<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/26629?offset=1420 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/20437/wuxi-has-acquired-nextcode-health Mon, 19 Jan 2015 08:17:35 -0600 https://bioinformaticsonline.com/news/view/20437/wuxi-has-acquired-nextcode-health <![CDATA[WuXi has acquired NextCODE Health]]> Shanghai, China-headquartered pharmatech company WuXi (NYSE: WX) has acquired NextCODE Health, a genomic analysis and bioinformatics company based in the USA.

The acquisition was made for $65 million in cash, and WuXi plans to merge its genome center with NextCODE Health to form a new company, WuXi NextCODE Genomics. The business will be headquartered in Shanghai and have operations in Cambridge, Massachusetts, and Reykjavik, Iceland.

With the huge unmet medical needs in diseases with a genetic component and the rapid advances in genomics and bioinformatics, now is the right time for WuXi to make a strategic investment in this field, and NextCODE is the right partner. This new venture of WuXi NextCODE Genomics will create important new genomic and bioinformatic products and services to help make personalized treatment and medicine a reality.  It will also enable doctors to provide better treatments to patients.

]]> Pranjali Yadav https://bioinformaticsonline.com/blog/view/44401/bioinformatics-tools-for-phylogeny Mon, 06 Nov 2023 03:09:59 -0600 https://bioinformaticsonline.com/blog/view/44401/bioinformatics-tools-for-phylogeny <![CDATA[Bioinformatics Tools for Phylogeny !]]> Direct access to the individual tools available on this server.

Multiple Alignment:Phylogeny:Tree viewers:Utilities:
MUSCLE PhyML TreeDyn Gblocks
T-Coffee / 3DCoffee TNT Drawgram Jalview
ClustalW BioNJ Drawtree Readseq
ProbCons MrBayes ATV (A Tree Viewer) Built-in converter
]]> BioStar https://bioinformaticsonline.com/bookmarks/view/35057/ectools-long-read-correction-and-other-correction-tools Fri, 05 Jan 2018 04:02:22 -0600 https://bioinformaticsonline.com/bookmarks/view/35057/ectools-long-read-correction-and-other-correction-tools <![CDATA[ECTOOLS: Long Read Correction and other Correction tools]]> Long Read Correction and other Correction tools

This package is a loose collection of scripts. To run the correction
routine see the section below. Descriptions of the other scripts
are at the bottom of this file.

Contact: gurtowsk@cshl.edu

In short, the correction algorithm takes as input the unitigs from a short read assembly and uses them to correct long read data. More background information for the algorithm can be found:
http://schatzlab.cshl.edu/presentations/2013-06-18.PBUserMeeting.pdf

Address of the bookmark: https://github.com/jgurtowski/ectools

]]> Jit https://bioinformaticsonline.com/opportunity/view/20677/postdoctoral-researcher-at-department-of-biotechnology-catholic-university-of-daegu-kyungsan-kyungbuk-south-korea Thu, 29 Jan 2015 12:11:16 -0600 <![CDATA[Postdoctoral Researcher at Department of Biotechnology, Catholic University of Daegu, Kyungsan, Kyungbuk, South Korea.]]> Applications are invited from Indian nationals for a Post Doctoral position at Molecular Medical Laboratory, Department of Biotechnology, Catholic University of Daegu, Kyungsan, Kyungbuk, South Korea.

Qualification required: PhD in Life Sciences/ Molecular Biology/ Bioinformatics or related discipline.

Desirable Qualification:

1. Candidates having experience in molecular biology techniques and must be well versed with bioinformatics tool or expert in relevant fields will be preferred.
2. The candidate should have good communication skill, knowledge about designing experiments and analyzing data.
3. Sense of initiative, autonomy, organization and thoroughness, good relation qualities.
Remuneration: 2000USD per month.

Last date of submitting the complete applications furnishing Bio-data is 10th February, 2015.

Interested candidates should send their resume including all personal as well as academic details to the principal investigator Prof Seung-Won Park (email:microsw@cu.ac.kr)

The shortlisted candidates will be intimated within February 2015.

]]> https://bioinformaticsonline.com/pages/view/36842/gap-filling-or-contigs-extensions-tools Fri, 01 Jun 2018 08:07:32 -0500 https://bioinformaticsonline.com/pages/view/36842/gap-filling-or-contigs-extensions-tools <![CDATA[Gap filling or Contigs extensions tools !]]> There are many tools to perform gap filling using Illumina short reads, for example "GapFiller: a de novo assembly approach to fill the gap within paired reads" or "Toward almost closed genomes with GapFiller". There are also some tools like GAPresolution that can help to perform local re-assemblies using 454 reads. We used GAPresolution but it is not a very good software, it is useful only in some specific situations.

