BOL: Related items

Assistant Professor in Molecular Synthesis for Drug Discovery and Development @ CBMR, Lucknow

Wed, 30 Oct 2013 06:42:27 -0500

ADVERTISEMENT FOR FACULTY POSITIONS AT CENTRE OF BIOMEDICAL RESEARCH (CBMR), LUCKNOW

Details of the Positions and Pay Structure:

03 Posts for Assistant Professor in Molecular Synthesis for Drug Discovery and Development

Essential Qualifications and Requirements:

1. PhD in Synthetic Organic Chemistry/Medicinal Chemistry with research publications in high quality international journals and first class grade at the preceding degree from recognised University/Institute in India or abroad with consistently good academic record.
2. Three Yrs of Post-doctoral experience in relevant area.
3. Below 35 Yrs of age at the time of application

Desirable Experience: Candidates having strong research background in organic synthesis, total synthesis of structurally complex and medicinally important natural products/drugs related to cancer, neurodegenerative diseases (neurotropically active molecules for Alzheimer's, Parkinson’s, dementia etc) and infectious diseases such as malaria, TB etc. will be preferred.

Interested candidates may apply with:

1. Filled up Application Form (download from CBMR Website: http://www.cbmr.res.in) along with the Cover Letter, Curriculum Vitae including academic record (Bachelor degree onwards), awards, honours, list of Publications and reprints of 5 best publications.
2. Proposed research plan (max 3-4 pages).
3. Names and address (with valid e-mail and Phone number) of at least 3 academic referees.
4. Online Payment Receipt with transaction reference no. of Rs. 1000/- (USD 100 or equivalent foreign currency) on following details.
Account Number: 30054847814 Name: Director, Centre of Biomedical Research
Bank: STATE BANK OF INDIA, SGPGI Campus Branch, LUCKNOW

IFSC Code: SBIN0007789
MICR No: 22602034

Applications can be sent by registered/speed post or by e-mail to the following address:

The Director,
Centre of Biomedical Research (CBMR),
Sanjay Gandhi PGI Campus,
Raebareli Road, Lucknow-226014
e-mail: cbmr.admin@cbmr.res.in,
gp.pandey@cbmr.res.in

More Info:

http://www.cbmr.res.in/career/Advertisement%20for%20the%20post%20of%20Professors%20and%20Assistant%20Professors.pdf

vcfR: a package to manipulate and visualize VCF data in R

Jit — Thu, 25 Oct 2018 09:05:59 -0500

VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.

Address of the bookmark: https://github.com/knausb/vcfR

Junior Bioinformatic position

Wed, 26 Aug 2015 05:35:28 -0500

Junior Bioinformatic position in the laboratory of Inflammation and immunology in cardiovascular pathologies at Humanitas:

We are seeking a highly motivated young PhD student with strong interest in high throughput data analysis.
Detailed descriptions of our recent research activities may be found here:
http://www.humanitas-research.org/condorelli-gianluigi-md-phd/

Position is available starting from October/November. A probationary period of one month will be required.

Please send a CV along with a cover letter stating the reasons for applying and contact details of one or more referees to Dr. Paolo Kunderfranco (paolo.kunderfranco@humanitasresearch.it).

Tools for RNA classification

Abhi — Tue, 08 Nov 2022 03:39:11 -0600

barrnap - https://github.com/tseemann/barrnap

CPAT - https://github.com/liguowang/cpat, http://lilab.research.bcm.edu/ (web server)

CPC2 - https://github.com/gao-lab/CPC2_standalone, http://cpc2.gao-lab.org/ (web server)

Infernal - http://eddylab.org/infernal/, https://github.com/EddyRivasLab/infernal

NCBI RefSeq - https://www.ncbi.nlm.nih.gov/refseq/

Rfam - http://rfam.xfam.org/, https://docs.rfam.org/en/latest/index.html

SILVA - https://www.arb-silva.de/

RNAmmer - http://www.cbs.dtu.dk/services/RNAmmer/ (web server, standalone download link)

Project Fellow @ National Institute of Malaria Research

Tue, 12 Nov 2013 07:40:51 -0600

National Institute of Malaria Research

Sector 8, Dwarka, Delhi -110077

WALK IN INTERVIEW

One position of project fellow is to be filled up in a DRL- funded research project on Molecular and morphological characterization of An. fluviatilis in North-eastern states and bordering areas. The position is purely temporary for one year and can be extended

Essential qualifications

Master’s degree in any branch of Life Sciences with hands on experience in molecular biology and/or bioinformatics.

