<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/37965?offset=60 https://bioinformaticsonline.com/opportunity/view/18820/jrfsrf-at-university-of-calcutta Fri, 31 Oct 2014 08:53:10 -0500 <![CDATA[JRF/SRF at University of Calcutta]]> Applications are invited to appear at a walk-in-interview for one post of Junior Research Fellow in the DBT(DBT Twinning NER) sponsored project entitled “Protein folding kinetics is a selection force on shaping codon usage bias in the high expression genes” in the room of the HOD, Department of Biotechnology and the Coordinator, DR. B. C. Guha Centre for Genetic Engineering and Biotechnology, University College of Science, 35 Ballygunge Circular Road, Kolkata 700019 on the 12th November, 2014 at 3:00 p.m.

Essential qualifications: First class M. Sc. in any branch of life sciences and qualified CSIR-UGC NET/GATE Examination.

Desirable qualifications: Practical experience in biochemical and biophysical studies of proteins

Emoluments: as per DBT norms

The project is tenable for two years, initially for one year.

Age: Below 28 years (relaxable in the case of SC/ST/OBC/women candidates)

Candidates are requested to bring two sets of complete applications on plain paper furnishing bio-data and copies of attested certificates along with originals (for verification) on the date of interview.

No TA/DA is admissible for candidates appearing at the interview.

Dr. Rajat Banerjee
Assistant Professor
Department of Biotechnology and
Dr. B. C. Guha Centre for Genetic Engineering and Biotechnology
University College of Science
35, Ballygunge Circular Road
Kolkata 700019

Advertisement: www.caluniv.ac.in/news/jrf_biotech_2.pdf

]]> https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs Fri, 03 Mar 2017 05:15:07 -0600 https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs <![CDATA[MetaPred2CS]]> MetaPred2CS Web server is a meta-predictor based on Support Vector Machine (SVM) that combines 6 individual sequence based protein-protein interaction prediction methods to predict prokaryotic two-component system protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods: in-silico two hybrid (i2h) and mirror tree (MT) methods and 4 genomics context based methods: phylogenetic profiling (PP), gene fusion (GF), gene neighbourhood (GN) and and gene operon methods (GO).

 http://metapred2cs.ibers.aber.ac.uk/

Address of the bookmark: https://github.com/martinjvickers/MetaPred2CS

]]> Manisha Mishra https://bioinformaticsonline.com/bookmarks/view/34744/foldit-solve-puzzles-for-science Thu, 21 Dec 2017 15:17:47 -0600 https://bioinformaticsonline.com/bookmarks/view/34744/foldit-solve-puzzles-for-science <![CDATA[Foldit: Solve Puzzles for Science]]> Foldit is an online puzzle video game about protein folding. It is part of an experimental research project developed by the University of Washington, Center for Game Science, in collaboration with the UW Department of Biochemistry. The objective of Foldit is to fold the structures of selected proteins as perfectly as possible

https://fold.it/portal/

Address of the bookmark: https://fold.it/

]]> Robert M Willioms https://bioinformaticsonline.com/pages/view/36392/protein-protein-interaction-sites-predictions Wed, 25 Apr 2018 04:53:20 -0500 https://bioinformaticsonline.com/pages/view/36392/protein-protein-interaction-sites-predictions <![CDATA[Protein-Protein Interaction Sites Predictions !]]> The study of Protein–Protein Interactions (PPIs) has a crucial role in biology, medicine and the pharmaceutical industry. PPIs can be investigated from two aspects: The interaction partners of a specific protein and the amino acid residues participating in a given PPI. Information about a protein’s interaction partners allows scientists to construct protein interaction networks, such as signaling pathways, which in turn facilitate the understanding of many biological and clinical observations. 

Following are the list of tools commonly used to PPIs predictions:

Protein-Protein Interaction Sites

PPISP

A consensus neural network method for predicting protein-protein interaction sites

HOMCOS

A server to predict interacting protein pairs and interacting sites by homology modeling of complex structures

HotPOINT

Prediction of protein interfaces using an empirical model

ISIS

Prediction of interaction hotspots from sequence

KFC server

Automated decision-tree approach to predicting protein-protein interaction hot spots

meta-PPISP

A meta server for predicting protein-protein interaction sites. meta-PPISP is built on three individual web servers: cons-PPISP, PINUP, and Promate

ODA

Identification of optimal surface patches with the lowest docking desolvation energy values

PINUP

Protein binding site prediction with an empirical scoring function

Other Sites (DNA, RNA, Metals)

CHED 

Web server for predicting soft metal binding sites in proteins

DBD-Hunter

A knowledge-based method for the prediction of DNA-protein interactions

DISPLAR

Given the structure of a protein known to bind DNA, the method predicts residues that contact DNA using neural network method

iDBPs

Predicts DNA binding proteins for proteins with known 3D structure.

PFplus

A tool for extracting and displaying positive electrostatic patches on protein surfaces which can be indicative of nucleic acid binding interfaces.
]]> Poonam Mahapatra https://bioinformaticsonline.com/bookmarks/view/44882/fantasia Wed, 20 Aug 2025 02:48:15 -0500 https://bioinformaticsonline.com/bookmarks/view/44882/fantasia <![CDATA[FANTASIA]]> FANTASIA is an advanced pipeline for the automatic functional annotation of protein sequences using state-of-the-art protein language models. It integrates deep learning embeddings and in-memory similarity searches, retrieving reference vectors from a PostgreSQL database with pgvector, to associate Gene Ontology (GO) terms with proteins.

https://www.nature.com/articles/s42003-025-08651-2

Address of the bookmark: https://github.com/CBBIO/FANTASIA

]]> BioStar 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     https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server Fri, 07 Dec 2018 08:04:57 -0600 https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server <![CDATA[GWASpro: A High-Performance Genome-Wide Association Analysis Server]]> GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.

     

    Address of the bookmark: https://bioinfo.noble.org/GWASPRO/

    ]]>     Rahul Nayak     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/blog/view/38248/how-to-set-up-ssh-on-ubuntu-1804 Thu, 22 Nov 2018 10:12:00 -0600 https://bioinformaticsonline.com/blog/view/38248/how-to-set-up-ssh-on-ubuntu-1804 <![CDATA[How to set up SSH on Ubuntu 18.04]]> SSH, also known as Secure Shell or Secure Socket Shell, is a network protocol that gives users, particularly system administrators, a secure way to access a computer over an unsecured network. SSH also refers to the suite of utilities that implement the SSH protocol.

    Here are the commands used to connect by Secure SHell:

    On the server side

    sudo apt-get install ssh

    sudo apt-get install openssh-server

    sudo /etc/init.d/ssh start

    sudo nano /etc/ssh/sshd_config

    Uncomment port 22
    Uncomment HostKey /etc/ssh/ssh_host_rsa_key
    Uncomment AuthorizedKeysFile .ssh/authorized_keys .ssh/authorized_keys2
    Set pubkey authentication to "yes"

    sudo systemctl restart sshd.service # or sudo /etc/init.d/ssh reload


    On the client side:
    in ~/.ssh

    ssh-keygen -t rsa # set passphrase or not
    ssh-copy-id -i ~/.ssh/id_rsa user@100.100.10.100

    --> write "yes" then password in


    ssh user@100.100.10.100

    --> write password --> you should be in

    --> in /home/user/.ssh/config type:
    Host WhateverName
    HostName 100.100.10.100
    User username
    ForwardX11 yes
    ForwardAgent yes
    IdentityFile ~/.ssh/id_rsa

    --> you should now be able to connect with :

    ssh WhateverName

    ]]>     AnHo