Science Team Lead - Cellular Reprogramming
e184

See the full job description on jobRxiv: https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/

#atacseq #CRISPRa #rnaseq #ScienceJobs #hiring #research
https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/?fsp_sid=5856

🧬 Ever wondered how the genome actually looks when it folds inside the nucleus — and how fast we can simulate it?

🔗 Multiscale molecular modeling of chromatin with MultiMM: From nucleosomes to the whole genome. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2024.09.025

📚 CSBJ: https://www.csbj.org/

#ChromatinModeling #3DGenome #ComputationalBiology #Genomics #MolecularModeling #GenomeArchitecture #ChromatinStructure #HiC #ATACSeq #Biophysics #StructuralBiology

Science Team Lead - Cellular Reprogramming
e184

See the full job description on jobRxiv: https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/

#atacseq #CRISPRa #rnaseq #ScienceJobs #hiring #research
https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/?fsp_sid=3805

Science Team Lead - Cellular Reprogramming
e184

See the full job description on jobRxiv: https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/

#atacseq #CRISPRa #rnaseq #ScienceJobs #hiring #research
https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/?fsp_sid=2083

Science Team Lead - Cellular Reprogramming
e184

See the full job description on jobRxiv: https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/

#atacseq #CRISPRa #rnaseq #ScienceJobs #hiring #research
https://jobrxiv.org/job/e184-27778-science-team-lead-cellular-reprogramming/?fsp_sid=1985

#ucsc We are pleased to announce the release of a new Public Hub, UniversalEPI ENCODE for hg38. This track hub displays normalized #atacseq and #HiC interaction predictions based on ENCODE data and generated using UniversalEPI. UniversalEPI is an attention-based deep ensemble model that predicts enhancer–promoter interactions (EPIs) up to 2 Mb apart using only DNA sequence and chromatin accessibility (ATAC-seq) data.

https://genome.ucsc.edu/cgi-bin/hgTracks?hubUrl=https://boevalab.inf.ethz.ch/resources/universalepi_pred_encode/ucsc_track_hub/hub.txt&genome=hg38&position=lastDbPos

#bioinformatics

I wrote my notes for using #nfcore /differencialabundance with the output of nfcore/atacseq" in the following gist: https://gist.github.com/lindenb/593ad97a884d465a04b15a8578af69b4

#nextflow #atacseq

For scRNA-seq and scATAC-seq, have people been using "reads" as the important measurement instead of "fragments" for the past few years? Because this paper seems to suggest people have been unintentionally over-inflating the variance in their data by counting "reads"

https://www.nature.com/articles/s41592-023-02112-6/figures/1

I thought we we figured this out a long time ago with the whole "RPKM vs FPKM vs TPM" debate in bulk RNA-seq years ago.

#single_cell #rnaseq #atacseq #compBio #bioinformatics

serious question. When one runs motif enrichment analysis, I think it is generaly desirable to know which specific peaks were found to have a motif. Why does a tool like HOMER's FindMotifsGenome.pl not report every instance of where each motif was found, and one must run a whole different tool for that task? Is this a feature more people would wish for?

#genomics #bioinformatics #atacseq #chromatin #motifs #computational #compbiology

Anyone know a good review paper / learning resource for building gene regulatory networks #GRN from #scATACseq #ATACseq and/or #scRNAseq data?
Thanks!

This useful paper looks into strengths and weaknesses of #TnSeq approaches in #bacterial #genetics screens for essential genes.

Importantly, a lot of false positives are attributable to Tn insertion failure on nucleoid-associated DNA — a result that my friends who use #ATACSeq & similar methods to map chromatin states in eukaryotes will be unsurprised by.

The obvious workaround is in vitro transposition on isolated DNA, if your system is amenable to that approach.

https://journals.asm.org/doi/full/10.1128/msystems.00896-22

Human fetal lung single cell atlas. scRNA-seq + scATAC-seq + Visium combined. Key finding: unrecognized cell states such as new progenitors and a subset of neuroendocrine cell related to lung cancer.
#singlecell #cellatlas #atacseq #spatialtranscriptomics #devbio
https://www.cell.com/cell/fulltext/S0092-8674(22)01415-5

And finally, some skills that will be helpful: #bioinformatic and #statistical skills: population genetics/#genomics, quantitative genetics, #RNAseq, #ATACseq, integration of #multi_omics data; willingness to get involved in data generation (wet lab) is a plus.

Hello world! :) #evodevo #butterfly #CRISPR #ATACseq