<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/26852?offset=860 https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r Fri, 06 Apr 2018 12:10:45 -0500 https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r <![CDATA[d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.]]> Mike Bostock’s D3.js is great for creating interactive network graphs with JavaScript. The d3Network package makes it easy to create these network graphs from R. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.

Address of the bookmark: http://christophergandrud.github.io/d3Network/

]]> Jit https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking Wed, 25 Apr 2018 05:15:53 -0500 https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking <![CDATA[Tools for Protein-Protein Docking !]]> Predicting the structure of protein–protein complexes using docking approaches is a difficult problem whose major challenges include identifying correct solutions, and properly dealing with molecular flexibility and conformational changes. Following are the tools to predict the structure of protein–protein complexes:

3D-Dock Suite

Global rigid search: FFTShape complementarity and electrostatics

Re-scoring and clustering. Refinement of interface side-chains

3D-Garden

Global rigid search in ensamble

Shape complementarity and Lennard–Jones potential

Side chain and backbone dihedral refinement

DOT

Global rigid search: FFTShape complementarity, electrostatics and VDWNone

Escher NG

Global rigid searchShape complementarity, hydrogen bonds and electrostatic

Integrated in VEGA

GRAMM 

Global rigid search: FFT. smooth protein surface representation for soft docking

Shape complementarity and Lennard-Jones potential

Clustering of conformations

GRAMM-X 

Global rigid search: FFT. smooth protein surface representation for soft docking

Shape complementarity and Lennard-Jones potentialminimization and re-scoring with multiple filters

HEX

Global rigid search: Fourier correlation of spherical harmonics

Shape complementarity

HADDOCK

Global rigid searchElectrostatic ,VDW and desolvation energy termsMD simulated annealing refinement . Filtering based on external data. 

ICM

Global rigid search: Monte CarloEmpirical scoring function

Clustering and selection of conformations. Refinement of interface side-chains and re-scoring

MolFit 

Global rigid search: FFTShape complementarity

Clustering of good solutions, filtering using a priori information and small, local rigid rotations around selected conformations

PatchDock

Global rigid searchShape complementarity and atomic desolvation energy

Clustering of conformations

PyDock

Global rigid search:FFTShape complementarity

rescoring by binding electrostatics and desolvation energy

RosettaDock

Local rigid search: Monte Carlo with low and high resolution structure representation levels

Different scoring parameters for the different resolutions 

ZDOCK

Global rigid search: FFTShape complementarity, desolvation energy, and electrostatics.

Energy minimization and re-scoringFree for academics

 

Point to note:

The proper treatment of flexibility in protein–protein docking is still an active field of research. You first should analyzed your proteins in order to define their conformational space and then choose the most suitable method for your docking problem.

]]> Poonam Mahapatra https://bioinformaticsonline.com/opportunity/view/12111/internship-program-with-arraygen-technolgies Sun, 22 Jun 2014 23:18:31 -0500 <![CDATA[Internship program with ArrayGen Technolgies]]> Internship Program for Bioinformatics / Biotechnology Professionals Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.

Interested candidates may email their resume along with a cover letter to careers@arraygen.com

Official website: http://www.arraygen.com/

]]> https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software Tue, 08 May 2018 04:39:39 -0500 https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software <![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]> EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see
http://arthropods.eugenes.org/EvidentialGene/

Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.

Download 

http://arthropods.eugenes.org/EvidentialGene/trassembly.html

https://sourceforge.net/p/evidentialgene/blog/

Address of the bookmark: http://arthropods.eugenes.org/EvidentialGene/trassembly.html

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes Thu, 09 Aug 2018 17:41:17 -0500 https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes <![CDATA[mmgenome: Tools for extracting individual genomes from metagneomes]]> The mmgenome toolbox enables reproducible extraction of individual genomes from metagenomes. It builds on the multi-metagenome concept, but wraps most of the process of extracting genomes in simple R functions. Thereby making the whole process of binning easy and at the same time reproducible through the Rmarkdown format.

The mmgenome R package also facilitates effortless integration with additional data sources and hence should not be seen as "yet another binning method", but rather a package to integrate different binning strategies.

All functions in the mmgenome R package has associated documentation, check it out in R by e.g. ?mmplot.

Address of the bookmark: https://github.com/MadsAlbertsen/mmgenome

]]> Jit 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/14215/the-8000-years-old-tibetian-gene-mutation Wed, 20 Aug 2014 21:57:44 -0500 https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation <![CDATA[The 8000 years old Tibetian gene mutation !!!]]> A new study has provided insight into how gene mutation around 8,000 years ago helped Tibetans' to survive in the thin air on the Tibetan Plateau, where an average elevation is of 14,800 feet.

A study led by University of Utah scientists is the first to find a genetic cause for the adaptation, a single DNA base pair change that dates back 8,000 years and demonstrate how it contributes to the Tibetans' ability to live in low oxygen conditions.

About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.

In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.

Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html

]]> Neel 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/34400/ioniser-tools-for-the-quality-assessment-of-data-produced-by-oxford-nanopore%E2%80%99s-minion-sequencer Thu, 23 Nov 2017 10:24:19 -0600 https://bioinformaticsonline.com/bookmarks/view/34400/ioniser-tools-for-the-quality-assessment-of-data-produced-by-oxford-nanopore%E2%80%99s-minion-sequencer <![CDATA[IONiseR: tools for the quality assessment of data produced by Oxford Nanopore’s MinION sequencer]]> This package is intended to provide tools for the quality assessment of data produced by Oxford Nanopore’s MinION sequencer. It includes a functions to generate a number plots for examining the statistics that we think will be useful for this task.

However, nanopore sequencing is an emerging and rapidly developing technology. It is not clear what will be most informative. We hope that IONiseR will provide a framework for visualisation of metrics that we haven’t thought of, and welcome feedback at mike.smith@embl.de.

If you’re not interested in the quality assement of the raw or event level data, and want to jump straight to the getting FASTQ format files from fast5 files you can go straight to the final section of this document.

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/IONiseR/inst/doc/IONiseR.html

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads Tue, 08 May 2018 04:27:22 -0500 https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads <![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]> HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs [Sirén et al. 2014], we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM). 

more at https://ccb.jhu.edu/software/hisat2/index.shtml

Address of the bookmark: https://github.com/infphilo/hisat2

]]> Rahul Nayak