Marina Gorostiola González

PhD student 👩‍💻| Computational Drug Discovery @CDDLeiden
Cancer research using AI and structure-based methods.
A bit of 🎻🥋📕🏞 📸 in my free time.

[Marina Gorostiola González @m_gorostiola]

Another one of my PhD chapters got published! 🎉🎉
In this chapter, @CDDLeiden we looked at the possibility of creating dynamic protein descriptors (3DDPDs) for bioactivity modeling from MD data.

https://t.co/2CmY1pYpyc
https://t.co/NxjrkIL6e3

[Sketching Science @sketchscience]

The highest impact factor is when your paper reaches your mom’s fridge❤️

[Marina Gorostiola González @m_gorostiola]

Great to see published this great collaborative effort that I contributed to! Have a look! 🎉✨

[Francesca Grisoni @fra_grisoni]

Check out our review on #AI for #naturalproduct drug discovery! Just out in @NatRevDrugDisc 👇

A huge collaborative effort between disciplines and institutions 💪🏻

[Marina Gorostiola González @m_gorostiola]

Amazing achievement by my PhD supervisor @GJPvWesten !! Stoked to be part of your group! ✨🎉

[LED3 hub (inactive account) @LED3hub]

Congratulations to our @LED3hub member @GJPvWesten on receiving the very prestigious Gold Medal of @KNCVchemie #IUPACCHAINS2023 @IUPAC2023, which is awarded for groundbreaking work in chemistry under the age 40. He is awarded for his groundbreaking work on AI in drug discovery.

[Misha Teplitskiy | Science of Science @MishaTeplitskiy]

The longer people are in academia, the more they realize that when reading papers it's best to ignore Intro, Discussion etc. and just look at Methods and Results
https://t.co/EzQL7WI71Q

[Elisa Granato @Prokaryota]

me on my 20th supplementary figure

[Diego del Alamo @DdelAlamo]

"Chatbots in Drug Discovery: A Case Study on Anti-Cocaine Addiction Drug Development with ChatGPT"

https://t.co/HSIgtou9nc

[Marinka Zitnik @marinkazitnik]

Introducing PINNACLE, a contextual graph AI model for comprehensive protein understanding

PINNACLE dynamically adjusts its outputs based on molecular contexts in which it operates

Providing outputs tailored to molecular contexts is essential for broader use of foundational models in biology and medicine

Leveraging #single-cell atlas, PINNACLE is trained on contextualized protein networks to generate context-aware representations split across 156 cell type contexts from 24 tissues

Pretrained PINNACLE protein representations can be adapted for broad array of tasks
🧪enhance 3D structural representations
💊study genomic drug effects across cell type contexts
🎯nominate #therapeutic targets
🌲zero-shot retrieval of the tissue hierarchy

Led by a superstar PhD student @_michellemli! Grateful for wonderful collaborators @harvardmed @HarvardDBMI @BrighamWomens @MassGeneralNews @MassGenBrigham @Roche @harvard_data

Y Huang @YepHuang, M Sumathipala @marissa_sumathi, MQ Liang, A Valdeolivas, A Ananthakrishnan, K Liao, and D Marbach

#AI4Science #SingleCell #AI #Proteins [1/4]

[Marina Gorostiola González @m_gorostiola]

Getting started!! #shef2023

[Gerard JP van Westen @GJPvWesten]

@CDDLeiden at #shef2023

Good times, good science..!

[Marina Gorostiola González @m_gorostiola]

New preprint alert! Our work @CDDLeiden on dynamic protein descriptors for PCM modelling is now available on ChemRvix and all the code on our group GitHub. Looking forward to the feedback on our newly developed 3DDPDs 🥳
https://t.co/eT2lPjr9al

[Computational Drug Discovery Leiden @CDDLeiden]

Work by @OlivierBeqgn , @BongersBrandon , @Willemjespers , @GJPvWesten et al. :” Papyrus: a large-scale curated dataset aimed at bioactivity predictions”

Get the data here: https://t.co/uUSYBMS0kb
Scripts to adapt your own data: https://t.co/h3klAISvAp

https://t.co/hpEtEn28cI

[Marina Gorostiola González @m_gorostiola]

Some pretty cool collaborative work on somatic mutations in GPCRs!

[Computational Drug Discovery Leiden @CDDLeiden]

Just online: "Pan-cancer functional analysis of somatic mutations in G protein-coupled receptors" Veni of @GJPvWesten and continued by @BongersBrandon , @m_gorostiola , @Willemjespers , et al!

CC @NWO_Science , @LACDR , @LED3hub , @LeidenScience
https://t.co/XFAJw6aOBq

[Marina Gorostiola González @m_gorostiola]

Probably the best @CDDLeiden tradition: Computational cheese day!!

[Yann LeCun @ylecun]

Too many studies that apply machine learning to science & medicine employ incorrect methodologies.
Many make very basic mistakes, such as not having separate training & test sets, using the test set (not a separate validation set) for feature selection, hyperparameter tuning, etc

[PyQuant News 🐍 @pyquantnews]

College completely failed to teach me data analysis.

So I spent over 10,000 hours learning Python.

Then, I picked the 13 best libraries for machine learning and data analysis.

But unlike college, these won't cost you $120,000.

Here they are for free:

[Computational Drug Discovery Leiden @CDDLeiden]

The amazing #2022ICCS is over. The @cddleiden delegation also had posters from: @BournezC , @martin_sicho , @ManuelG81702324 , @sohvi_luukkonen , @DavidAraripe , @1inde1 , @BolaK_DDD , @BongersBrandon , Helle vd Maagdenberg, Rosan Kuin. CC @LeidenScienceEN , @LACDR #2022ICCS

[Marina Gorostiola González @m_gorostiola]

@yew_mun Not yet, but hopefully before the end of the year!

[Marina Gorostiola González @m_gorostiola]

Today I presented our work on 3D protein dynamic descriptors (3DDPDs) at #2022ICCS . Great ideas during the Q&A session and room for collaboration with other tools presented these days!

[Computational Drug Discovery Leiden @CDDLeiden]

Great presence of @CDDLeiden at the @intconfchemstr. Talks by @OlivierBeqgn and @m_gorostiola. Posters by many group members. CC @sails_Leiden @LACDR #2022iccs

[Brandon Bongers @BongersBrandon]

@m_gorostiola presenting her work about 3DDPDs. Used a preliminary version of Papyrus for collecting data. Super nice presentation (though, once again, I am very biased). #2022ICCS