BOL: Related items

Research Rabbit

LEGE — Fri, 07 Apr 2023 12:01:33 -0500

You’re determined students, passionate teachers, and inspired creators of everything we know! Yet, all the researchers we spoke with over the past year uncovered the same reality:

Despite the degrees you’ve earned, the effort and passion you put in every day, the sacrifices you make – academia burdens you with tons of stressors. Financial, psychological, physical, and more.

We’re an unconventional team with backgrounds in various fields – both inside and outside of academia. And through our lens, it’s clear that academia deeply undervalues and underserves its very own community!

It’s time to reimagine research.

Address of the bookmark: https://researchrabbitapp.com/

Monitor running jobs on Linux server

Jitendra Narayan — Fri, 06 Jun 2014 16:18:43 -0500

You as a bioinformatican run lots of program on your servers. Sometime the shared server is also used by your colleague. If server is busy you sometime need to check the running programs and want to monitor the running programs as well. The "top" command will come in handy when you need to find out if things are still running, how long they’ve been running, or how much memory is being used.

‘top’ is very simple to run: type

%% top

You’ll get a screen that looks like this, and is updated regularly:

Simple, right? Heh.

First! Note that you can use ‘q’ or ‘CTRL-C’ to exit from ‘top’.

Now let’s read and understand at each line independently.

The first line:

top - 23:00:48 up 39 days, 2 user, load average: 0.00, 0.00, 0.00

The first line tells you the current time, how long the machine has been up, how many users are logged in, and the short/medium/long-term compute load on the machine. If you run something for a long time, you’ll see these numbers go up. Right now, the machine is basically just sitting there, so these are all close to 0.

The second line:

Tasks: 239 total,   1 running, 238 sleeping,   0 stopped,   0 zombie

This line tells you how many processes are running. If you are using laptops machines it’s not so interesting because you really are the only one using this machine.

Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st

This line contains the CPU load. The first two numbers are how busy the system is doing computation (“us” stands for “user”) and how busy the system is doing system-y things like accessing disks or network (“sy” stands for “system”). We’ll talk more about this later.

Mem:   49457320k total,    3492174k used, 14535596k free,    1435148k buffers

This should be easy to understand – how much memory you’re using!

Swap:   539356k total,   28332k used,   836562k free,    29862014k cached

Swap is just on-disk memory that can be used to “swap” out programs from main memory. Again, we’ll talk about this later.:

PID USER      PR NI VIRT RES SHR S %CPU %MEM    TIME+ COMMAND
1 root      39 19 0 0 0 S 0.0 0.0   246:57.22 kipmi0
2 root      RT   0     0    0    0 S 0.0 0.0   0:00.00 migration/0

And... finally! What’s actually running! The two most important numbers are the %CPU and %MEM towards the right, as well as the COMMAND. This tells you how compute- and memory-intensive your program is. Right now, nothing’s running so the numbers aren’t very interesting, but just wait until we run something...

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/

Enrichr: a comprehensive gene set enrichment analysis

Jit — Thu, 27 Apr 2017 05:42:09 -0500

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw377

Address of the bookmark: http://amp.pharm.mssm.edu/Enrichr/

Apache server setting !

Abhi — Fri, 29 Oct 2021 04:29:51 -0500

Apache is an open source web server that’s available for Linux servers free of charge.

In this tutorial we’ll be going through the steps of setting up an Apache server.

What you’ll learn

How to set up Apache
Some basic Apache configuration

Address of the bookmark: https://ubuntu.com/tutorials/install-and-configure-apache#3-creating-your-own-website

Heatmap Draw !

BioStar — Mon, 06 Mar 2023 04:24:57 -0600

Server for heatmap generation !

https://software.broadinstitute.org/morpheus/

Address of the bookmark: https://software.broadinstitute.org/morpheus/

FRODOCK 2.0: fast protein–protein docking server

Neel — Wed, 17 Oct 2018 04:31:30 -0500

frodock: a user-friendly protein–protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein–protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein–protein binding conformations that can be further refined with more computationally demanding strategies.

Address of the bookmark: http://frodock.chaconlab.org/

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/

CSAR-web: a web server of contig scaffolding using algebraic rearrangements

BioStar — Fri, 10 Apr 2020 04:39:36 -0500

CSAR-web is a web-based tool that allows the users to efficiently and accurately scaffold (i.e. order and orient) the contigs of a target draft genome based on a complete or incomplete reference genome from a related organism.

CSAR-web can serve as a convenient and useful scaffolding tool allowing the users to efficiently and accurately scaffold their draft genomes according to a complete or incomplete reference genome.

Address of the bookmark: http://genome.cs.nthu.edu.tw/CSAR-web

htop explained

Jit — Wed, 06 Jul 2022 01:28:09 -0500

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/