BOL: Related items

PhD at University of Calgary

Fri, 27 Dec 2013 20:24:39 -0600

Institution/Company:
University of Calgary
Location:
Calgary, AB
Job Description:

Novel diagnostic platform for detection of Osteoarthritis

I invite applications from highly motivated individuals to join my laboratory as a PhD student in Systems Biology at the University of Calgary McCaig Institute for Bone and Joint Health. This project is aimed at characterizing the networks of physical (protein-protein) interactions underlying inflammatory processes in patients with Osteoarthritis and how this differs from patients with Rheumatoid Arthritis and normal individuals. This work will eventually lead to the development of a novel diagnostic platform for the non-invasive and accurate detection of early Osteoarthritis. The selected candidate will use state-of-the-art computational methodologies to systematically analyze proteomic data, and develop /implement new algorithms to identify protein and functional interaction networks from high throughput experimental data. The individual will also benefit by working closely with experts at the UofC and UofA through an AIHS Alberta Osteoarthritis Team Grant which includes experts from all pillars of health research. The candidate will also be supported to attend bioinformatics workshops and conferences to advance and disseminate their research.
Qualifications: The ideal candidate will have a Master’s degree in Computational Biology, Bioinformatics, or equivalent with strong background knowledge of the Biological Sciences, Biochemistry, and Microbiology. The individual should additionally have experience in handling high-throughput data sets as well as programming skills. The candidate will be registered as a PhD student in Dr. Krawetz’s laboratory, located in the new state-of-the-art Health Research Innovation Centre at the UofC. The individual will have strong verbal and written skills and the ability to work efficiently in a team environment.

In addition to the outstanding research opportunities available in this setting, students also enjoy the many cultural and sporting amenities provided in the city of Calgary, and can take advantage of the unparalleled skiing and hiking in the Rocky Mountains that are less than an hour away.

Candidates must be academically competitive and will be expected to apply for external funding. The stipend is $25,000/yr. For outstanding PhD students, internal top-up award opportunities are available on a competitive basis. If interested in joining the lab, please contact Dr. Krawetz directly at rkrawetz@ucalgary.ca and provide the following information:

- Short cover letter explaining your interest in the lab
- Resume
- Scanned copy of transcript or listing of course grades
- Names and contact information for two individuals who will be willing to provide letters of reference

Scientist-B (Bioinformatics) at AIIMS, Delhi

Sun, 20 Dec 2020 04:34:55 -0600

Name of the Project: “Artificial intelligence in Oncology, Harnessing big data and advanced computing to provide personalized diagnosis and treatment for Cancer patients”

Age Limit: 35

How to Apply for the AIIMS Life Science Job:

Interested applicants are asked to send out a detailed CV to Dr Ashok Sharma (aioncoaiims@gmail.com). Laboratory of Chromatin and also Cancer Epigenetics, Department of Biochemistry with the subject line “Application for Scientist-B position for MeitY project” latest by January 01st, 2021.
Complete Information of the year of passing, experience, marks, etc. ought to be mentioned in the CV Incomplete. applications will certainly be rejected Just shortlisted applicants will be called for interview. Chosen candidates will certainly be intimated by email/phone.
No TA/DA will certainly be paid for appearing in the interview.
Note, The institute reserved the right to fill up or not to fill up the post advertised.

Emoluments: Rs. 56,000/- plus 24 percent HRA

Eligibility:
2nd class Master’s Degree with a PhD in a pertinent subject (Bioinformatics) from.a recognized University
1st class Master’s degree in Life Sciences (Bioinformatics) from a recognized university OR.
Bachelor’s Degree in Engineering or-Technology with minimal 60% marks from a recognized University or equivalent.

Desirable Qualifications:
Experience in Bioinformatics/NGS data. Analysis/System Biology/Computer Science/ statistics with experience in Machine learning/Al project.
Experience of Deep learning applications in biological data ( image/text).
Proficient in Rf Python machine learning libraries.
Prior experience in the cancer-related project (ML-based) will be advantageous.
Experience with PyTorch/TensorFlow will certainly be very desirable.
Applicant should have strong scientific writing as well as. verbal abilities.
Papers in sci-indexed journals demonstrating ML skill sets.
Database handling will certainly be plus yet not required.

