<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/41009?offset=10 https://bioinformaticsonline.com/bookmarks/view/26322/liftover Mon, 08 Feb 2016 15:45:03 -0600 https://bioinformaticsonline.com/bookmarks/view/26322/liftover <![CDATA[liftover]]> Convenient conversions between genome assemblie. The liftover package makes it easy to remap genomic coordinates to a different genome assembly.

More at https://github.com/aaronwolen/liftover

https://www.bioconductor.org/help/workflows/liftOver/

Address of the bookmark: https://github.com/aaronwolen/liftover

]]> Jitendra Narayan https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments Fri, 13 May 2016 05:25:26 -0500 https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments <![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]> Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.

Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs.

You can find the manual here.
Download the latest source code from here.
Stable versions can also be downloaded from the Broad Institute's web site.

An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is here.

If you use Satsuma in your research, please cite:
Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alföldi, J., Di Palma, F., & Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51.

Tutorial at http://evomics.org/learning/genomics/satsuma/

Address of the bookmark: http://satsuma.sourceforge.net/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab Fri, 30 Jun 2017 08:48:26 -0500 https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab <![CDATA[DIYA: a bacterial annotation pipeline for any genomics lab]]> DIY Genomics is an open source bioinformatics consortium intended to bring a collection of tools and libraries into the hands of small scale genomics labs for the process of sequence assembly and annotation. Projects include DIYA, MGAP, CRISPR, and DIYGV

http://gmod.org/wiki/Diya

Address of the bookmark: https://sourceforge.net/projects/diyg/

]]> Jit https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2 Wed, 22 Aug 2018 22:10:56 -0500 https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2 <![CDATA[ComparativeGenomics Exercise2]]> COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP  @ cbs.dtu.dk

Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf

]]> Neel https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources Tue, 28 Jun 2022 04:08:06 -0500 https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources <![CDATA[List of comparative genomics resources !]]>

Compare structural and functional annotations of proteins between sequenced genomes.

View AREs in the human transcriptome and study the comparative genomics of AREs in model organisms.

Find information about orthologous genes in prokaryotes.

Search for publicly available QTL data on livestocks and animal species.

Find information about bovine genomics data.

A multi-organism web-based resource system designed to easily retrieve, correlate and interpret data across species.

A database resource of developmentally associated conserved non-coding elements.

Delineate conserved non-coding blocks from upstream regions of putative orthologous gene pairs from man, mouse, rat, fugu, Mus musculus, Danio rerio, and zebrafish.

Find coexpressed gene lists and networks in human and mouse.

Construct phylogenetic tree of microorganisms based on oligopeptide content of their complete proteomes.

A novel database server that classifies GenBank's dbEST (database of expressed gene sequences) libraries and removes contaminants.

Find information about the ancestral relationship between genes.

Provides an overview of the genomic organization of microRNAs and extent of conservation during evolution in different metazoan species.

Conduct comparative biometric analysis of chromosomes of different organisms.

Search for Indices of gene and transcripts in human and mouse.

Search and compare 12 new and old Drosophila genomes.

Access to whole genome alignments of human, mouse, rat and fish sequences.

Find eukaryotic paralog/paralogon information.

Analyze the evolutionary process of overlapping genes when comparing different species.

The first publicly available system reported to handle inter-species gene mention normalization.

A web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes.

Visualize gene indices of human, mouse, Arabidopsis, Zebrafish, Drosophila and Sheep.

Find information about mutated mouse genes.

A data management and analysis system for metagenomes

Search for influenza sequence, vaccine, and drug resistance information.

LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal models for their research.

The missing link between multi-species full genome comparisons and functional analysis.

Conduct comparative analysis of completely sequenced microbial genomes.

A biologist-centric software for evolutionary analysis of DNA and protein sequences.

Conduct single nucleotide polymorphisms diversity measurements among homologous sequences from the Mammalia class.

Find information about 1000s of microbial genomes.

A database dedicated to the study of genome conservation.

Explore orthologous relations across 352 complete genomes.

Browse complete genomes in several clades.

A database of orthologous genomic markers for placental mammal phylogenetics.

Conduct genome wide functional and structural analysis.

Conduct genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes.

Compare phenotypes of a given gene or gene set in different model organisms.

Phylemon is a web server that integrates a selected suite of more than 20 different tools from the most popular stand-alone programs of phylogenetic and evolutionary analysis.

Use this database to see where in the evolution some phylogenetic lineages were started, and over which species they were contained.

Search for genomic information on nematode satellite species Pristionchus pacificus.

Find information about related protein sequences.

Database hosting genomics and post-genomics data from multiple protozoans.

A database of pseudogene families based on the protein families from the Pfam database.

Find genomic information about mammals.

Find information about predicted regulons in prokaryotic transcription regulation.

Perform systematic comparison of proteome data among species.

A comparative map viewer dedicated to the biology of the Solanaceae family.

Analyze data from functional analysis on fragmented microbial genetic material.

Visualize and explore comparative genomic hybridization data sets.

Search for genome-wide annotations of regulatory sites in yeast and prokaryotes genomes.

Search for information on adaptive evolution in gene families of higher plants and chordate.

Generate graphical maps of circular genomes that show sequence features, base composition plots, analysis results and sequence similarity plots.

Conduct a comprehensive analysis of genes and genomes.

