BOL: Related items

2 positions on the evolutionary analysis of biological sequences in Montpellier - France

Mon, 28 Sep 2015 08:25:48 -0500

The Methods and Algorithms for Bioinformatics (MAB) team at the LIRMM (computer science, robotics and microelectronics laboratory at the CNRS & University of Montpellier, France) is looking for talented individuals to fill two postdoctoral positions. We are seeking candidates with a strong background in computational evolutionary biology. The positions will start by the end of 2015.

The first of the positions (duration: 18-24 months), associated with the European VIROGENESIS project (http://www.kuleuven.be/english/research/EU/p/horizon2020/sc/sc1/Virogenesis), concerns the evolutionary analysis of viral sequences. Topics include -- but are not limited to -- phylogenetic classification of metagenomic reads and the recombination history of viruses.

The second position (duration: 1 year), associated with the Institute for Computational Biology (IBC, http://www.ibc-montpellier.fr), concerns evolutionary analyses of large-scale genomic data -- including the inference of very large phylogenies, gene/species tree reconciliation, comparative genomics, phylogenetic network inference and verification, phylogeography, the use of phylogenies to study the evolution of characters.

A one thousand year old city, Montpellier is a thriving research community with a multitude of biology and biomedical research centers. It is the fastest growing city in France where approximately one third of the population are students, and a wonderful location for outdoor activities (kite/wind surfing, sailing, river/sea kayaking, hiking and rock climbing). The LIRMM is one of the most visible computer science laboratories in France.

Pre- or postdoctoral research fellowship in Structural Bioinformatics at Padova

Thu, 05 Nov 2015 22:15:12 -0600

A research fellowship for a software developer is available at the BioComputing UP Laboratory, University of Padova (URL: http://protein.bio.unipd.it/).
A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures.

The BioComputing UP Laboratory, headed by Prof. Silvio Tosatto, is a dynamic group of a dozen people working on several aspects of prediction of protein structure & function employing techniques at the intersection between biology, medicine, chemistry, physics & computer science.
Our aim is to integrate the development of novel methods and their application to biologically relevant problems.

We are looking for candidates with a solid Bioinformatics background, programming experience (Python, C++ and/or Java) and good knowledge of molecular biology (protein structure/function). Good knowledge of statistics as well as experience in using database systems (MongoDB, MySQL and/or Postgres) is desirable. Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial.

The fellowship, which should start as soon as possible, is renewable and initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be working full-time at the BioComputing UP Laboratory, University of Padova. Travel support for conferences and/or research visits abroad is provided.
To apply, please send your CV, with a motivation letter and brief description of your research background as well as the names of two (or more) references to: biocomp@bio.unipd.it.

Start date: As soon as possible

Duration: 1 year, renewable

Salary on grant: Commesurate to experience

Contact Person (Referent): Silvio Tosatto

Ref. E-Mail: biocomp@bio.unipd.it

Tel: +39 049 827 6269
Fax: +39 049 827 6260

Group Web Page: http://protein.bio.unipd.it/

Kamaleshwar Singh Lab

Fri, 25 Mar 2016 10:46:49 -0500

The focus of Dr. Singh’s research and teaching is on the molecular mechanistic basis for environmental carcinogen-induced genetic (DNA damage) and epigenetic changes, and susceptibility to human cancer development

More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html

Chekulaevalab

Tue, 12 Jan 2016 02:32:03 -0600

Focusing on understanding the molecular mechanisms that regulate mRNA translation, localization and stability and role of non-coding RNAs in this process. Up to 90% of human DNA is estimated to be transcribed into so called non-coding RNAs that are not translated into proteins. Many of them act as potent modifiers of gene expression. miRNAs are a class of such short non-coding RNAs. They regulate expression of more than a half of eukaryotic genes, thus, affecting multiple biological processes, including cell proliferation, differentiation, apoptosis and senescence. Not surprisingly, miRNAs are involved in many human pathologies, including cancer and neurological disorders and hold great potential as drug targets, disease markers, as well as therapeutic agents.
Our lab is located at the Berlin Institute for Medical Systems Biology (BIMSB), a part of the Max Delbrück Center for Molecular Medicine (MDC).

http://www.chekulaevalab.org/

Centurion

Jit — Fri, 12 Feb 2016 04:45:41 -0600

Although centromeres are essential for life and are the subject of extensive research, centromere locations in yeast genomes are difficult to infer, and in most species they are still unknown. Recently, the chromatin conformation assay Hi-C has been re-purposed for diverse applications, including de novo genome assembly, deconvolution of metagenomic samples, and inference of centromere locations. We describe a method, Centurion, that jointly infers the locations of all centromeres in a single yeast genome by exploiting the centromeres’ tendency to cluster in 3D space. We first demonstrate the accuracy of Centurion in identifying known centromere locations from high coverage Hi-C data of budding yeast and a human malaria parasite. We then use two metagenomic samples with relatively low coverage Hi-C data to infer centromere locations for each chromosome in 14 different yeast species. For yeasts with large centromeres (e.g., S. pombe) Centurion predicts the exact centromere locations. For seven yeasts with point centromeres, Centurion predicts most of the centromeres at an average of 5~kb distance from their known locations. Finally, we predict centromere coordinates for six yeast species that currently lack centromere annotations. These results suggest that Centurion can be used for centromere identification for a large number of yeast species, even with a limited amount of Hi-C sequencing.

