BOL: Related items

LoVis4u: Locus Visualisation tool for comparative genomics

LEGE — Tue, 17 Sep 2024 02:30:57 -0500

Description

LoVis4u is a bioinformatics tool for Loci Visualisation.

LoVis4u, a command-line tool and Python API designed for highly customizable and fast visualisation of multiple genomic loci. LoVis4u generates vector images in PDF format based on annotation data from GenBank or GFF files. It is capable of visualising entire genomes of bacteriophages as well as plasmids and user-defined regions of longer prokaryotic genomes. Additionally, LoVis4u offers optional data processing steps to identify and highlight accessory and core genes in input sequences.

https://art-egorov.github.io/lovis4u/

Address of the bookmark: https://github.com/art-egorov/lovis4u

Postgraduate Research Associate Bioinformatics / Computational Biology (Reference code: 59)

Tue, 04 Aug 2015 20:32:39 -0500

The Department of Biotechnology, group “Genome Bioinformatics” is currently seeking a Postgraduate Research Associate Bioinformatics / Computational Biology (Reference code: 59)

Extent of employment: 30 Hours per Week
Duration of employment: 1st of October 2015 to 30th of September 2019
Gross monthly salary and pay grade in terms of collective agreement for university staff (payable 14 times per year): B1, € 1.997,20

Responsibilities
The successful candidate (f/m) will pursue a Ph.D. project related to the interpretation of plant genome and transcriptome sequencing data from next-generation sequencing (NGS) platforms. In particular, the candidate will characterize the unexplored genome of quinoa, a crop plant of long-standing tradition in Latin America. We collaborate with research partners in Austria and abroad, and the candidate’s project will be of central importance in the context of this research network.

Required skills and qualifications
We are looking for a graduate student (f/m) with a Master’s degree in bioinformatics or in a related field, solid programming skills (e.g. developing sequence analysis tools), experience with the analysis of NGS data sets, understanding of lab methods and knowledge of genomics/transcriptomics. The group has successfully performed several projects using NGS technology. We have recently published the reference genome sequence of sugar beet (Dohm et al., Nature, 2014), a crop plant closely related to quinoa (same family, but different genus). Not yet published is a quinoa genome assembly that we have generated, and which will serve as the starting point of the candidate’s project. We are a multidisciplinary team and offer work in a lively and friendly atmosphere, and state-of-the-art computing infrastructure. We are looking forward to expanding our team by a dedicated and strongly motivated person with a distinct interest in the challenges of plant genomics.

Applications can be submitted until: 16th of August 2015

University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.

Please send your job application (incl. letter of motivation, CV, summary of Master’s thesis and contact details for two referees) to Personnel department, University of Natural Resources and Life Sciences, 1190 Vienna, Peter-Jordan-Straße 70; E-Mail: kerstin.buchmueller@boku.ac.at. (Reference code: 59)

We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.