More detail at https://www.aiims.edu/images/pdf/recruitment/advertisement/biochem-16-12-20.pdf

Postdoc positions in computational biology - Center for Genomic Science - Milan, Italy

Thu, 12 Dec 2013 18:34:47 -0600

Job Description: three postdoc positions in computational biology are available at the Center for Genomic Science in Milan (Italy):

- Development of computational methods to investigate the interplay between epigenetic and genetic layers and their role in tumor progression, by integrating genomic, epigenomic and transcriptional data. PI: Mattia Pelizzola (http://tiny.cc/comEpi)
- Epigenome and transcriptome analysis in mouse models of Hepatocellular Carcinoma. PI: Bruno Amati - Small and long non-coding RNAs in cancer stem cells. PI: Francesco Nicassio

All projects will benefit from the availability of both in-house and publicly available next-generation sequencing datasets. Familiarity with Linux environment, programming skills (especially in R) and a background in either computational biology, or physics/engineering/math will be advantageous.

Deadline for the application January 6th, to apply: http://genomics.iit.it/resources.html

Start date: March 1st, 2014

Duration: 1+2 years

Contact Person (Referent): Mattia Pelizzola

Ref. E-Mail: mattia.pelizzola@iit.it

Tel: 0039-02-94375058
Group Web Page: http://genomics.iit.it

Postdoctoral scientist genome analytics/ genome bioinformatics (m/f/*)

Sun, 16 Feb 2020 02:57:40 -0600

https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html
Your profile:
Degree in bioinformatics, biostatistics, or equivalent
Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance computing
Strong competence in working in Unix/Linux environments (shell)
Strong programming skills (in particular: Python, R, Perl)
Experience with using git and snakemake
Fluent English language skills, both spoken and written
Strong communication skills and motivation to work in a young, interdisciplinary, dynamic team

Additional Information:

If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).

Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).

Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.

Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.

EMBO practical Course on "Bioinformatics and Genomes Analyses" at Hellenic Pasteur Institute, Athens, Greece

Sat, 21 Dec 2013 10:00:24 -0600

The main objectives of this Practical Course are to strengthen skills
of PhD students and young researchers in the domain of Bioinformatics
and Genome Data Analyses on the use of advanced fundamental algorithms
and their applications in genome studies.

The course topics will include theoretical and practical aspects in:
- Genomes comparisons,
- Evolutionary analyses (orthologs, paralogs and ancestral genomes
inference),
- RNAseq and Next Generation Sequencing (including algorithms, methods
and sequence mapping tools, data analyses and applications).

The course programme will be centred on theoretical presentations
followed by practical sessions. Practical sessions in a Linux
environment will involve Unix shell and Perl scripting. Participants
are assumed to be familiar with this environment.

A series of lectures delivered by prominent scientists on recent hot
topics in genome (Viruses, Prokaryotes, Eukaryotes) studies will be
included in the programme and future research perspectives will be
highlighted.

The topics that will be included in the course programme are similar
to those included in previously organized courses:http://www.pasteur.fr/~tekaia/BGA_courses.html

The course is aimed at motivated Ph.D students and Post-Doctoral
Researchers in Academic Institutions, with background in Mathematics,
Statistics, Biology or Computer Science and who are involved in
Bioinformatics and Genomes studies.

Selection of participants will be based on their background, running
research projects and on expressed motivations.
Selected students will have free accommodation and meals and are
expected to contribute with 200 euros and to pay for their travel
expenses.
All participants (students and invited speakers) will stay in the same
hotel.

Detailed indications are available on the course web site: http://events.embo.org/14-comparative-genomics/index.html

Candidates are advised to complete carefully the application form,
together with an abstract of at least one of their running projects, a
"one-page CV" and a personal Identity Picture (Photo).

The application deadline is March 14, 2014.

The organizers:
Menelaos Manoussakis, Hellenic Pasteur Institute, Athens, Greece.
Evdokia Karagouni, Hellenic Pasteur Institute, Athens - Greece.
Evie Melanitou, Institut Pasteur Paris - France.
Fredj Tekaia ( Institut Pasteur Paris France)
URL: http://www.pasteur.fr/~tekaia/BGA_courses.html

Date: 5 – 17 May, 2014.
More at http://events.embo.org/14-comparative-genomics/index.html
will take place in the ,

Choosing the Right NGS Sequencing Instrument for Your Study

Neel — Wed, 15 Jun 2022 00:37:29 -0500

The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared metrics for each of the instruments available. If you’re new to high-throughput sequencing and have questions about how you should design your sequencing run, fill out our free consultation form and we'll get in touch with you to help.