Age limit: 28 years, (relaxation for SC/ST/OBC candidates as per government of India rules)

Stipend: Rs.12, 000.00 per month (fixed)

Eligible candidates may walk in for an interview on 15 November 2013 at 11 AM at the above mentioned address along with a copy of CV (with a passport size photograph affixed), photocopies of all mark sheets/certificates and originals (for verifications). No TA/DA will be paid for attending the interview .Registration of candidates will start at 10:00AM and end at 10:45 AM.

Advertisement: http://www.mrcindia.org/vacancy/add-4.doc

Comprehensive list of visualization tools for biological pathways

Neel — Tue, 30 Jan 2018 06:01:31 -0600

The study of biological pathways is a key to understand the different processes inside a cell: proteins exert their function not in isolation but in a tightly controlled network of interactions and reactions. Activation of a pathway typically leads to a change of state in the cell. Pathways come in different flavors, depending on their functions in the cell – the three main types are metabolic pathways, gene regulatory pathways, and signaling pathways. These biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization.

Following are the comprehensive list of visualization tools for biological pathways:

BiNA

Drawings of metabolic networks supporting hiding of cofactors and drawing of chemical structures

http://bina.unipax.info/

BioTapestry

Interactive tool for building, visualizing and sharing gene regulatory network models over the web

http://www.biotapestry.org/

Caleydo

Visual analysis framework targeted at biomolecular data. Visualization of interdependencies between multiple datasets

http://www.caleydo.org/

CellDesigner

A modeling tool for biochemical networks

http://www.celldesigner.org/

Edinburgh Pathway Editor

Edit and draw pathway diagrams

http://epe.sourceforge.net/SourceForge/EPE.html

GenMAPP

Visualization of gene expression and other genomic data on maps representing biological pathways and groupings of genes

http://www.genmapp.org/

Ingenuity IPA

Data integration platform and manually annotated pathways

http://tinyurl.com/IngenuityPath

JDesigner

Graphical modeling environment for biochemical reaction networks

http://jdesigner.sourceforge.net/Site/JDesigner.html

KaPPA View

Plant pathways

http://kpv.kazusa.or.jp/

KEGG Atlas

Interactive Kyoto Encyclopedia of Genes and Genomes pathways

http://www.genome.jp/kegg/

Omix

Visualizing multi-omics data in metabolic networks

https://www.omix-visualization.com

PathVisio

Biological pathway analysis software that allows drawing, editing and analysis of biological pathways

http://www.pathvisio.org/

VitaPad

Application to visualize biological pathways and map experimental data to them

http://tinyurl.com/vitapad/

Web tools for pathways

ArrayXPath

Mapping and visualizing microarray gene-expression data and integrated biological pathway resources using SVG

http://tinyurl.com/ArrayXPath/

GEPAT

Integrated analysis of transcriptome data in genomic, proteomic and metabolic contexts

http://gepat.sourceforge.net/

iPath

Web-based tool for the visualization, analysis and customization of pathway maps

http://pathways.embl.de/

Kegg-Based Viewer

KEGG-based pathway visualization tool for complex high-throughput data

http://www.g-language.org/data/marray/

MapMan

User-driven tool that displays large datasets onto diagrams of metabolic pathways or other processes

http://mapman.gabipd.org/web/guest/mapman

MetPA

Analysis and visualization of metabolomic data within the biological context of metabolic pathways

http://metpa.metabolomics.ca

Omics Viewer

Data mapping on BioCyc pathways (collection of 5500 pathway/genome databases)

