BOL: Related items

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

RNAseq data analysis links !

Robert M Willioms — Mon, 27 Nov 2017 16:28:11 -0600

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.

A survey of best practices for RNA-seq data analysis

RNA-seq workflow: gene-level exploratory analysis and DE

RNAseq analysis notes from Tommy Tang

Analysis of RNA ‐ Seq Data

RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

EBI RNA-Seq exercise

An open RNA-Seq data analysis pipeline tutorial with an example

RNA-Seq Analysis Workflow

Transcript-level expression analysis of RNA-seq experiments

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

Data Steward / Research & Development Specialist at at the Luxembourg Centre for Systems Biomedicine (LCSB)

Sun, 25 Oct 2020 22:36:38 -0500

Applications should be addressed online to: Prof. Dr. Reinhard Schneider, Head of the Bioinformatics Core Facility

For further information, please contact: Dr. Pinar Alper (pinar.alper@uni.lu)

Applications should be submitted online and include:

A detailed curriculum vitae
Cover letter mentioning the reference number
List of publications/software projects
Description of past experience and future interests
Names and addresses of three referees
Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered.

*gn=gender neutral.

More at https://recruitment.uni.lu/en/details.html?nPostingId=54616&nPostingTargetId=74219&id=QMUFK026203F3VBQB7V7VV4S8&LG=UK&mask=karriereseiten&sType=Social%20Recruiting

EGAD: Ultra-fast functional analysis of gene networks

Rahul Nayak — Fri, 14 Dec 2018 04:10:35 -0600

With the EGAD (Extending ‘Guilt-by-Association’ by Degree) package, we present a series of highly efficient tools to calculate functional properties in networks based on the guilt-by-association principle. These allow rapid controlled comparisons and analyses. Two of the core features are: a function prediction algorithm which is fully vectorized (neighbor_voting), allowing network characterization across even thousands of functional groups to be accomplished in minutes in cross-validation and an analytic determination of the optimal prior to guess candidates genes across multiple functional sets (calculate_multifunc, auc_multifunc).

Address of the bookmark: https://github.com/sarbal/EGAD

Postdoctoral Researcher in Statistical Bioinformatics at Örebro University

Wed, 26 Aug 2020 10:20:11 -0500

The position is in Medical Sciences, with special focus on Statistical Bioinformatics.

The position is a full-time position for a fixed term of two years. The salary depends on the successful candidate’s qualifications and experience.

For more information, please contact Prof. Dirk Repsilber,This is an email address, Prof. Hugo Hesser, This is an email addressor Prof. Allan Sirsjö, allan.This is an email address, or Prof. Robert Brummer,This is an email address.

Örebro University actively pursues an equal work environment and values the qualities that diversity adds to our operations.

More detail at https://www.oru.se/english/working-at-orebro-university/jobs-and-vacancies/job/?jid=20200286/

ProteoClade: A taxonomic toolkit for multi-species and metaproteomic analysis

Jit — Wed, 18 Mar 2020 14:27:20 -0500

ProteoClade is a Python library for taxonomic-based annotation and quantification of bottom-up proteomics data. It is designed to be user-friendly, and has been optimized for speed and storage requirements.

ProteoClade helps you analyze two general categories of experiments:

Targeted Database Searches: Experiments in which a limited number of species are defined ahead of time, such as those involving Patient-Derived Xenografts (PDXs) or host-pathogen interactions. Reference protein sequence databases are used for targeted searches (ex: using Mascot, MaxQuant).
De Novo Searches: Experiments in which the organisms are unspecified ahead of time or involve samples of high taxonomic complexity. Mass spectra are analyzed in the absence of a reference database (ex: using PEAKS, PepNovo).

ProteoClade scales from two organisms to every organism in UniProt. Please refer to the complete documentation at proteoclade.readthedocs.io for installation, a user's guide, and examples.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007741

Address of the bookmark: https://github.com/HeldLab/ProteoClade

ICMR Scientist Jobs For Biotech/Life Science/Biology & Bioinformatics

Tue, 10 Nov 2020 18:45:49 -0600

CMR welcomes on-line applications up to 5th December 2020 till 5:30 PM to fill out the vacancies of 42 Scientist’ E’ (Medical), 01 Scientist ‘E’ (Non-Medical), 16 Scientist ‘D’ (Medical) and also 06 Scientist ‘D’ (Non-Medical) from Indian Citizens for appointment on regular basis under Direct Recruitment with all India transfer liability under the Council.

Post I

Name of the Post: Scientist-E (Non-Medical)

Number of positions: One

Upper Age limit: 50 years

Post II

Name of the Post: Scientist-D (Non-Medical)

Number of positions: Six

Upper Age limit: 45 years

Fee:

Application Fee of Rs. 1500/- (Rupees one thousand five hundred only) is needed. SC / ST / Women/ PWD/ EWS applicants are exempted from application fee. Application Fee is to be paid by candidates through online web link given up the application. Application fees when paid will certainly not be reimbursed under any situations.

How to apply:

i) Candidates should apply online on https://recruit.icmr.org.in. A separate application needs to be submitted for every post, with the required application fee.

ii) Following self-attested documents are required to be uploaded together with the application:
a) Proof of Date of Birth.
b) Educational qualifications.
c) Experience.

More at https://recruit.icmr.org.in/assets/uploads/advertisement/ICMR_Advertisement_06112020.pdf

Galaxy Training Resources !

Jit — Sun, 27 Dec 2020 05:28:07 -0600

Welcome to Galaxy Training!

Collection of tutorials developed and maintained by the worldwide Galaxy community

Topic	Tutorials
Introduction to Galaxy Analyses	10
Assembly	6
Climate	3
Computational chemistry	6
Ecology	6
Epigenetics	6
Genome Annotation	3
Imaging	3
Metabolomics	4
Metagenomics	7
Proteomics	18
Sequence analysis	2
Statistics and machine learning	8
Transcriptomics	23
Variant Analysis	8
Visualisation	2

Address of the bookmark: https://training.galaxyproject.org/training-material/

RNA-seq workflow: gene-level exploratory analysis and differential expression

Jit — Sat, 09 Oct 2021 07:59:23 -0500

Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count datasets for downstream analysis. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.

Address of the bookmark: http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html