www.boku.ac.at

Dr. Ken Buetow: IS & Personalized Medicine Lecture-Part 1

Sun, 29 Sep 2013 20:11:09 -0500

Full Lecture Abstract Creating an Evidence Engine to Support Personalized Medicine Personalized medicine is transforming biomedical research and healthcare service delivery. Disease definition, diagnosis, treatment, and prevention are being fundamentally altered by the capacity to routinely perform comprehensive molecular characterization. Nowhere is this change happening faster than in the field of cancer. Increasingly sophisticated technology provides the capacity to describe, in multiple molecular dimensions, the tumor and the individual in which it has developed. These technologies identify the millions of variants present in normal individuals and thousands of alterations that occur during the course of the disease process. The generation of this unprecedented amount of data presents us with the challenge contextualizing that data and converting into actionable information. Currently, the context is drawn from fragmented research literature generated by "siloed" reductionist basic science investigations, t incomplete outcomes of clinical research designed for regulatory approval, t out-of-date recommendations made by bodies of experts, and day-to-day clinical experience of the practitioner. The integration and interpretation of this complex multidimensional information into the evidence necessary to support clinical care exceeds the raw human cognitive capacity. Information systems have the capacity to provide the needed "tool" to tackle this challenge -- to generate the necessary evidence to support the delivery of personalized medicine. Arizona State University's (ASU) Complex Adaptive Systems team is building such an Evidence Engine in its Next Generation Cyber Capability (NGCC). The ASU NGCC -- composed of networks, hardware, software, and people transforms "Big Data" to information and creates the evidence necessary to enable personalized medicine. Bio Dr. Buetow currently serves as Director of Computational Sciences and Informatics within Arizona State University's (ASU) Complex Adaptive Systems Initiative (CASI). CASI applies systems approaches that leverage ASU's interdisciplinary research strengths to address complex global challenges. The Computational Sciences and Informatics program is developing and applying information technology to connect and enhance trans-disciplinary knowledge both within ASU and across the broader knowledge-generating ecosystem to address problems in biomedicine, the environment, and national security. Dr. Buetow previously served as the Director of the Center for Biomedical Informatics and Information Technology within the National Institutes of Health's National Cancer Institute (NCI). In that capacity he initiated and oversaw the NCI's efforts to connect the global cancer community through community-developed, standards-based, interoperable informatics capabilities that enable secure exchange and use of biomedical data. Buetow designed and built one of the largest biomedical computing efforts in the world. He was responsible for coordinating biomedical informatics and information technology. The NCI center he led focused on speeding scientific discovery and facilitated translational research by coordinating, developing and deploying biomedical informatics systems, infrastructure, tools and data in support of NCI research initiatives. The primary focus of the Buetow laboratory is the application of computational technologies to solve major biomedical challenges, particularly the role of genetics in complex human diseases such as cancer. It undertakes this mission through a systems approach in which genetic analytic approaches are applied to multiple high-throughput molecular characterizations integrated through informatics. The Buetow laboratory approaches diseases such as cancer as a complex adaptive system. The Buetow laboratory has a long history of developing and applying bioinformatics methods to find genetic components underlying complex traits. The laboratory was instrumental in the earliest studies developing and applying linkage disequilibrium methods as genetic mapping tools. The laboratory also developed methods and pipelines to generate and apply genome-wide genetic maps. In early work with genome-wide gene sequence data, the laboratory developed approaches to efficiently and accurately computationally identify variants. More recently, the analytic approaches have been extended to systematically identify insertion/deletion variation, translocations, and rearrangements. In application to transcriptome data, these methods facilitate identification of splicing and alternative transcripts. More information available at: https://sols.asu.edu/people/kenneth-buetow-0

Ensembl 77 has been released!

Seema Singh — Sun, 05 Oct 2014 16:38:58 -0500

New updates in e!77 !!

Updated human gene set (GENCODE 21)
Updated rat gene set including manual annotation from HAVANA
New species: Vervet-African green monkey
Imported Transcript Support Levels (TSLs) from UCSC for human and mouse
Imported APPRIS flag for human and mouse
Updated Amazon molly gene set

Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/

Orange-Bioinformatics 2.5.34

Robert M Willioms — Mon, 06 Oct 2014 12:51:37 -0500

Orange Bioinformatics extends Orange, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.

Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.

Address of the bookmark: https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34

JRF/SRF at University of Hyderabad

Fri, 17 Oct 2014 01:55:44 -0500

Applications are invited for the following post of Junior Research Fellow (temporary position coterminous with the project) under DBT funded research project on ““Understanding the functions of α1β1γ1/α2β1γ1 selective AMPK Modulators in dissecting the pharmacological role of these isozymes in metabolic diseases”

Qualified and interested candidates can send their curriculum vitae by e-mail to hr@drils.org on or before 27th October 2014 mention in the subject line of the mail the following code: AMPK-Biology.

Selected candidates will be called for a personal interview to Dr. Reddy’s Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad. The selected candidate is expected to report within two weeks from the date of selection to start work on the project.

Junior Research Fellowship (Molecular Modeling/Biology) for two years and Senior Research fellowship for one year

Junior Research Fellowship: Rs. 15,600/- (consolidated) per month for first two years.
Senior Research Fellowship: Rs. 18,200/-(consolidated) per month for the 3rd year.

Duration: The duration of the fellowship is for three years. However, the performance of the candidate will be reviewed after the completion of every year and the fellowship will be renewed only upon satisfactory performance.

Responsibilities:

1) Literature search.
2) Design, plan and execute experiments under the supervision of the scientist.
3) Provide scientific support to the scientist in his/her research activities.
4) Book keeping and maintenance of stocks and consumables.

Essential Qualifications:

Required: M.Sc. in Microbiology/Biotechnology/Bioinformatics or any other related branch of basic Sciences from a recognized university/institute with a consistent academic record of minimum 60% aggregate in all qualifying examinations. The candidate should be NET qualified for lectureship. The candidate should be motivated to work with dedication.