http://www.biocyc.org/

Pathway Explorer

Interactive Java drawing tool for the construction of biological pathway diagrams in a visual way and the annotation of the components and interactions between them

http://genome.tugraz.at/pathwayexplorer/pathwayexplorer_description.shtml

Pathway projector

Zoomable pathway browser using KEGG atlas and Google Maps API

http://www.g-language.org/PathwayProjector/

PATIKA

Integrated environment composed of a central database and a visual editor, built around an extensive ontology and an integration framework

http://www.cs.bilkent.edu.tr/~patikaweb/

Reactome SkyPainter

Visualization of over-represented pathways and reactions from gene lists

http://www.reactome.org/skypainter-2

WikiPathways

Wiki-based, open, public platform dedicated to the curation of biological pathways by and for the scientific community

http://www.wikipathways.org/

The Graveley Lab

Tue, 19 Nov 2013 18:02:48 -0600

Research in the Graveley lab is primarily focused on the regulation of alternative splicing and small RNA mediated gene regulation. These are fascinating and extraordinarily important mechanisms by which genes can be regulated. Our long-term goals are to understand how these processes are regulated at a mechanistic level and to understand the logic of these processes in significant biological settings. To achieve these goals, we strive to think outside the box to creatively attack the problems being addressed using a wide variety of approaches that include biochemistry, genetics, imaging, deep sequencing, large-scale RNAi screening and bioinformatics.

Lab page @ http://graveleylab.cam.uchc.edu/Graveley/index.html

List of visualization tools for genome alignments

Rahul Nayak — Fri, 02 Feb 2018 13:25:33 -0600

Genome browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and interpretation of results:

ABySS Explorer

Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata

http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer

BamView

Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation

http://www.sanger.ac.uk/resources/software/artemis/

DNannotator

Annotation web toolkit for regional genomic sequences

http://bioapp.psych.uic.edu/DNannotator.htm

JVM

Java Visual Mapping tool for NGS reads

http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501

LookSeq

Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation

http://lookseq.sourceforge.net

MagicViewer

Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome

http://bioinformatics.zj.cn/magicviewer/

MapView

Alignments of huge-scale single-end and pair-end short reads

http://omictools.com/mapview-s1367.html

MultiPipMaker

Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a ‘percent identity plot’ (pip)

http://pipmaker.bx.psu.edu/pipmaker/

PileLineGUI

Handling genome position files in NGS studies

http://sing.ei.uvigo.es/pileline/pilelinegui.html

SAMtools tview

Simple and fast text alignment viewer; NGS compatible

http://www.htslib.org/

SEWAL

Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run

http://www.sourceforge.net/projects/sewal

STAR

A web-based integrated solution to management and visualization of sequencing data

http://wanglab.ucsd.edu/star/browser

SVA

Software for annotating and visualizing sequenced human genomes

http://www.svaproject.org

Viewer (IGV)

Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution

https://www.broadinstitute.org/igv/

ZOOM Lite

NGS data mapping and visualization software

http://bioinfor.com/zoom/lite/

Ph.D. student in Computational Systems Biology

Tue, 10 Dec 2013 18:46:05 -0600

Ph.D. student in Computational Systems Biology

Location : The Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, Luxembourg, Luxembourg
Deadline for applications : unknown.
Description :

