BOL: Related items

Google Genomics

Tenzin Paul — Thu, 18 Dec 2014 11:05:42 -0600

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/

Bioinformatics Made Easy Search: Bioinformatics tools and run genomic analysis in the cloud

Rahul Nayak — Thu, 20 Aug 2015 02:21:20 -0500

InsideDNA makes hundreds of bioinformatics tools immediately available to run via an easy-to-use web interface and allows an accurate search across all functions, tools and pipelines.

With InsideDNA, you can upload and store your own genomic/genetic datasets in a limitless cloud space, and instantly analyze it with a powerful compute instance, without any tool installation or set up hassle.

More at https://insidedna.me/

Address of the bookmark: https://insidedna.me/

Cancer research database

Neel — Tue, 01 Sep 2015 17:36:31 -0500

Researchers in Andhra Pradesh have developed a database to identify genes that are common in tumours to provide their colleagues with easy access to insights into the genetic alterations in cancer.

The database, hosted at the Sri Venkateswara University (SVU) in Tirupati, will integrate information on cancer genes and markers with experimental data.

The Cancer Gene Markers Database (CGMD) is meant to help scientists better understand tumour genes and markers at a molecular level by combining data with literature on treatment regimen and recent advances in cancer therapy.

The database is free to access, and already includes 309 genes and 206 markers that correspond to 40 different human cancers. Accompanying literature comes from databases such as the United States’ National Center for Biotechnology Information and the Kyoto Encyclopedia of Genes and Genomes. It also includes experimental data from PubMed.

In a paper published last month in Nature Scientific Reports, the researchers from SVU’s department of animal biotechnology, describes the need for a database for different genes and markers along with their molecular characteristics and pathway associations.

SLURM basics !

Radha Agarkar — Fri, 13 May 2016 04:42:24 -0500

SLURM is a queue management system and stands for Simple Linux Utility for Resource Management. SLURM was developed at the Lawrence Livermore National Lab and currently runs some of the largest compute clusters in the world.

SLURM is similar in many ways to most other queue systems. You write a batch script then submit it to the queue manager. The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.

SLURM has a number of valuable features compared to other job management systems:

Kill and Requeue SLURM’s ability to kill and requeue is superior to that of other systems. It waits for jobs to be cleared before scheduling the high priority job. It also does kill and requeue on memory rather than just on core count.
Memory Memory requests are sacrosanct in SLURM. Thus the amount of memory you request at run time is guaranteed to be there. No one can infringe on that memory space and you cannot exceed the amount of memory that you request.
Accounting Tools SLURM has a back end database which stores historical information about the cluster. This information can be queried by the users who are curious about how much resources they have used.

Summary of SLURM commands

The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.

	SLURM	SLURM Example
Submit a batch serial job	sbatch	`sbatch runscript.sh`
Run a script interatively	srun	`srun --pty -p interact -t 10 --mem 1000 /bin/bash /bin/hostname`
Kill a job	scancel	`scancel 999999`
View status of queues	squeue	`squeue -u akitzmiller`
Check current job by id	sacct	`sacct -j 999999`

BioDownloader

Surabhi Chaudhary — Sat, 25 Feb 2017 17:52:33 -0600

BioDownloader is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:

optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).
allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)
has a built-in repository containing the settings for the most common bioinformatics download needs
built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)
capable of performing multiple download or update tasks simultaneously

BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.

http://dunbrack.fccc.edu/BioDownloader/

Address of the bookmark: http://dunbrack.fccc.edu/BioDownloader/

Binding Site Prediction in Protein !

Poonam Mahapatra — Wed, 25 Apr 2018 04:35:57 -0500

The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).

Pockets Identification

CASTp

Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin

Pocket-Finder

Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.

PocketPicker

Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for PyMOL

Binding Site Prediction

ConSurf

Identification of functional regions in proteins by surface-mapping of phylogenetic information

CRESCENDO

Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.

Ligand Binding Sites

3DLigandSite

The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.

FINDSITE

A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.

LIGSITE^csc

Prediction of binding site by pocket identification using the Connolly surface and degree of conservation

metaPocketA meta server for ligand-binding site prediction. metaPocket use LIGSITE^csc, PASS, Q-SiteFinder and SURFNET

Bioinformatics web development course

Jit — Wed, 06 Nov 2019 20:42:48 -0600

This web development course, targeted at Biology and Bioinformatics students, aims at teaching from scratch all the skills needed to setup a fully working Linux web server and to develop and deploy web applications for Bioinformatics.

