BOL: Related items

Khalturin Lab

Wed, 06 May 2026 19:04:26 -0500

Our lab focuses on the comparative genomics and developmental biology of basal metazoans, particularly on jellyfish and hydra models. We are interested in understanding the molecular mechanisms underlying stem cell dynamics, regeneration, and the evolutionary origins of these processes in early-diverging animal lineages.

More at https://jellyfish.icob.sinica.edu.tw/index.html

The Centre for Bioinformatics (MCB) Lab

Sun, 14 Jul 2013 12:41:20 -0500

The Centre for Bioinformatics (MCB) is a diverse collection of professors, postdoctoral fellows, and students, who share a common interest in Bioinformatics.

Research Area

We are interested in the development of the statistics and computational methods for the analysis of this data in breast cancer.
We have worked on probabilistic models for subcellular localization, protein-protein interactions, and problems related to chemical genomics.
We are interested in the development of bioinformatics/biostatistical methodology in the analysis of epigenetic/epigenomic data.
We are interested in integrative bioinformatics approaches to learn the gene, gene products, interactions, and regulatory mechanisms involved in mental retardation.

Link @ http://www.mcgill.ca/mcb/

BioProgramming

Jitendra Narayan — Sun, 14 Jul 2013 16:29:53 -0500

The completion of the first human genome drafts was just a start of the modern DNA sequencing era which resulted in further invention, improved development toward new advanced strategies of high-throughput DNA sequencing, so called the “high-throughput next generation sequencing” (HT-NGS). The decreasing genome sequencing cost and desire to explore and understand biological machanism at genomic level, speed up the genomic sequencing projects. In the fast growing HT-NGS technologies, the main challenge is to cope with the analysis of vast production of sequencing database through advanced bioinformatics tools. In oder to develope sotware/tools bioinformatician/ biological programmers need to expertise in any one one the programming language. However, sometime one language are not enough to handle all sort of biological needs, which compel us to learn new biologically suitable language to handle ever growing genome or protein sequences.

The next step after reading genetic code is writing a script to analyse and explore the hidden information. This tutorial is aimed to introduce you new biological programming languages with their packages/libraries, and assist in your scripting work.

Navigate the sub-section of this page [ see right hand side of the page for it ]

EMBO Practical Course, Bioinformatics, large-scale data, at Shenzhen, China

Wed, 14 Aug 2013 09:50:56 -0500

This international advanced course will provide training on bioinformatics and statistics methods for genomic research. It will give insight into how biological knowledge can be generated from high-throughput sequencing (DNA-Seq, RNA-seq, ChIP-seq) experiments and will illustrate how to analyze such data. The course covers both the underlying statistical and algorithmic concepts, and the practice of how to automate and code such analyses using the scripting language R.

17 Nov 2013 -22 Nov 2013

More at http://events.embo.org/13-large-scale-data/

Online Registration: https://www.conference-service.com/pc13-47/welcome.cgi

The Minerva Research Group for Bioinformatics

Tue, 27 May 2014 15:48:14 -0500

The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.

http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27

Kelso Group
Department of Evolutionary Genetics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
Phone: +49 341 3550 500

Job:
http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40

Spotlight on Genomics: Understanding Our Genes - A Step to Personalized Medicine

Mon, 26 Aug 2013 17:07:44 -0500

(Visit: http://www.uctv.tv/) Learn about the essential role of genomics in the development of stem cell based therapies. Craig Venter, president and founder of the J. Craig Venter Institute and Catriona Jamieson, director for stem cell research at the UCSD Moores Cancer Center, speak about the future of personalized medicine in which genomics, the study of genes and their function, is applied to pinpoint specific treatments for patients. Sandra Dillon, a clinical trial participant, gives a patient's perspective. [7/2013] [Health and Medicine] [Show ID: 24530]

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...

Make Genomic Research Less Ethnically-Biased

Shikha Logwani — Wed, 30 Oct 2013 16:08:17 -0500

Mexican billionaire Carlos Slim Hélu, the world’s 2nd-richest man, is giving an additional $74 million to a genomics center in Boston in order to right a bias in the field–a kind of scientific racism, you might call it. The problem: most samples of DNA analyzed in biomedical research come from people of European descent.

Find more detail news at http://www.forbes.com/sites/erincarlyle/2013/10/30/carlos-slim-gives-another-74-million-to-make-genomic-research-less-ethnically-biased/?utm_campaign=forbesfbsf&utm_source=facebook&utm_medium=social

Janggu - Deep learning for Genomics

Jit — Tue, 23 Mar 2021 05:14:43 -0500

Janggu is a python package that facilitates deep learning in the context of genomics. The package is freely available under a GPL-3.0 license.

Detail tutorial at https://janggu.readthedocs.io/en/latest/

USE cases

https://github.com/wkopp/janggu_usecases

Address of the bookmark: https://github.com/BIMSBbioinfo/janggu

MetaSim A Sequencing Simulator for Genomics and Metagenomics.

Jit — Mon, 04 Dec 2017 07:18:20 -0600

Our software can be used to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to design a metagenome by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a simulation of a number of different sequencing technologies. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.

Address of the bookmark: http://ab.inf.uni-tuebingen.de/software/metasim/