The Luxembourg Centre for Systems Biomedicine (LCSB) was created within the Health Technologies Initiative from the Government of Luxembourg as one of the research priorities of the University of Luxembourg. The LCSB is an Interdisciplinary Centre of the University that combines experimental and computational approaches to analyse complex biological systems and disease processes. The Computational Biology Group (CBG) provides the LCSB with a solid infrastructure in developing theoretical framework for computational modeling on biomedical problems, especially in the area of network biology in the context of cellular programming/reprogramming. The CBG group includes researchers with theoretical, computational and wet lab backgrounds, thereby providing an unusually interdisciplinary environment.
The Computational Biology Group seeks a highly-skilled Ph.D. student to work on an exciting project on reconstruction and analysis of an integrated gene regulatory network model to elucidate key mechanisms of cellular reprogramming. The model will rely on the integration and mining of diverse transcriptomics and epigenomics data of different cell types from the Central Nervous System. The Ph.D. student is expected to collaborate with other members of the CBG to develop a computational methodology aiming at designing, in-silico, cellular reprogramming events, with a focus on the nervous system. This project will be carried out in collaboration with Prof. Noel Buckleys lab at Kings College London.
Requirements of the ideal candidate:
Master degree in Bioinformatics, Computer Science, Biology or a related discipline
Prior experience in mathematical modelling of biological networks, especially in network inference and analysis
Excellent working knowledge in English.
.
We offer:
Full contract for Ph.D. student for three years with possibility of renewal
Opportunity to do applied research to medical problems within a highly dynamic research institution (LCSB) and in collaboration with internationally recognized partners
An exciting international environment
A very competitive salary

For further information, please contact:

Prof. Dr. Antonio del Sol
E-mail: antonio.delsol@uni.lu

Applications should contain the following documents:
A detailed curriculum vitae
cover letter mentioning the reference number
description of past research experience and future interests
name and addresses of three referees

All applications should be sent preferably in electronic version until December 31st, 2013 to the following address:

Luxembourg Centre for Systems Biomedicine (LCSB)
University of Luxembourg
7, avenue des Hauts-Fourneaux
L-4362 Esch-sur-Alzette
Tel: +352-466644-6982 (Office)
Email: antonio.delsol@uni.lu
http://www.lcsb.lu

Gap filling or Contigs extensions tools !

Rahul Nayak — Fri, 01 Jun 2018 08:07:32 -0500

There are many tools to perform gap filling using Illumina short reads, for example "GapFiller: a de novo assembly approach to fill the gap within paired reads" or "Toward almost closed genomes with GapFiller". There are also some tools like GAPresolution that can help to perform local re-assemblies using 454 reads. We used GAPresolution but it is not a very good software, it is useful only in some specific situations.

Take a look at the PRICE software from the DeRisi lab. Its meant to do something very similar. http://derisilab.ucsf.edu/index.php?page=software

You could also look at SSPACE (http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/sspacev12/), ATLAS tools (http://www.hgsc.bcm.tmc.edu/content/bcm-hgsc-software), and SCARPA (http://compbio.cs.toronto.edu/hapsembler/scarpa.html).

See the PAGIT protocol: http://www.sanger.ac.uk/resources/software/pagit/

In particular, take a look at the IMAGE tool: http://genomebiology.com/2010/11/4/R41

Also SOAPdenovo has ha function for scaffolding. Not sure about ABYSS

Here there is a useful explanation of several tools.

https://bioinformaticsonline.com/search?q=scaffolding&entity_type=object&entity_subtype=bookmarks&offset=0&search_type=entities

I could be wrong, but the above answers to your hypothetical scenario appear to miss the point that you aren't interested in assembling the full genome, just the 100 kb part you're interested in. I suggest the following algorithm:

1. Start with the initial assembly C0 of the contigs you have identified as overlapping your region of interest, and the set S of reads those contigs contain. Let C = C0.

2. Repeat:
a. Identify paired-end reads (not in C) for which one or both ends align within, or extending, contigs in C.
b. Identify unpaired reads that align extending these new paired-end reads.
c. Construct a new assembly C' from C and the new reads identified in (a) and (b).
d. Trim C' so it does not extend more than 100 kb to either end of C0. Set C = C'.
e. Let S' denote the reads that contribute to C'. If S' does not contain any reads not present in S, stop. Otherwise, Set S = S'.

3. If you don't have a complete assembly of the region of interest, generate an STS for each end of each contig, probe a library for clones including these STSes, subclone these clones into a paired-end sequencing vector, and generate paired-end reads for this library; then try steps (1) and (2) again, adding these new sequencing reads to what you had before.

4. If your average sequencing depth for the region of interest exceeds 25 or so without filling all gaps, it is likely that the remaining gaps represent sequences that are not getting cloned in your sequencing vectors. Try different sequencing vectors.