No previous programming knowledge is assumed. By following this tutorial you will learn the fundamental concepts of programming by using scripting languages: variables, types, arrays, cycles, conditional statements, functions, objects, regular expressions, files reading and manipulation et-cetera.

Address of the bookmark: http://www.cellbiol.com/bioinformatics_web_development/introduction/

Research Associate Bioinformatics in IISc Recruitment 2020

Tue, 23 Jun 2020 21:53:34 -0500

Research Associate Bioinformatics in IISc Recruitment 2020

Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.

Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.

Desirable Qualifications (Research Associate/s): i) Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment).

ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv) Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.

The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.

Emoluments: As per DST, GOI norms and commensurate with experience.

More at https://www.iisc.ac.in/positions-open/

Stay Connected and Productive: Unlock the Power of Screen, Tmux, and Mosh for Bioinformatics

BioStar — Wed, 22 Jan 2025 00:29:52 -0600

If you are a bioinformatician, chances are you have spent hours running long, complex analyses on remote servers only to lose your session because of an unstable connection. Frustrating, isnt it? Fear not! With tools like screen, tmux, and mosh, you can safeguard your workflow and stay productive, no matter where you are.

Why Remote Session Management is a Must-Have

In bioinformatics, tasks like genome assembly, RNA-seq analyses, and phylogenetic computations often take hours or days. A dropped SSH connection can result in:

Lost Progress: Restarting a job from scratch wastes valuable time.
Workflow Interruptions: Disruptions can derail your focus and productivity.
Corrupted Data: Interrupted processes may lead to incomplete or corrupted outputs.

By integrating screen, tmux, or mosh into your workflow, you can avoid these setbacks and ensure a seamless experience.

Screen: The Classic Workhorse

Screen is a terminal multiplexer that comes pre-installed on most Linux systems. It allows you to manage multiple terminal sessions and reconnect to them even after being disconnected.

Getting Started with Screen:

Start a Session:

screen
Detach from a Session:
Press Ctrl+A, then D.
Reattach to a Session:

screen -r

Pro Tip: Enhance your screen experience with a customized .screenrc configuration file. Download one here: Get .screenrc.

Tmux: A Modern Alternative

Tmux takes everything great about screen and adds modern features, including better key bindings and intuitive session management. It\u2019s perfect for bioinformaticians who want more control over their workflow.

Getting Started with Tmux:

Start a Session:

tmux
Detach from a Session:
Press Ctrl+B, then D.
Reattach to a Session:

tmux attach

Customize Your Tmux Experience:
Use a .tmux.conf file to personalize your setup. Grab one here: Download .tmux.conf.

Mosh: The Mobile Shell for Unreliable Connections

SSH works well for stable networks, but it struggles in areas with spotty connectivity. Enter Mosh, the Mobile Shell. Designed for intermittent networks, Mosh keeps your session alive even when the connection drops temporarily.

Why Mosh is a Game-Changer:

No lag over high-latency networks.
Automatically reconnects when the network is restored.
Ideal for working on the go, from cafes to trains.

Getting Started with Mosh:

Install Mosh:

sudo apt install mosh # For Debian/Ubuntu
Connect to a Server:

mosh username@server

Learn more at mosh.org.

Why This Matters for Bioinformatics

Every bioinformatician knows the value of time and data integrity. Tools like screen, tmux, and mosh provide a lifeline when running long analyses, enabling you to:

Safeguard your work against disconnections.
Easily manage multiple workflows in parallel.
Stay productive, even in challenging environments.

Quickstart Cheat Sheet

Screen:

screen # Start a session Ctrl+A, D # Detach screen -r # Reattach
Tmux:

tmux # Start a session Ctrl+B, D # Detach tmux attach # Reattach
Mosh:

mosh username@server

Final Thoughts

As a bioinformatician, your time is too valuable to spend restarting analyses due to technical hiccups. With screen, tmux, and mosh in your toolkit, you can work smarter, protect your progress, and stay productive no matter where you are. Start using these tools today and transform the way you work with remote systems.

Let me know how these tools work for you, and don\u2019t forget to follow for more bioinformatics tips!

Phylogenomics/Phylogenetic website

Aaryan Lokwani — Mon, 07 Apr 2014 02:17:18 -0500

Welcome to phylobabble.org, a discussion forum for phylogenetic theory and applications. The primary goal of this forum is to discuss best practice and new developments in phylogenetics. Although we do have a Troubleshooting category for getting feedback on analyses, this is not a help site for running phylogenetics programs.

A great place to chat about phylogenetics for researchers and the broader community of students and science-interested citizens.

Address of the bookmark: http://phylobabble.org/