Tweetovi
- Tweetovi, trenutna stranica.
- Tweetovi i odgovori
- Medijski sadržaj
Blokirali ste korisnika/cu @jinboxu_chicago
Jeste li sigurni da želite vidjeti te tweetove? Time nećete deblokirati korisnika/cu @jinboxu_chicago
-
Just saw the video of my talk at ISMB 3DSIG in the summer of 2019 about deep learning for protein structure prediction. In case that you are interested in it, it is at https://www.youtube.com/watch?v=qAm22TRtgOU … .
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jinbo Xu proslijedio/la je Tweet
#Protein structures could be accurately predicted with deep learning on personal computers. A groundbreaking discovery, this finding could be the key to understanding#biological processes. In PNAS: http://ow.ly/o23V50vGhm4 pic.twitter.com/eEDoYOYB01
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
-
There will be a computational biology workshop in my institute in September 2019. Registration is free and all are welcome to attend. See https://sites.google.com/ttic.edu/compbioworkshop2019 … for some details.
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
A recent comprehensive review of machine learning for protein structure prediction (with some minor inaccuracy) Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning | Journal of Computational Biology https://www.liebertpub.com/doi/full/10.1089/cmb.2019.0193#.XV6iEobK4BU.twitter …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Impact factor impacts on early-career scientist careershttps://www.pnas.org/content/116/34/16659 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jinbo Xu proslijedio/la je Tweet
Read highlights from this week’s issue of PNAS: Tracking the source of radioactive ruthenium, Deep learning and protein structure prediction, Neonicotinoids, honeydew, and insect mortality:http://ow.ly/EniG50vDEnh
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
An excellent review on protein structure prediction and design.https://twitter.com/NatRevMCB/status/1162305557887430656 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
The journal version of my paper about deep learning for distance-based folding is officially published. Some of my source code is also released along with this publication. Distance-based protein folding powered by deep learninghttps://www.pnas.org/content/early/2019/08/08/1821309116 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Are Commercial Labs Stealing Academia’s AI Thunder? by
@Synced_Globalhttps://link.medium.com/KzVS2XrcdYHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Not sure if this works or not. Readers will find out the journal name sooner or later.https://twitter.com/lpachter/status/1131546083249643530 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Had a great time while visiting Baker’s group. Also learned a lot from his young people.https://twitter.com/UWproteindesign/status/1131686385864171521 …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jinbo Xu proslijedio/la je Tweet
Open source software is
to science. Many of the packages, libraries + applications crucial to biomedicine are built by researchers who volunteer their time + effort to make these tools available. We’re excited to announce support for #opensource toolshttps://bit.ly/2Q4G1zRPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Good to know that a 12-year old paper is still remembered: https://link.springer.com/chapter/10.1007/978-3-540-71681-5_2 …pic.twitter.com/PdKpqyLZKn
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Just finished a report of our CASP13 results: https://www.biorxiv.org/content/10.1101/624460v1 …. Surprised to find out that we predicted correct folds for all the 3 largest hard targets (~350 amino acids) and generated the best 3D models for two of them (T0950-D1 and T0969-D1).
@MoAlQuraishi@sokryptonpic.twitter.com/ZzgTnbBPFU
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
Čini se da učitavanje traje već neko vrijeme.
Twitter je možda preopterećen ili ima kratkotrajnih poteškoća u radu. Pokušajte ponovno ili potražite dodatne informacije u odjeljku Status Twittera.