An interactive online poster presentation on the Macaque genome, including high-quality images, video clips, and Web resources

Search for annotated genetic information of expressed sequence tags (ESTs) in different eukaryotic organisms.

Find mapping and expression information for a unigene cluster (ESTs and full-length mRNA sequences organized into clusters that each represent a unique known or putative gene)

A public online resource for identifying or designing 'universal' overgo-hybridization probes from conserved sequences that can be used to efficiently screen one or more genomic libraries from a designated group of species.

Comprehensive suite of programs and databases for comparative analysis of genomic sequences.

Find metabolic networks and phylogenomic information on a taxonomically diverse range of eukaryotes.

]]> Shruti Paniwala https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer Wed, 11 Feb 2015 04:59:57 -0600 https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer <![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]>

Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'

Abstract

Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.

Webinar Details


Sessions

San Francisco Time
(PST)

Tokyo Time
(GMT+09:00)

Berlin Time
(GMT+01:00)

Mumbai Time
(GMT+05:30)

Session 1

25 Feb 
12:30 AM

25 Feb 
5:30 PM

25 Feb 
9:30 AM

25 Feb 
2:00 PM

Session 2

25 Feb 
9:00 AM

26 Feb
2:00 AM

25 Feb 
6:00 PM

25 Feb 
10:30 PM

Register here: http://www.strand-ngs.com/webinar_registration

About Speaker:

Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.

Please feel free to contact us 24/5, for availing free online training or if you have any questions.

Email: sales@strandngs.com

Phone (USA): 1-800-752-9122

Phone (ROW): +1-650-353-5060

 

]]> Yeshodari https://bioinformaticsonline.com/opportunity/view/43227/project-associate-i-project-associate-ii-senior-project-associate-igib Thu, 05 Aug 2021 16:11:32 -0500 <![CDATA[Project Associate-I | Project Associate-II | Senior Project Associate @ IGIB]]> Experience in Next Generation Sequencing (NGS) application and interest in Genomics/ Clinical / Translational Applications. OR Good computational programming skills and deep interest in working on interface of Genomics and Clinical application.

Project Scientist-I
Experimental / Computation analysis experience in highthroughput genomics/ clinical application.

Project Manager
Experience in handling large biological projects involving high-throughput genomics/ clinical application.

Scientific Administrative Assistant
Lab Work.

More at https://vinodscaria.genomes.in/positionsopen

]]> https://bioinformaticsonline.com/opportunity/view/18385/biinformamatics-lead-at-google-life-sciences Fri, 17 Oct 2014 02:24:55 -0500 <![CDATA[Biinformamatics Lead at Google Life Sciences]]> Google Life Sciences is recruiting a technical lead with experience in bioinformatics and clinical bioinformatics, including for biomarker discovery projects such as the Baseline study.

Responsibilities

Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.
Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.
Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.
Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.
Create scientifically rigorous visualizations, communications, and presentations of results.

Reference @ https://www.google.com/about/careers/search#!t=jo&jid=62095001

]]> https://bioinformaticsonline.com/news/view/41956/blast-on-docker-google-cloud-amazon-cloud Thu, 09 Jul 2020 02:57:11 -0500 https://bioinformaticsonline.com/news/view/41956/blast-on-docker-google-cloud-amazon-cloud <![CDATA[Blast on Docker, Google Cloud, Amazon Cloud]]> As announced in a previous post, we offer a Docker version of NCBI BLAST+ that you can use locally or on the Google Cloud where we have pre-loaded BLAST databases.  We are happy to announce that the same functionality is now available on the Amazon Cloud.  In addition, we now offer 23 different BLAST databases on each cloud platform.

As mentioned before, working with BLAST+ in Docker and the cloud has several advantages:

  • Docker manages installation and maintenance of the BLAST programs and databases.
  • Docker makes it is easier to integrate BLAST with other tools in your pipelines.
  • NCBI BLAST databases are pre-loaded now on the both the Google Cloud and Amazon Cloud, providing fast access.

You can also use the BLAST+ Docker image on any Docker-enabled platform, such as another cloud platform or on your local computer.

See the  BLAST+ in the Cloud and  database information documentation to get started.

If you have any questions, please email us at blast-help@ncbi.nlm.nih.gov

Source:Dave Arndt

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation Mon, 29 May 2017 05:39:29 -0500 https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation <![CDATA[dbCAN: a web server and DataBase for automated Carbohydrate-active enzyme ANnotation]]> dbCAN is a web server and DataBase for automated Carbohydrate-active enzyme ANnotation, funded by the BioEnergy Science Center of the DOE. Similar resources on the web include CAZy database and CAT. All data in dbCAN are generated based on the family classification from CAZy database while it has the following unique features compared with CAZy database and CAT:

  • dbCAN provides the capability of automated and comprehensive CAZyme annotation of a given genome submitted by the user;
  • dbCAN provides an explicitly defined signature domain for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced genomes;
  • dbCAN provides the most complete set of metagenomic CAZyme genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;
  • dbCAN provides a subfamily classification of the existing CAZyme families based on sequence similarities;
  • dbCAN make all pre-computed data freely available to the public, including sequence alignments, hidden markov models (HMMs) and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.

dbCAN is updated regularly when CAZy database created new families based on latest literature.

Address of the bookmark: http://csbl.bmb.uga.edu/dbCAN/index.php

]]> Jit