More at https://genohub.com/ngs-instrument-guide/

Address of the bookmark: https://genohub.com/ngs-instrument-guide/

Oldest Hominin DNA Sequenced

Surajeet — Fri, 27 Dec 2013 19:58:31 -0600

Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.

From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.

Reference

http://www.sciencedaily.com/releases/2013/12/131204132018.htm

Common steps for reads mapping !

BioStar — Thu, 09 Mar 2023 02:48:02 -0600

Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis. Here are some general steps to follow for mapping reads to a genome:

Choose a read mapper: There are many read mappers available, such as BWA, Bowtie, and HISAT2. Choose a mapper that is appropriate for your type of data and research question.
Index the reference genome: Before mapping reads, the reference genome needs to be indexed. This involves creating an index of the genome sequence that allows the mapper to quickly find matches to the reads. Most mappers have their own indexing tools.
Prepare the read data: The reads should be in a format that is compatible with the mapper. Most mappers accept FASTQ or BAM files. Depending on the quality of the data, it may need to be filtered or trimmed before mapping.
Run the mapper: The mapper is run with the command-line interface or using a graphical user interface. The specific command depends on the mapper being used, but typically involves specifying the input data, reference genome, and output file format.
Evaluate the mapping results: After the mapping is complete, the results should be evaluated. This includes assessing the quality of the mapping, such as the mapping rate, the number of mapped reads, and the mapping quality score.
Post-processing: Depending on the analysis being performed, post-processing of the mapped reads may be necessary. This can include filtering reads based on quality, removing duplicate reads, and calling variants.

Overall, mapping reads to a reference genome is a complex process that requires careful consideration of the type of data, the research question, and the specific mapper being used.

List of bioinformatics open source projects/software.

Rahul Nayak — Tue, 21 Jan 2014 14:28:37 -0600

Open source software is software that can be freely used, changed, and shared (in modified or unmodified form) by anyone. Open source software is made by many people, and distributed under licenses that comply with the Open Source Definition.The Open Source Initiative (OSI) is a global non-profit that supports and promotes the open source movement. Followings are the OS bioinformatics projects/software :

.NET Bio

http://blogs.msdn.com/b/msr_er/archive/2011/10/18/microsoft-biology-foundation-evolves-into-new-toolkit-net-bio.aspx

A language-neutral bioinformatics toolkit built using the Microsoft 4.0 .NET Framework to help developers, researchers, and scientists.

AMPHORA ("AutoMated Phylogenomic infeRence Application")

http://wolbachia.biology.virginia.edu/WuLab/Software.html

Metagenomics analysis software

Anduril

http://www.anduril.org/anduril/site/

Component-based workflow framework for data analysis

Armadillo workflow platform

Tool for designing and executing phylogenetic workflows

AutoDock

http://autodock.scripps.edu/

suite of automated docking tools

Biochemical Algorithms Library (BALL)

http://www.ball-project.org/

C++ library and framework for molecular modeling and visualization designed for rapid prototyping

Bio4j

http://bio4j.com/

Bio4j is a bioinformatics platform and graph based database built around most data available in UniProt KB(Swiss-Prot + TrEMBL), Gene Ontology (GO), UniRef (50,90,100), RefSeq, NCBI taxonomy, and Expasy Enzyme DB

Bioclipse

www.bioclipse.net

Visual platform for chemo- and bioinformatics based on the Eclipse Rich Client Platform (RCP).

Bioconductor

http://www.bioconductor.org/

R (programming language) language toolkit

Bioinformatics Learning Tutorial (BLT)

http://sourceforge.net/projects/biotutorial/

Educational interactive tutorials and 3D animations for Replication, Transcription, and Translation

BioHaskell

http://biohaskell.org/

Haskell (programming language)

BioJava

http://biojava.org/wiki/Main_Page

Java (programming language)

BioMOBY

http://biomoby.org/

registry of web services

BioPerl

http://www.bioperl.org/wiki/Main_Page

Perl language toolkit

BioPHP

http://www.biophp.org/

PHP language toolkit

Biopython

http://biopython.org/wiki/Main_Page

Python language toolkit

BioRails

https://github.com/biorails

a data management system designed to support researchers in drug discovery

BioRuby

http://bioruby.org/

Ruby language toolkit

BioSmalltalk

https://code.google.com/p/biosmalltalk/

Smalltalk language toolkit

BioUno

http://www.biouno.org/

BioUno is a project that applies Continuous Integration tools and techniques in Bioinformatics. It uses Jenkins and its plug-in API to create biology workflows and manage computer clusters.

caCORE

ontologic representation environment

caArray

https://cabig-stage.nci.nih.gov/community/tools/caArray

ontologic representation environment

EMBOSS

http://emboss.sourceforge.net/

Suite of packages for sequencing, searching, etc.

