Posts Tagged ‘x57l’

Leaving LastPass

March 26, 2023

https://twit.tv/shows/security-now/episodes/904?autostart=false

Found the whole @LastPass debacle depressing. First, I trusted [Steve Gibson’s] endorsement. Then I trusted it. Now I’m unsure what to do.

Bitwarden? 1password ?

Proving a photo is fake is one thing. Proving it isn’t is another | The Economist

March 6, 2023

https://www.economist.com/science-and-technology/2023/01/09/proving-a-photo-is-fake-is-one-thing-proving-it-isnt-is-another

Writefull

March 6, 2023

https://www.writefull.com/

Might be useful for sentence revision:
https://x.writefull.com/academizer

Might be useful if you have a full paper:
https://www.writefull.com/writefull-revise

Turn emails into Google Calendar appointments | Parseur

November 28, 2022

https://parseur.com/integration/email-to-google-calendar

A comprehensive SARS-CoV-2–human protein–protein interactome reveals COVID-19 pathobiology and potential hos t therapeutic targets | Nature Biotechnology

October 16, 2022

https://www.nature.com/articles/s41587-022-01474-0

A comprehensive SARS-CoV-2–human protein–protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets Yadi Zhou, Yuan Liu, Shagun Gupta, Mauricio I. Paramo, Yuan Hou, Chengsheng Mao, Yuan Luo, Julius Judd, Shayne Wierbowski, Marta Bertolotti, Mriganka Nerkar, Lara Jehi, Nir Drayman, Vlad Nicolaescu, Haley Gula, Savaş Tay, Glenn Randall, Peihui Wang, John T. Lis, Cédric Feschotte, Serpil C. Erzurum, Feixiong Cheng & Haiyuan Yu

ScEQTL

May 12, 2022

https://www.nature.com/articles/s41586-022-04713-1

Published: 11 May 2022
Single-cell eQTL models reveal dynamic T cell state dependence of disease loci Aparna Nathan, Samira Asgari, Kazuyoshi Ishigaki, Cristian Valencia, Tiffany Amariuta, Yang Luo, Jessica I. Beynor, Yuriy Baglaenko, Sara Suliman, Alkes L. Price, Leonid Lecca, Megan B. Murray, D. Branch Moody & Soumya Raychaudhuri
Nature (2022)

Setting up an email address for a Slack channel

April 29, 2022

https://slack.com/help/articles/206819278-Send-emails-to-Slack

Hartwig

April 23, 2022

the marker paper of the Hartwig Medical Foundation paper.

Pan-cancer whole-genome analyses of metastatic solid tumours https://www.nature.com/articles/s41586-019-1689-y
Peter Priestley, Jonathan Baber, Martijn P. Lolkema, Neeltje Steeghs, Ewart de Bruijn, Charles Shale, Korneel Duyvesteyn, Susan Haidari, Arne van Hoeck, Wendy Onstenk, Paul Roepman, Mircea Voda, Haiko J. Bloemendal, Vivianne C. G. Tjan-Heijnen, Carla M. L. van Herpen, Mariette Labots, Petronella O. Witteveen, Egbert F. Smit, Stefan Sleijfer, Emile E. Voest & Edwin Cuppen
Nature volume 575, pages
210–216 (2019)

There have been numerous follow-up papers since.

Also, the Glioma Longitudinal Analysis (GLASS) Consortium datasets, which are publicly accessible via www.synapse.org/glass.
The first marker paper is here:
https://www.nature.com/articles/s41586-019-1775-1.

Mutation bias reflects natural selection in Arabidopsis thaliana | Nature

April 14, 2022

https://www.nature.com/articles/s41586-021-04269-6

https://twitter.com/MarkGerstein/status/1510065060806283269

Interesting paper, relating de novo mutation rate to epigenetic features. Wonder exactly how this connects to the fact that the background mutation rate in cancer genomes depends strongly on epigenetics.

Important genomic regions mutate less often than do other regions https://www.nature.com/articles/d41586-022-00017-6

Biologically informed deep neural network for prostate cancer discovery | Nature

April 12, 2022

https://www.nature.com/articles/s41586-021-03922-4

https://twitter.com/SEHanlon/status/1513548800949989377

At #AACR22, @VanAllenLab gives a nice overview of his paper using an interpretable NN model to get insights into determining cancer severity (https://nature.com/articles/s41586-021-03922-4)
Biologically informed deep neural network for prostate cancer discovery

Liked the way he hard-coded specific genes & pathways into the model & looked in detail where the model misclassified specific patients #AACR22 #AACR2022

Also, thought the hard-coding of genes into the model was similar to that in another interpretable AI approach (for brain disease, https://science.org/doi/10.1126/science.aat8464) Could have used the “rank projection trees” from this to highlight important genes #AACR22 #AACR2022