Jose L. Oliver

Jose L. Oliver

@Jose_Oliver

Followers336
Following412

Professor of Genetics. Likes: DNA, computers and walking by Sierra Nevada

Granada, Spain
Joined on July 01, 2009

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Statistics

We looked inside some of the tweets by @Jose_Oliver and here's what we found interesting.

Inside 100 Tweets

Time between tweets:
19 days
Average replies
1
Average retweets
16
Average likes
35
Tweets with photos
10 / 100
Tweets with videos
0 / 100
Tweets with links
0 / 100

gCluster algorithm: detection of CGIs as statistically significant clusters of CpG dinucleotides: http://bioinfo2.ugr.es:8080/gCluster/ 

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The central paradox of the current state of nanopore sequencing: pores are great for long DNA but long DNA is not great for pores: http://omicsomics.blogspot.com/2019/05/nanopores-long-dna-paradox.html …

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Quoted @BioinfoGenyo

Curso análisis e integracion de datos -omicos

Curso análisis e integracion de datos -omicos

https://cemed.ugr.es/curso/19gr56/ 

As ONC201 moves through human clinical trials, scientists finally figure out that the compound and its analogs target a mitochondrial protease:

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Curso sobre análisis bioinformático de datos -omicos: https://cemed.ugr.es/curso/19gr56/ 

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Análisis Bioinformático e integración de datos-omicos en enfermedades complejas:

Análisis Bioinformático e integración de datos-omicos en enfermedades complejas:

Cris
2 days ago

Curso de Análisis Bioinformático e integración de datos -omicos en enfermedades complejas. ¡No os lo podeis perder! https://cemed.ugr.es/curso/19gr56/  @fcienciasugr @CemedUGR

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Machine learning algorithms predict the repairs made to DNA after Cas9 cuts:

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Quoted @carninci

Single celll blood transcriptomics of supercentenarians, individuals that live more than 110 years, in a project to study what is healthy aging. https://twitter.com/biorxivpreprint/status/1130474597437124609 …

Is this a biomarker for healthy aging? Fascinating. As an aside, Okinawa has a cultural saying: “hara hachi bu”, which means eat until you are 80% full. Best, -NK & @NEBiolabs #transcriptome #immunology

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A method for differential analysis of transcription factor activity from gene expression data:

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We found a way to decompress gzip files in parallel. With @RayanChikhi. Code: https://github.com/Piezoid/pugz/  Paper: https://arxiv.org/abs/1905.07224 

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Errors in annotation are just as prevalent as they were in the past, if not more so. How are we to solve this growing problem?

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There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies:

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How high-throughput sequencing technologies have revolutionized the microbiology research field and their emerging impact on clinical practice:

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A la orilla del lago Maracaibo: una emocionante historia de como se descubrió el gen de la enfermedad de Huntington

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Houssay: “Los países ricos lo son porque dedican dinero al desarrollo científico-tecnológico, y los países pobres lo siguen siendo porque no lo hacen. La ciencia no es cara, cara es la ignorancia”.

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Origins and evolution of CRISPR-Cas systems

.....
- via Researcher
https://researcher-app.com 
(@ResearcherApp)

Origins and evolution of CRISPR-Cas systems ..... - via Researcher https://researcher-app.com  (@ResearcherApp)

Human dna contamination in (mostly) small, draft bacterial and archaeal genomes is rife in NCBI RefSeq: '3,437 bogus proteins in 2,250 contaminated genomes' according to @StevenSalzberg1 and colleagues http://bit.ly/30nDZzr  #NBThighlight

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Transcriptional cofactors display specificity for distinct types of core promoters

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Transcriptional cofactors (COFs) communicate regulatory cues from enhancers to promoters and are central effectors of transcription activation and gene expression. COFs display specificity for distinct types of core promoters

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For more than two decades now @nature has supported preprint deposition; we now encourage it

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