BOL: Related items

Salzberg lab

Mon, 15 May 2017 05:14:01 -0500

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.

https://salzberg-lab.org/

Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.

Jit — Tue, 18 Jun 2019 05:33:04 -0500

Cogent is a tool that identifies gene families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check assemblies for the presence of these known coding sequences.

Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on Iso-Seq data and in cases where there is no reference genome or the ref genome is highly incomplete.

See a recent presentation on Cogent being applied to the Cuttlefish Iso-Seq data.

Cogent preliminary draft paper (updated 2016Dec version), Supplementary

Please see wiki for details on usage.

Address of the bookmark: https://github.com/Magdoll/Cogent

The 8000 years old Tibetian gene mutation !!!

Neel — Wed, 20 Aug 2014 21:57:44 -0500

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

Vital-IT

Abhi — Thu, 18 Dec 2014 10:46:59 -0600

Vital-IT is a bioinformatics competence center that supports and collaborates with life scientists in Switzerland and beyond. The multi-disciplinary team provides expertise, training and maintains a high-performance computing (HPC) and storage infrastructure, so as to help develop, maintain and extend life science and medical research (activities).

Address of the bookmark: http://www.vital-it.ch/

MIT Computational Biology Group

Thu, 18 Dec 2014 14:47:01 -0600

My research group consists primarily of computer science graduate students and postdocs with expertise in algorithms, statistical inferences and machine learning, and sharing a passion for understanding fundamental biological problems.

We work in a highly interdisciplinary environment at the interface of Computer Science and Biology. Since its inception, our lab has eagerly engaged in collaborative research partnerships with biological and experimental collaborators, facilitated by our affiliation with the Broad Institute and the Computational and Systems Biology initiative (CSBi) at MIT, our participation in the Epigenome Roadmap, ENCODE, and modENCODE consortia, and by several other ongoing collaborations at MIT, Harvard, and the Harvard Medical School affiliated hospitals.

http://compbio.mit.edu/

Genome Stability Laboratory

Mon, 07 Mar 2016 04:16:32 -0600

The bakers yeast, Saccharomyces cerevisiae is an ideal model organism to understand mechanisms of meiotic chromosome segregation. In S. cerevisiae and in mammals, the majority of meiotic crossovers are formed through a highly conserved MSH4p-MSH5p, MLH1p-MLH3p dependent pathway. We are interested in charactering the role of these complexes in crossover formation and distribution among all homolog pairs. Errors in this process are linked to congenital birth defects in humans such as Down's syndrome.Our laboratory is also interested in understanding the effect of genetic background on mutation rate variation using S. cerevisiae as a model. These studies are relevant for understanding cancer progression, genome evolution and architecture. We use high- throughput genomic methods as well as classical genetics to achieve these aims.

More at http://faculty.iisertvm.ac.in/~nishantkt/index.html

Katju Lab

Fri, 26 Feb 2016 03:25:32 -0600

TheLab seek to understand the genetic factors contributing to genomic variation and phenotypic diversity. To this end, we employ molecular and bioinformatic tools to study evolutionary processes at the level of populations, both experimental and natural, and genomes. Our research interests encompass a wide range of topics, including the evolution of organellar and nuclear genomes, gene duplication and the origin of novel function, and the fitness and phenotypic consequences of mutation in evolution. For details regards ongoing projects, please see the Research page.

http://katjulab.com/research.html

You and your friend have similar DNA !!!

Jit — Sun, 27 Jul 2014 20:44:05 -0500

New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.

Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes — a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.

The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.

Reference:

http://www.pnas.org/content/111/Supplement_3/10796.full

Image : http://i.kinja-img.com

Advanced Bash-Scripting Guide

Jit — Thu, 18 Feb 2016 04:50:51 -0600

This tutorial assumes no previous knowledge of scripting or programming, yet progresses rapidly toward an intermediate/advanced level of instruction . . . all the while sneaking in little nuggets of UNIX® wisdom and lore. It serves as a textbook, a manual for self-study, and as a reference and source of knowledge on shell scripting techniques. The exercises and heavily-commented examples invite active reader participation, under the premise that the only way to really learn scripting is to write scripts.

This book is suitable for classroom use as a general introduction to programming concepts.

More at http://tldp.org/LDP/abs/html/

Address of the bookmark: http://tldp.org/LDP/abs/html/

Bioinformatics tools and software

Jit — Tue, 05 Jul 2016 10:02:26 -0500

USEARCH >
Extreme high-throughput sequence analysis. Orders of magnitude faster than BLAST. MUSCLE >
Multiple sequence alignment. Faster and more accurate than CLUSTALW.

UPARSE >
OTU clustering for 16S and other marker genes. Highly accurate OTU sequences and improved diversity measures. UCHIME >
Chimeric sequence detection. PILER >
De novo genome repeat finder. PILER-CR >
Detection of CRISPR repeats in bacterial genomes. QSCORE >
Compare two multiple alignments for benchmarking. PALS >
Whole-genome alignment. PREFAB >
Protein Reference Alignment Database. MSA benchmark collection >
Selected multiple alignment benchmarks in a standardized FASTA format.

Address of the bookmark: http://drive5.com/software.html