Gaggle

https://www.gaggle.net/

A framework for interoperability between systems biology software

Galaxy

http://galaxyproject.org/

Scientific workflow and data integration system

GenePattern

http://www.broadinstitute.org/cancer/software/genepattern/

Scientific workflow system that provides access to more than 150 genomic analysis tools

GeWorkbench

http://wiki.c2b2.columbia.edu/workbench/index.php/Home

Genomic data integration platform

GMOD

http://www.gmod.org/wiki/Main_Page

Toolkit for addressing many common challenges at biological databases.

GeneProf

http://www.geneprof.org/GeneProf/

A web-based, bioinformatics software suite for the analysis of functional genomics experiments, e.g. RNA-seq or ChIP-seq.

GeneTalk

http://www.gene-talk.de/

Tool for filtering sequence variants in VCF files. Network for scientists and clinicians for expertise and knowledge exchange. Database of annotations aboute sequence variants with clinically relevant information.

GenGIS

http://kiwi.cs.dal.ca/GenGIS/Main_Page

Application that allows users to combine digital map data with information about biological sequences collected from the environment.

GenomeSpace

http://www.genomespace.org/

Centralized web application that provides data format transformations and facilitates connections with other bioinformatics tools

GENtle

http://directory.fsf.org/wiki/GENtle

An equivalent to the proprietary Vector NTI, a tool to analyze and edit DNA sequence files

Integrated Genome Browser

http://bioviz.org/igb/

Java-based desktop genome browser

Integrative Genomics Viewer (IGV)

http://www.broadinstitute.org/igv/

High-performance desktop tool for interactive visual exploration of diverse genomic data

IntAct

http://www.ebi.ac.uk/intact/

molecular interaction database

InterMine

http://intermine.github.io/intermine.org/

Extensive data warehouse system for the analysis and integration of biological datasets

Java Treeview

http://jtreeview.sourceforge.net/

microarray data viewer

LabKey Server

http://labkey.com/

platform for integrating, analyzing and sharing data

OpenClinica

https://www.openclinica.com/

software for capturing and managing data in clinical trials

PromKappa

http://xbioinformatics.wordpress.com/tag/promkappa/

PromKappa (Promoter analysis by Kappa) software program used for promoter pattern generation and promoter analysis.

MeV: Multi-Experiment Viewer

http://www.tm4.org/mev.html

a desktop application for the analysis, visualization and data-mining of large-scale genomic data

PathVisio

http://www.pathvisio.org/

a desktop software for drawing, analysis and visualization of biological pathways

REDCRAFT

software for determining tertiary protein structure given assigned Residual Dipolar Coupling data

SAM Tools

Data format (SAM) and accompanying tool suite, for storing large nucleotide sequence alignments

Staden Package

Sequence assembly, editing and analysis, primarily consisting of gap4, gap5 and spin.

STAMP

Software package for analyzing metagenomic profiles that promotes ‘best practices’ in choosing appropriate statistical techniques and reporting results.

supraHex

An open-source R/Bioconductor package for omics data analysis using a supra-hexagonal map

Taverna workbench

Tool for designing and executing workflows

TGAC Browser

Genome Browser, visualisation solutions for big data in the genomic era

T-REX WebServer

Bioinformatics and phylogenetics webserver (NJ, PhyML, RAxML, MAFFT, MUSCLE, Newick viewer, Horizontal gene transfer detection, Reticulograms, Substitution models)

UGENE

integrated bioinformatics tools

Visomics

bioinformatics tools for omics data

Genome Analysis Toolkit 1.0 (GATK 1.0)

a software package to analyse next-generation resequencing data

1mb long DNA with Nanopore technology

Jit — Tue, 19 Dec 2017 18:49:28 -0600

The first continuous DNA read of more than a million bases (>1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO