BOL: Related items

BINC (Bioinformatics National Certification) Examination 2018

Jit — Mon, 23 Apr 2018 03:34:53 -0500

Bioinformatics National Certification (BINC) was instituted by Department of Biotechnology, Government of India in 2005 at Savitribai Phule Pune University, formerly University of Pune, Pune to certify bioinformatics professionals and recognizing candidate's theoretical and practical ability and fostering interdisciplinary research. Later on, it was transferred to Jawaharlal Nehru University, New Delhi and then to Pondicherry University, Puducherry. Pondicherry University conducted the BINC examination in 2015, 2016 and 2017.

Biotech Consortium India Limited (BCIL), New Delhi is conducting the BINC 2018 examination on behalf Department of Biotechnology, Government of India.

BINC is a certification programme for graduate and post-graduate students for recognizing their exceptional bioinformatics knowledge and skills and to improve their employment opportunities. There is a growing need for trained manpower in the area of Bioinformatics. Currently, various universities and institutions, both government and private, impart Bioinformatics education in India. The qualifying candidates will be awarded a lifetime certificate. This certification would facilitate industries and potential employers in recruitment of Bioinformatics professionals having exceptionally good bioinformatics skills.

The certification under Bioinformatics National Certification (BINC) scheme is given to the candidates after three tier selection process. The successful candidates are also eligible for availing Junior Research Fellowship (JRF) for pursuing Ph.D. in Bioinformatics at recognized Indian universities/institutes. The research fellowships of all BINC qualified Indian nationals are funded by DBT. BINC qualified candidates are called DBT certified Bioinformaticians while the individuals availing the fellowships are called as DBT-BINC Junior Research Fellows (DBT-BINC-JRF). Cash prize of 10,000/- each is awarded to the top 10 BINC qualifiers.

Eligibility

i) Bachelor's/Master's degree in Life Sciences, Physical Sciences, Chemical Sciences, Mathematical Sciences, Agriculture, Veterinary, Medicine, Pharmacy, Engineering and Technology.

ii) No formal training, diploma or certificate in bioinformatics is required.

iii) Candidates in final year of Bachelor's/ Master's degree are also eligible to apply.

Pattern of Examination

Syllabus

The syllabus consists of six sections - Bioinformatics, Biology, Physical Science, Chemical Science, Mathematics & Statistics, and Information Technology.

Note: Paper-III will be computer based practical and will include programming on Bioinformatics

Important Dates

Examination Centers

BINC Fellowship

Forms & Downloads

FAQs

Contact Us

Nisha Singh
Biotech Consortium India Limited
(CIN: U73100DL1990PLC041486)
5th Floor, Anuvrat Bhawan 210, Deen Dayal Upadhyaya Marg New Delhi - 110 002
Tel.: 011-2321 9064-67 Ext. 231, 236
Email - For general BINC queries:binc.dbt@biotech.co.in
Helpline for Application submission related queries:binchelpdesk@biotech.co.in
Website: www.bcil.nic.in/BINC.html

Understanding GO analysis

Neel — Wed, 08 Feb 2023 04:22:01 -0600

The confusion about gene ontology and gene ontology analysis can start right from the term itself. There are actually two different entities that are commonly referred to as gene ontology or “GO”:

the ontology itself, which is a set of terms with their precise definitions and defined relationships between them, and
the associations between gene products and GO terms, which are used to capture the existing knowledge about what each gene is known to do.

But the term gene ontology, or GO, is commonly used to refer to both, which is sometimes a source of potential confusion. In order to avoid this, here we will use the term “GO ontology” to describe the set of terms and their hierarchical structure and “GO annotations” to describe the set of associations between genes and GO terms.

There are 3 types of terms, or domains if you wish, in the gene ontology:

Biological Processes (BP)
Molecular Functions (MF)
Cellular Components (CC)

Address of the bookmark: https://advaitabio.com/faq-items/understanding-gene-ontology/

Interview Puzzles for Bioinformatician !

Rahul Nayak — Tue, 17 Jul 2018 05:26:18 -0500

These are some of the most famous Interview Puzzles being asked in top tech companies.

Here is a list of Top 25 puzzles which have been asked in top Tech Interview.

Specially for Microsoft Interview Puzzles, you may refer,
Top 15 Microsoft Interview Puzzles
Microsoft Interview Puzzles

Other MOST COMMON Interview Puzzles-
Top 25 Tech Interview Logical Puzzles

Each of the puzzles got repeated a number of times in interviews even for top tech companies

DIY Transcriptomics

Abhi — Wed, 31 Jul 2024 01:19:26 -0500

A semester-long course covering best practices for the analysis of high-throughput sequencing data from gene expression (RNA-seq) studies, with a primary focus on empowering students to be independent in the use of lightweight and open-source software using the R programming language and the Bioconductor suite of packages. This course follows a hybrid format in which online lectures are paired with in-person labs where students participate in hands-on, live coding exercises using real ‘omic datasets. The course is focused on datasets and topics central to infectious disease research, immunology, and One-Health, but the concepts and approaches covered are applicable to any genomic study.

https://diytranscriptomics.com

Address of the bookmark: https://diytranscriptomics.com

Bioinformatics Programme Officer @ International Centre for Genetic ICGEB Engineering and Biotechnology

Fri, 23 Nov 2018 03:50:16 -0600

The following vacancies are available in the DBT Apex Biotechnology Information project at ICGEB, New Delhi, India. These positions are available for a period of approx. two years, however, initial appointment offer will be for 6 months, which will be extended based on performance of work. Salaries will be offered as per DBT, educational qualification and experience. Depending on requirements, selected candidates may be required to work on location from the Department of Biotechnology, New Delhi. Shortlisted candidates will be invited for an interview at ICGEB. Only the selected candidates will be informed individually. No TA/DA or accommodation will be offered to the candidates attending the interview.

4 Programme Officer 1
5 Technical Research Assistant 1

Minimum Educational Qualification, desirable experience and expected duties:

4: The applicants should be Postgraduates with experience in Data collection and Statistics, especially in Biotechnology-related data.

Expected duties: Collection of Biotechnology related information from India, to facilitate the Apex BTIC experts committee review of programmes at centres and R&D programs funded by DBT.

5: The applicants should be Postgraduates in Science with experience in Bioinformatics-related projects.
Expected duties: The candidates will assist the senior staff of the centre in daily activities and help in the preparation of the Annual Training Calendar, seminar and training podcasts/videos, repository of training material and Apex BTIC Newsletter.

Interested candidates should submit their full, updated Curriculum Vitae with a detailed description of relevant experience, along with two references by December 14th, 2018, addressed to, The Chairperson, DBT- Apex BTIC, ICGEB, Aruna Asaf Ali Marg, New Delhi 110067, Email: abtic@icgeb.res.in, kindly write “Application for DBT Apex BTIC vacancy” in the subject of the email or envelope, if sending by post.

Advertisement: http://www.icgeb.org/tl_files/Vacancies/dbt-abtic-vac-annmntrevsk.pdf

PeGAS: A Comprehensive Bioinformatic Solution for Pathogenic Bacterial Genomic Analysis

LEGE — Mon, 01 Sep 2025 01:18:10 -0500

This is PeGAS, a powerful bioinformatic tool designed for the seamless quality control, assembly, and annotation of Illumina paired-end reads specific to pathogenic bacteria. This tool integrates state-of-the-art open-source software to provide a streamlined and efficient workflow, ensuring accurate insights into the genomic makeup of pathogenic microbial strains.

Address of the bookmark: https://github.com/liviurotiul/PeGAS

Thank You Email After Bioinformatics Interview !

Jit — Tue, 08 Jan 2019 15:37:33 -0600

A good interview thank you email or note should contain three essential pieces:

a) Show appreciation for their time and thank them

b) Mention something specific you talked about in the interview, so they know it’s not a cut & paste email

c) Express interest in the position and tell them you’re excited to learn more

d) Invite them to contact you if they have any questions/concerns, or need clarification on anything discussed

First sample:

Dear Dr XYZ
I enjoyed speaking with you today about the XXX position at the X Lab, Uni. The job seems to be an excellent match for my skills and interests.

The lab loaded with new updated technology and international experts, that you informed while interviewing confirmed my desire to work with X lab.

In addition to my enthusiasm, I will bring to the position strong writing skills, assertiveness, and the ability to encourage others to work cooperatively with the group

I appreciate the time you took to interview me. I am very interested in working with you and look forward to hearing from you regarding this position.

Sincerely,
XXX

Second sample:

Dear Dr XXX,
I wanted to take a second to thank you for your time . I enjoyed our conversation about and enjoyed learning about the position overall.
It sounds like an exciting opportunity, and an opportunity I could succeed and excel in! I’m looking forward to hearing any updates you can share, and don’t hesitate to contact me if you have any questions or concerns in the meantime.
Thanks again for the great conversation .
Best Regards,
XXX

Single Cell RNAseq data analysis tutorial !!

Robert M Willioms — Mon, 27 Nov 2017 16:24:29 -0600

A major breakthrough (replaced microarrays) in the late 00’s and has been widely used since
Measures the average expression level for each gene across a large population of input cells
Useful for comparative transcriptomics, e.g. samples of the same tissue from different species
Useful for quantifying expression signatures from ensembles, e.g. in disease studies
Insufficient for studying heterogeneous systems, e.g. early development studies, complex tissues (brain)
Does not provide insights into the stochastic nature of gene expression

Following are the useful links:

Single Cell RNAseq data analysis Tutorial

A step-by-step workflow for low-level analysis of single-cell RNA-seq data

A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

SCell: single-cell RNA-seq analysis software

https://github.com/diazlab/SCell

Beta-Poisson model for single-cell RNA-seq data analyses

https://github.com/nghiavtr/BPSC

Sincera: A Computational Pipeline for Single Cell RNA-Seq Profiling Analysis

https://research.cchmc.org/pbge/sincera.html

SC3 – consensus clustering of single-cell RNA-Seq data

http://biorxiv.org/content/early/2016/09/02/036558

Citrus: A toolkit for single cell sequencing analysis

http://biorxiv.org/content/early/2016/09/14/045070

Single-Cell Resolution of Temporal Gene Expression during Heart Development

http://www.cell.com/developmental-cell/fulltext/S1534-5807(16)30682-7

Scalable latent-factor models applied to single-cell RNA-seq data separate biological drivers from confounding effects

http://biorxiv.org/content/early/2016/11/15/087775

Single cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes

http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract

SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

http://biorxiv.org/content/early/2016/11/21/088856

SCOUP is a probabilistic model to analyze single-cell expression data during differentiation

https://github.com/hmatsu1226/SCOUP

scLVM is a modelling framework for single-cell RNA-seq data

https://github.com/PMBio/scLVM

Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories

https://github.com/jw156605/SLICER

SinQC: A Method and Tool to Control Single-cell RNA-seq Data Quality

http://www.morgridge.net/SinQC.html

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

https://github.com/zji90/TSCAN

Visualization and cellular hierarchy inference of single-cell data using SPADE

http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html

OEFinder: Identify ordering effect genes in single cell RNA-seq data

https://github.com/lengning/OEFinder

Bioinformatics Services / CRO Services

RASA Life Sciences — Wed, 06 Nov 2019 00:33:11 -0600

RASA is set to provide premium technical and scientific services in a form of solutions, product development and training. .We are also very proficient in providing the high quality Research & Development services in life science informatics field like Next Generation Sequencing (NGS) Data Analysis,Computational Drug Discovery, Bioinformatics, Chemo-informatics and BIO-IT.

RASA offers faster, better and cost effective cutting edge technology solutions to chemical and life science research and industry. We provide our customers with A seamless model of wide expertise and comprehensive platforms. Our Value is to take our customers

3 PhD positions available in the area of Bioinformatics/Computational Biology at ulster.ac.uk

Thu, 02 Jan 2020 12:41:10 -0600

3 PhD positions available in the area of Bioinformatics/Computational Biology, Machine Learning (ML)/Artificial Intelligence (AI), Biomarker Discovery, Stratified/Personalized Medicine in Mental Health, Diabetes and Multimorbidity. Please see details (weblinks) below:

1. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/510894
2. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/511458
3. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/512618

Looking for students with good computational/programming skills (preferable in Linux/Shell, Python and/or R) and knowledge in computational biology and statistics. However, students from more biology oriented background but strong interest to learn bioinformatics and programming are also encouraged to apply.

Informal inquiries are welcomed at: p.shukla@ulster.ac.uk

Dr Priyank Shukla PhD FHEA FCHERP
Lecturer (Asst Prof) in Stratified Medicine (Bioinformatics)

Northern Ireland Centre for Stratified Medicine
Biomedical Sciences Research Institute
University of Ulster (Magee Campus)
C-TRIC Building, Altnagelvin Area Hospital
Glenshane Road, Derry/Londonderry
BT47 6SB, Northern Ireland, United Kingdom

T: +44 28 7167 5690
E: p.shukla@ulster.ac.uk
W: https://www.ulster.ac.uk/staff/p-shukla