Take a look at the PRICE software from the DeRisi lab. Its meant to do something very similar. http://derisilab.ucsf.edu/index.php?page=software

You could also look at SSPACE (http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/sspacev12/), ATLAS tools (http://www.hgsc.bcm.tmc.edu/content/bcm-hgsc-software), and SCARPA (http://compbio.cs.toronto.edu/hapsembler/scarpa.html).

See the PAGIT protocol: http://www.sanger.ac.uk/resources/software/pagit/

In particular, take a look at the IMAGE tool: http://genomebiology.com/2010/11/4/R41

Also SOAPdenovo has ha function for scaffolding. Not sure about ABYSS

Here there is a useful explanation of several tools.

https://bioinformaticsonline.com/search?q=scaffolding&entity_type=object&entity_subtype=bookmarks&offset=0&search_type=entities

I could be wrong, but the above answers to your hypothetical scenario appear to miss the point that you aren't interested in assembling the full genome, just the 100 kb part you're interested in. I suggest the following algorithm:

1. Start with the initial assembly C0 of the contigs you have identified as overlapping your region of interest, and the set S of reads those contigs contain. Let C = C0.

2. Repeat:
a. Identify paired-end reads (not in C) for which one or both ends align within, or extending, contigs in C.
b. Identify unpaired reads that align extending these new paired-end reads.
c. Construct a new assembly C' from C and the new reads identified in (a) and (b).
d. Trim C' so it does not extend more than 100 kb to either end of C0. Set C = C'.
e. Let S' denote the reads that contribute to C'. If S' does not contain any reads not present in S, stop. Otherwise, Set S = S'.

3. If you don't have a complete assembly of the region of interest, generate an STS for each end of each contig, probe a library for clones including these STSes, subclone these clones into a paired-end sequencing vector, and generate paired-end reads for this library; then try steps (1) and (2) again, adding these new sequencing reads to what you had before.

4. If your average sequencing depth for the region of interest exceeds 25 or so without filling all gaps, it is likely that the remaining gaps represent sequences that are not getting cloned in your sequencing vectors. Try different sequencing vectors.

]]> Rahul Nayak https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly Tue, 22 Jan 2019 09:39:02 -0600 https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly <![CDATA[List of tools frequently used while genome assembly]]> List of tools frequently used while genome assembly:

I have used the following assemblers

I have used the following mappers

I have used the following polishing tools

I have used the following tools to assess genome assembly characteristics

If you have any ideas or superior tools we have missed please let us know in the comments.

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/42570/breeding-insight Wed, 06 Jan 2021 19:49:21 -0600 https://bioinformaticsonline.com/bookmarks/view/42570/breeding-insight <![CDATA[Breeding Insight]]> Breeding Insight at Cornell University will leverage recent improvements in genomics and open source informatics components, and in partnership with small breeding programs, will enable these programs to harness  powerful digital tools to accelerate their genetic gains

Breeding Insight is funded by the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) through Cornell University. The USDA ARS delivers scientific solutions to national and global agricultural challenges. As a global leader in agricultural discovery through scientific excellence, ARS is committed to delivering cutting-edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well-being of all people; sustaining our nation’s agroecosystems and natural resources; and ensuring the economic competitiveness and excellence of our agriculture.

Address of the bookmark: https://www.breedinginsight.org/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43364/ragtag-a-collection-of-software-tools-for-scaffolding-and-improving-modern-genome-assemblies Sat, 11 Sep 2021 00:28:14 -0500 https://bioinformaticsonline.com/bookmarks/view/43364/ragtag-a-collection-of-software-tools-for-scaffolding-and-improving-modern-genome-assemblies <![CDATA[RagTag: a collection of software tools for scaffolding and improving modern genome assemblies]]> RagTag is a collection of software tools for scaffolding and improving modern genome assemblies. Tasks include:

Address of the bookmark: https://github.com/malonge/RagTag

]]> Jit https://bioinformaticsonline.com/news/view/21241/pacman Mon, 16 Feb 2015 12:15:17 -0600 https://bioinformaticsonline.com/news/view/21241/pacman <![CDATA[Pacman]]> The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions. This package is ideally added to .Rprofile to increase workflow by reducing time recalling obscurely named functions, reducing code and integrating functionality of base functions to simultaneously perform multiple actions.

Function names in the pacman package follow the format of p_xxx where ‘xxx’ is the task the function performs. For instance the p_load function allows the user to load one or more packages as a more generic substitute for the library or require functions and if the package isn’t available locally it will install it for you.

Installation

To download the development version of pacman:

Download the zip ball or tar ball, decompress and run R CMD INSTALL on it, or use the devtools package to install the development version:

## Make sure your current packages are up to date
update.packages()
## devtools is required
devtools::install_github("trinker/pacman")

Note: Windows users need Rtools and devtools to install this way.

More at https://github.com/trinker/pacman

 

]]> Rahul Nayak