes, and PCGP data. - Using RNA-seq technology to reveal the transcriptome and methods for isolating translated mRNA. - Resources for analyzing Human Microbiome Project data
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2. Secondary analysis maps reads to a reference genome to produce SAM/BAM files and calls variants to produce VCF files.
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Qi liu 08.08.2014
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Assays for protein dna interactions
This presentation talks about 3 ways to detect protein DNA interactions - Chromatin immunoprecipitation (ChIP), yeast one system (Y1H), and some In-silico tools, in brief. Animations might not work.
Informal presentation on bioinformatics
Here are some suggestions for open online bioinformatics lectures and courses from famous universities:
- MIT OpenCourseWare has free bioinformatics course materials and videos from MIT courses.
- edX has massive open online courses (MOOCs) in bioinformatics from universities like Harvard, Berkeley, MIT. Some are free to audit.
- Coursera has bioinformatics courses from top universities like Johns Hopkins, University of Toronto, Peking University.
- YouTube has full lecture videos from bioinformatics courses at universities like Stanford, UC San Diego, University of Cambridge.
- Khan Academy has introductory bioinformatics lectures on topics like sequence alignment, gene finding, protein structure.
- EMBL-
20140710 1 day1_nist_ercc2.0workshop
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This document summarizes the assembly of the Phytophthora ramorum genome using PacBio long reads. It describes the error correction and assembly process for two P. ramorum strains, Pr102 and ND886. For Pr102, multiple assembly versions (V1-V5) were generated using different error correction and assembly protocols. The V5 assembly resulted in fewer scaffolds, larger size, and fewer gaps compared to previous versions. For ND886, PacBio reads were error corrected and assembled. Both assemblies captured more repetitive elements compared to previous Sanger-based assemblies. Gene predictions were also improved in number and quality.
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This document outlines the schedule and topics for a class on SNPs and gene expression. The class will have 6 sessions, with groups of 2 students presenting on selected papers in each session. Topics to be covered include an introduction to terminology like forward and reverse genetics; how often SNPs occur in the general population; databases of SNPs like dbSNP and haplotype projects like HapMap; gene expression analysis using microarrays; and experimental design, data analysis, and visualization techniques for microarray data. Papers for each group to present on are also listed. The next class will involve discussing one particular paper on SNPs.
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This document discusses the development of a new lightweight version of the Eumicrobedb database called Transcriptomicsdb. The new version reduces the database size and dependencies by decreasing the number of tables and views from 329 to 37 and 127 to 18 respectively in Eumicrobedb-Oracle. It also improves query time from 10 seconds to 1.2 seconds and reduces genome upload time from 12-14 hours to 2 hours. The document describes how the new database will help laboratories with limited hosting facilities to store and analyze sequencing data. It notes that the source code will soon be released to allow others to replicate the database without needing an Oracle license and various bioinformatics packages.
Lecture7,8
Pharmacogenetics refers to how genetic differences affect individuals' responses to drugs. It influences different metabolic pathways and is responsible for over 106,000 deaths annually in the US. Certain genetic mutations can determine how effectively drugs are processed in the body. Microarrays are DNA chips that allow researchers to analyze large numbers of genes simultaneously, helping to identify genetic factors influencing drug responses and diseases.
Lecture5,6
Many diseases are caused by genetic mutations. Over 4000 diseases are linked to altered genes, including heart disease, cancer, autoimmune disorders, and diabetes. Specific mutations are associated with certain cancers, such as mutations in the RB1 and BRCA1 genes which can lead to retinoblastoma and breast cancer respectively. Large-scale projects like the Cancer Genome Atlas and ENCODE project aim to catalogue all mutations in cancers and across the human genome. Immunogenetics research examines the genetic links to immune-related disorders. The HapMap and 1000 Genomes projects studied genetic variants and helped map human genetic diversity.
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The document discusses the history and process of genome sequencing, as well as several important genome projects such as the Human Genome Project. It also examines the role of databases in genomic research, describing different types of biological databases and how they can be used to store, organize, and retrieve genomic data. Finally, it provides examples of popular databases and genome browsers that are widely used by researchers.