Desirable: expertise/experience in both Molecular Modeling and Molecular Biology.

Experience: 0-2 years in the areas of Molecular Modeling and/or Molecular Biology and cell biology and Biochemistry.

Preferable: Relevant research experience as evident from thesis/dissertation/project work.

Advertisement: http://www.ilsresearch.org/userfiles/Junior%20REsearch%20Fellowship%20-%20AMPK(Biology).pdf

Biinformamatics Lead at Google Life Sciences

Fri, 17 Oct 2014 02:24:55 -0500

Google Life Sciences is recruiting a technical lead with experience in bioinformatics and clinical bioinformatics, including for biomarker discovery projects such as the Baseline study.

Responsibilities

Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.
Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.
Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.
Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.
Create scientifically rigorous visualizations, communications, and presentations of results.

Reference @ https://www.google.com/about/careers/search#!t=jo&jid=62095001

dcGOR

Martin Jones — Sat, 08 Nov 2014 14:54:28 -0600

An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.

The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:

1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html

2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html

3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html

ICGEB Bioinformatics RA/SRF/JRF Vacancies

Thu, 13 Nov 2014 13:39:30 -0600

Research Associate/JRF/SRF position, DBT Sponsored Bioinformatics Infrastructure Facility

Applicants should hold a PhD or a first class MSc/MTech degree in Bioinformatics of Biotechnology/Life Sciences; experience in using bioinformatics tools, working in Linux and knowledge of computer network administration.

Submit CV and letter of interest by email to: Dr. Dinesh Gupta atdinesh@icgeb.res.in

NIAB Molecular Biology/Bioinformatics Scientist/RA Openings

Fri, 12 Dec 2014 21:08:47 -0600

D. No. 1-121/1, 4th and 5th Floors, Axis Clinicals Building, Miyapur, Hyderabad, Telangana, India- 500 049

Email: admin@niab.org.in Telephones: +91 40 2304 9403 Telefax: +91 40 2304 2740
Advertisement No: 5/2014

About NIAB National Institute of Animal Biotechnology (NIAB), Hyderabad, an autonomous institute under the aegis of Department of Biotechnology, Government of India, is aimed to harness novel and emerging biotechnologies and create knowledge in the cutting edge areas for improving animal health and productivity.

Applications are invited for the following temporary research positions to work in ongoing DBTBBSRC sponsored research project entitled “Transcriptome Analysis in Indian buffalo and the Genetics of Innate Immunity” at the National Institute of Animal Biotechnology, Hyderabad.

(A) Project Scientist – Level B (One Position)

Emoluments: Rs. 15600 + GP Rs. 5400 + 30 % HRA p.m. (Total emoluments will be Rs. 49,770/-p.m. for the duration of the project)

Essential Qualification: Candidates having M.V.Sc. in Veterinary Microbiology / Veterinary Pathology / Veterinary Public Health / Ph.D. degree in Life Sciences, Biotechnology, Molecular Biology or any other related field from the recognized university are eligible to apply.

The candidate should have a good academic record and research experience as evidenced from published in standard referred journals / patents.

Desirable: Candidates having research experience in the area of tissue culture, genomics, Transcriptomics and Advanced Molecular Biology will be given preference.

Age Limit: Not exceeding 30 years as on last date of the submission of the application.

(B) Research Associate in Bioinformatics (One position)

Fellowship: Rs. 22,000 + 30 % HRA

Essential Qualification: Candidates having Ph.D. degree or M.Tech. with three years of
experience in Bioinformatics, Computational Biology, Biotechnology, Life Sciences or any other related field are eligible to apply.

Desirable: Candidate having research experience in the area of next generation sequencing (NGS) data analysis, Genome wide association studies, Genomic selection, advance genomic data analysis etc., will be given preference. The candidate should have a good academic record and research experience as evidenced from published papers in standard journals / patents.

Age Limit: Not exceeding 30 years as on last date of the submission of the application.

Project Duration: The duration of the project is Three years and the positions are co- terminus with the duration of the project. (Initial appointment will be for one year and further extension will be granted based on annual review).

Mode of submission of application: Only online applications are to be submitted through
www.niab.org.in on or before 08 December, 2014. Link for online submission of applications will be available from 10 November 2014.

Advertisement: www.niab.org.in/Notifications/Advt_5_2014/Advt_5_2014.pdf