Paper:http://www.ncbi.nlm.nih.gov/pubmed/25940625

More at http://cbio.ensmp.fr/centurion/

Address of the bookmark: http://cbio.ensmp.fr/centurion/

Radka Reifová Lab

Mon, 15 Feb 2016 06:00:48 -0600

We are generally interested in the mechanisms of species origin from a molecular and ecological perspective. Particularly, we are interested in the role of sex chromosomes in speciation. Most of our research is done on birds and mammals. Currently, we focus our research on two hybridizing song birds, the Common nightingale (Luscinia megarhynchos) and the Thrush Nightingale (L. luscinia). Combining population genomic and ecological approaches we try to elucidate the genetic architecture of reproductive isolation and understand the role of interspecific competition and song convergence in the evolution of reproductive isolation between the species.

More at http://web.natur.cuni.cz/~radkas/index.php?page=research

Genome Browser : GBrowse

Jit — Fri, 19 Feb 2016 09:22:43 -0600

Generic Genome Browser Version 2: A Tutorial for Administrators

This is an extensive tutorial to take you through the main features and gotchas of configuring GBrowse as a server. This tutorial assumes that you have successfully set up Perl, GD, BioPerl and the other GBrowse dependencies. If you haven't, please see the GBrowse HOWTO During most of the tutorial, we will be using the "in-memory" GBrowse database (no relational database required!) Later we will show how to set up a genome size database using the berkeleydb and MySQL adaptors.

More at http://elp.ucdavis.edu/tutorial/tutorial.html

Address of the bookmark: http://elp.ucdavis.edu/tutorial/tutorial.html

RNA-Seq De novo Assembly Using Trinity

Surabhi Chaudhary — Wed, 23 Mar 2016 05:53:46 -0500

Trinity, developed at the Broad Institute and the Hebrew University of Jerusalem, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes. Briefly, the process works like so:

Inchworm assembles the RNA-seq data into the unique sequences of transcripts, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts.
Chrysalis clusters the Inchworm contigs into clusters and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full transcriptonal complexity for a given gene (or sets of genes that share sequences in common). Chrysalis then partitions the full read set among these disjoint graphs.
Butterfly then processes the individual graphs in parallel, tracing the paths that reads and pairs of reads take within the graph, ultimately reporting full-length transcripts for alternatively spliced isoforms, and teasing apart transcripts that corresponds to paralogous genes.

More at https://github.com/trinityrnaseq/trinityrnaseq/wiki

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Download Trinity here.

Build Trinity by typing 'make' in the base installation directory.

Assemble RNA-Seq data like so:

 Trinity --seqType fq --left reads_1.fq --right reads_2.fq --CPU 6 --max_memory 20G

Find assembled transcripts as: 'trinity_out_dir/Trinity.fasta'

Address of the bookmark: https://github.com/trinityrnaseq/trinityrnaseq/wiki

DISCOVAR

Abhimanyu Singh — Mon, 18 Apr 2016 11:59:16 -0500

DISCOVAR is a new variant caller and DISCOVAR de novo a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or longer — produced on MiSeq or HiSeq 2500 — and from a single PCR-free library. These data enable a level of completeness and continuity that was not previously possible.

DISCOVAR can call variants on a region by region basis, potentially tiling an entire large genome. DISCOVAR variant calling is under active development and transitioning to VCF.

DISCOVAR de novo can generate de novo assemblies for both large and small genomes. It currently does not call variants.

More at https://www.broadinstitute.org/software/discovar/blog/?page_id=14

Address of the bookmark: https://www.broadinstitute.org/software/discovar/blog/

HOMER: Software for motif discovery and next-gen sequencing analysis

Neel — Tue, 26 Apr 2016 03:48:23 -0500

This tutorial covers topics independently of HOMER, and represents knowledge which is important to know before diving head first into more advanced analysis tools such as HOMER.

Setting up your computing environment
Retrieving and storing sequencing files (your own data or from public sources)
Checking sequence quality, trimming, general sequence manipulation
Mapping reads to a reference genome
Manipulating SAM/BAM alignment files
Visualizing data in a genome browser

RNA-Seq

Microarray

Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor

General Tips for Data Analysis

Excel workarounds, adding gene annotation, X-Y plots tips, etc.

Address of the bookmark: http://homer.salk.edu/homer/basicTutorial/