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Tyler presentation
This document discusses oomycete genomics research that has been funded by the National Science Foundation, USDA CSREES, and USDA NIFA from 2007-2016. Over 120 destructive oomycete pathogen species have been studied, including the genera Phytophthora and Hyaloperonospora. The genomes of several Phytophthora species have been sequenced, with efforts underway to sequence all species through a new initiative with BGI. Comparisons between sequenced oomycete genomes show both conserved and unique genes. Effector genes associated with disease are located in repeat-rich regions of genomes and have expanded through evolution.
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Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
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Chapter 6
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Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
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Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Changes in vegetation cover refer to variations in the distribution, composition, and overall
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26 nov2013seminar
- 4. Databases Data Mining Visualization and Curation. Transcriptomics, Alternative Splicing and Gene prediction. Sequencing Pipeline and Assembly. Comparative and Evolutionary Genomics Epigenomics and Non-coding Genome Population and personal Genomics
- 5. Medsavant: integrated solution for storage, annotation, filtration, prioritization and visual inspection of variants. #1000 genome project; #FORGE consortium 425 individuals Mendel App Finding of Rare disease genes
- 6. The Genome Institute at Washington University – Genome Modelling System. ◦ ◦ ◦ ◦ TCGA ICGC (Int. Cancer Genome Consortium) 1000 genomes project PCGP (Pediatric Cancer Genome Project) https://github.com/genome/gms
- 7. RNA-seq (RNA Sequencing), also called "Whole Transcriptome Shotgun Sequencing" [1] ("WTSS"), is a technology that uses the capabilities of next-generation sequencing to reveal a snapshot of RNA presence and quantity from a genome at a given moment in time.[2]
- 8. Mario Stanke at Institute of Mathematics and computer science, Germany ◦ Synteny based approach in gene prediction Method for isolating Ribosome bound mRNA ◦ Tufts University, Boston, MA. ◦ Specifically can tell which mRNAs are actually translated.
- 9. Data Analysis and coordination center (DACC). ◦ For HMP data analysis ◦ CloVR virtual machine ◦ http://www.Hmpdacc.org/tools_protocols/tools_pr otocols.php In silico genome subtraction tool ◦ MGC (Microbial Genome Comparison tool) – A stand alone Java package
- 10. Studying co-expression network with micrarrays and RNAseq ◦ 3320 microarray experiments vs 813 RNAseq samples with 8 datasets Major biological difference Hundreds and thousands of samples necessary to build a robust RNAseq dataset RNAseq co-expression analysis necessary.
- 11. RNAseq Analysis pipeline using Ion Torrent data. ◦ Tophat-cufflink ◦ STAR-cufflink ◦ TMAP-cufflink Expression levels are zero for STAR, TMAP aligners •Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR: STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29:15-21. PubMed Abstract | Publisher Full Text Return to text •TMAP is a short read aligner specifically tuned for data from the Ion Torrent PGM
- 12. •FPKM vs RSEM and cufflink •Lior Pachter @lpachter1 Nov @konrad_jk @tuuliel @joe_pickrell @yarbsalocin I'm sure RSEM, Sailfish, and many other tools can handle it as well. •http://liorpachter.wordpress.com /seq/ RNAseq Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNAseq. Nat. Methods 5, 621– 628 (2008). ICEseq
- 13. Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol. 2013 Jan;31(1):46-53. doi: 10.1038/nbt.2450. Epub 2012 Dec 9. PubMed PMID: 23222703. Trapnell, C. et al. Transcript assembly and quantification by RNA-seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515(2010). Dissects the difference between a gene and a transcript – emphasizes on differential expression in isoform in a given condition. RPKM vs FPKM (# of mapped reads)/(length of transcript in kilo base)/(million) (# of fragments)/(length of transcript in kilo base)/(million)
- 15. SAILFISH Sailfish: Alignment-free Isoform Quantification from RNA-seq Reads using Lightweight Algorithms bio.math.berkeley.edu/eXpress/simdata RSEM or eXPRESS
- 16. A -> I editing -> sequenced as Guanine ◦ Mapping to genome may correct this, but how to distinguish this from SNP? Adapted ICE (Inosine Chemical Erasing) using Cyanoethylation. Computational pipeline to analyze this.
- 17. IICB features in Omics map… www.omicsmaps.com
- 20. We created a virtual machine….. Akash Gupta Arijit Panda Subhadeep Das Neha Sanghi Madhu C. Deeksha Singh Arpita Ghorai http://front.math.ucdavis.edu/ arXiv