<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/41901?offset=30 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/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 https://bioinformaticsonline.com/bookmarks/view/38908/busca-an-integrative-web-server-to-predict-subcellular-localization-of-proteins Thu, 07 Feb 2019 14:08:11 -0600 https://bioinformaticsonline.com/bookmarks/view/38908/busca-an-integrative-web-server-to-predict-subcellular-localization-of-proteins <![CDATA[BUSCA: an integrative web server to predict subcellular localization of proteins]]> BUSCA (Bologna Unified Subcellular Component Annotator) is a web-server for predicting protein subcellular localization. BUSCA integrates different tools to predict localization-related protein features (DeepSig, TPpred3, PredGPI and ENSEMBLE3.0) as well as tools for discriminating subcellular localization of both globular and membrane proteins (BaCelLo, MemLoci and SChloro).

Address of the bookmark: http://busca.biocomp.unibo.it/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/41504/quartataweb-user-friendly-server-developed-for-polypharmacological-and-chemogenomics-analyses Wed, 01 Apr 2020 10:30:52 -0500 https://bioinformaticsonline.com/bookmarks/view/41504/quartataweb-user-friendly-server-developed-for-polypharmacological-and-chemogenomics-analyses <![CDATA[QuartataWeb: user-friendly server developed for polypharmacological and chemogenomics analyses.]]> Data on protein-drug and protein-chemical interactions are rapidly accumulating in databases such as DrugBank and STITCH. These data usually reflect observed interactions, while the lack of data for a given protein-drug/chemical pair does not necessarily mean the lack of interaction. Indeed, recent studies, both computational and experimental, highlighted the promiscuity of both proteins and small molecules: many drugs have side effects i.e. they target proteins other than those known in public databases; and many proteins bind chemicals other than those known, opening the way to design repurposable drugs, new chemicals, or polypharmacological treatments.

https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa210/5813333

Address of the bookmark: http://quartata.csb.pitt.edu/

]]> Neel https://bioinformaticsonline.com/bookmarks/view/43907/htop-explained Wed, 06 Jul 2022 01:28:09 -0500 https://bioinformaticsonline.com/bookmarks/view/43907/htop-explained <![CDATA[htop explained]]> For the longest time I did not know what everything meant in htop.

I thought that load average 1.0 on my two core machine means that the CPU usage is at 50%. That's not quite right. And also, why does it say 1.0?

I decided to look everything up and document it here.

Address of the bookmark: https://peteris.rocks/blog/htop/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/39272/ansible-simple-agentless-it-automation-that-anyone-can-use Wed, 17 Apr 2019 21:41:04 -0500 https://bioinformaticsonline.com/bookmarks/view/39272/ansible-simple-agentless-it-automation-that-anyone-can-use <![CDATA[ansible: Simple, agentless IT automation that anyone can use]]> Ansible is a universal language, unraveling the mystery of how work gets done. Turn tough tasks into repeatable playbooks. Roll out enterprise-wide protocols with the push of a button. Give your team the tools to automate, solve, and share.

Address of the bookmark: https://www.ansible.com/

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases Wed, 12 Feb 2020 01:16:29 -0600 https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases <![CDATA[Biological databases !]]> Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...

ftp://ftp.ncbi.nih.gov/genomes/

https://hgdownload.soe.ucsc.edu/downloads.html

Address of the bookmark: ftp://ftp.ncbi.nih.gov/genomes/

]]> BioStar https://bioinformaticsonline.com/opportunity/view/43272/bioinformatics-head-bioinformatics-manager-iii-cancer-genomics-research-laboratory-at-frederick-national-laboratory Wed, 18 Aug 2021 00:19:48 -0500 <![CDATA[Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at Frederick National Laboratory]]> Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR). CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

]]> https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software Sun, 08 Jun 2014 10:06:26 -0500 https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software <![CDATA[Ten recommendations for creating usable bioinformatics command line software]]> Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author’s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user’s time, and improve the quality of scientific analyses.

Address of the bookmark: http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

]]> RAJESH DETROJA https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics Thu, 18 Dec 2014 11:05:42 -0600 https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics <![CDATA[Google Genomics]]>

  • Explore genetic variation interactively. Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.

  • Process big genomic data easily. Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.

  • Use Google's infrastructure and big data expertise. Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.

  • Support emerging global standards. Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.

    • Address of the bookmark: https://cloud.google.com/genomics/

    ]]>     Tenzin Paul