JULIO SOLIS-Bioinformatician & Molecular Biologist (@jsolis_s) 's Twitter Profile
JULIO SOLIS-Bioinformatician & Molecular Biologist

@jsolis_s

Bioinformatics is shaping all life sciences and my world on Andean lupins...

ID: 1264159072367992833

calendar_today23-05-2020 11:40:14

7,7K Tweet

422 Followers

504 Following

Oscar Arias (@oacerebro) 's Twitter Profile Photo

🔍 Buscar en Bases de Datos puede ser un desafío 🧩, pero este Review te enseña a formular las preguntas correctas y aprovechar al máximo cada herramienta. 💡🔬 #Ciencia #Investigación drive.google.com/file/d/1XPTJqS…

🔍 Buscar en Bases de Datos puede ser un desafío 🧩, pero este Review te enseña a formular las preguntas correctas y aprovechar al máximo cada herramienta. 💡🔬 #Ciencia #Investigación 

 drive.google.com/file/d/1XPTJqS…
owl (@owl_posting) 's Twitter Profile Photo

RNA structure prediction is hard. How much does that matter? owlposting.com/p/rna-structur… my surface level take is that it matters a lot less than i expected. but lots of people are trying to prove me wrong! and i think they have a good case too! both opinions are included here

Eric Topol (@erictopol) 's Twitter Profile Photo

🆕 Science Magazine How do our cells have long term memory of inflammation that can later lead to persistent, chronic inflammation and disease? Through specific epigenetic chromatin changes, aka "memory domains" Science Visuals science.org/doi/10.1126/sc… science.org/doi/10.1126/sc…

🆕 <a href="/ScienceMagazine/">Science Magazine</a> 
How do our cells have long term memory of inflammation that can later lead to persistent, chronic inflammation and disease?
Through specific epigenetic chromatin changes, aka "memory domains" <a href="/ScienceVisuals/">Science Visuals</a> 
science.org/doi/10.1126/sc…
science.org/doi/10.1126/sc…
Marios Georgakis (@mariosgeorgakis) 's Twitter Profile Photo

This is a great open-access resource (The Genotype-Phenotype Map) linking fine-mapped GWAS summary statistics for 16,000 traits and molecular QTLs for 2.7 million omics measurements with colocalization across significant loci.

This is a great open-access resource (The Genotype-Phenotype Map) linking fine-mapped GWAS summary statistics for 16,000 traits and molecular QTLs for 2.7 million omics measurements with colocalization across significant loci.
Eric Topol (@erictopol) 's Twitter Profile Photo

A new feature Science Magazine on the clusters of cells that enhance the spread of cancer, and what can be done to break them up Science Visuals science.org/content/articl…

A new feature <a href="/ScienceMagazine/">Science Magazine</a> on the clusters of cells that enhance the spread of cancer, and what can be done to break them up <a href="/ScienceVisuals/">Science Visuals</a> 
science.org/content/articl…
Joachim Schork (@joachimschork) 's Twitter Profile Photo

Missing data is a common problem in almost every dataset, and it can seriously affect the validity of analyses if not handled properly. A widely used solution is missing data imputation, where the gaps in the data are estimated and replaced with plausible values rather than

Missing data is a common problem in almost every dataset, and it can seriously affect the validity of analyses if not handled properly. A widely used solution is missing data imputation, where the gaps in the data are estimated and replaced with plausible values rather than
ChileBio (@chilebio_ag) 's Twitter Profile Photo

🌿 Un proyecto global está generando un recurso genómico abierto para entender cómo las plantas producen compuestos terapéuticos. Clave para acelerar el descubrimiento de nuevos fármacos y biotecnología. 🔗 chilebio.cl/2026/04/01/con… #Genómica #Biotecnología #Salud #Medicinal

🌿 Un proyecto global está generando un recurso genómico abierto para entender cómo las plantas producen compuestos terapéuticos.

Clave para acelerar el descubrimiento de nuevos fármacos y biotecnología.

 🔗 chilebio.cl/2026/04/01/con…

#GenĂłmica #BiotecnologĂ­a #Salud #Medicinal
Scholarships Corner (@scholar_corner) 's Twitter Profile Photo

Humboldt Research Fellowship 2027 in Germany | Fully Funded Applications are now open for the Humboldt Research Fellowship 2027. This is a great opportunity for international researchers to conduct research in Germany with full financial support and access to top institutions.

Humboldt Research Fellowship 2027 in Germany | Fully Funded

Applications are now open for the Humboldt Research Fellowship 2027. This is a great opportunity for international researchers to conduct research in Germany with full financial support and access to top institutions.
Ming "Tommy" Tang (@tangming2005) 's Twitter Profile Photo

Terminal Genome Viewer github.com/zeqianli/tgv Another one that is around for a while: ASCIIGenome github.com/dariober/ASCII…

Terminal Genome Viewer github.com/zeqianli/tgv

Another one that is around for a while: ASCIIGenome github.com/dariober/ASCII…
Joachim Schork (@joachimschork) 's Twitter Profile Photo

K-means clustering is one of the simplest and most widely used methods for identifying patterns in data. The idea is straightforward: Group observations into k clusters so that points within each cluster are as similar as possible. In the visualization below, the algorithm

K-means clustering is one of the simplest and most widely used methods for identifying patterns in data.

The idea is straightforward:

Group observations into k clusters so that points within each cluster are as similar as possible.

In the visualization below, the algorithm
Bioinformatics Advances (@bioinfoadv) 's Twitter Profile Photo

🌳 Check out the latest in Bioinformatics Advances: "An optimization framework for hierarchical clustering"  Read it here: doi.org/10.1093/bioadv…

🌳 Check out the latest in Bioinformatics Advances: "An optimization framework for hierarchical clustering" 

Read it here: doi.org/10.1093/bioadv…
JULIO SOLIS-Bioinformatician & Molecular Biologist (@jsolis_s) 's Twitter Profile Photo

Con el 93% de actas contabilizadas (ONPE): JP: 1,890,115 votos (12.006%) Porky: 1,876,391 votos (11.919%) Diferencia actual: JP +13,724 votos. Votos faltantes estimados: Porky: 28,000 (extranjero) + 17,671 (Lima) = 45,671 JP: 25,000 (PerĂş) + 2,800 (extranjero) = 27,800 Gana Porky

Con el 93% de actas contabilizadas (ONPE):
JP: 1,890,115 votos (12.006%)
Porky: 1,876,391 votos (11.919%)
Diferencia actual: JP +13,724 votos.
Votos faltantes estimados:
Porky: 28,000 (extranjero) + 17,671 (Lima) = 45,671
JP: 25,000 (PerĂş) + 2,800 (extranjero) = 27,800
Gana Porky