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...
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...
github.com - 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...
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...
github.com - 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...
training.galaxyproject.org - Welcome to Galaxy Training!
Collection of tutorials developed and maintained by the worldwide Galaxy community
TopicTutorials
Introduction to Galaxy Analyses
10
Assembly
6
Climate
3
Computational...
Lonza (https://www.lonza.com/) are seeking a highly motivated and skilled (Senior) Scientist with experience in Structure-based Protein Engineering and Bioinformatics to join Lonza's Applied Protein Services (APS) Bioinformatics team based in...
master.bioconductor.org - 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...
the sequenced reads can be mapped to the organism’s genes to assess how differently the genes are expressed under the experimental circumstances as opposed to the control scenario. This is known as differential expression (DE) analysis