Harvard Data Science Initiative

Your friendly neighborhood Data Science Initiative.

[Harvard Data Science Initiative @harvard_data]

A reminder that the Harvard Data Science Initiate can be found on a variety of platforms:

- Threads and Instagram as "thehdsi"
- Facebook as "harvarddatascience"
- Linkedin https://t.co/0yxNYnlXP6
- YouTube https://t.co/RkL52clMyR
- Our Newsletter https://t.co/W8AYRvAc65

[Harvard Data Science Review @TheHDSR]

🎉 New HDSR Podcast!

🍷 For our latest episode, "How Many Glasses of Wine a Day Keeps the Doctor Away?," we talk to esteemed guests, @LauraCatena & @ATawakolMD about the health benefits and potential drawbacks of #wine.

🎧 Listen now! https://t.co/jM4lRnoCJb

[Harvard Data Science Initiative @harvard_data]

🔬 In this @TheHDSR paper, HDSI Faculty Affiliate Mark Glickman + PhD student Yi Zhang explain how #AI + #GenerativeAI tools are changing the landscape for #research discovery and summarization: https://t.co/jc00shiruE

[Marinka Zitnik @marinkazitnik]

Excited to share our new paper on Contextual AI models for context-specific prediction in biology in @NatureMethods led by stellar @_michellemli

https://t.co/aZDbRJghyd

Understanding how proteins work and developing new therapies requires knowing which cell types proteins act in and how they interact with each other.

Predicting and optimizing protein targets must happen in context. We can draw a parallel with the polysemic word “apple,” whose meaning is resolved via the context of surrounding words. Just as one can “grow an apple” or “buy an apple,” the roles of genes and proteins are resolved via cell context—particularly the environment where a drug will operate.

In this @naturemethods paper, we introduce PINNACLE, an approach that uses geometric deep learning to create context-aware protein models.

Using a protein interaction dataset and a multi-organ single-cell atlas @cziscience, PINNACLE analyzes protein interactions in 156 cell types across 24 tissues, generating nearly 395,000 protein representations. PINNACLE dynamically adjusts its outputs to biological contexts. Excited to soon share with you models across @cziscience #CellxGene Discover datasets.

It paves the way for a type of AI that can learn contexts to understand a given protein plus its surrounding environment and identify its many potential roles.

Providing outputs tailored to biological contexts is essential for the broad use of foundation models in biology. We tested PINNACLE on tasks such as enhancing 3D structural representations of therapeutically relevant interactions in immunology, studying the effects of drugs across cell-type contexts, nominating therapeutic targets in a cell-type-specific manner, and zero-shot retrieval of tissue hierarchy.

@harvard @HarvardDBMI @harvard_data @KempnerInst @Roche @MassGenBrigham @BrighamWomens

Fantastic team of collaborators: @_michellemli, M Sumathipala, MQ Liang, A Valdeolivas, AN Ananthakrishnan @kat_liao @danmarbach

Thanks to @DrArunimaSingh for editorial guidance

Paper:
https://t.co/aIxZrRSdzS

Research Briefing:
https://t.co/iU7mL6ZrzJ

Code:
https://t.co/GXfkwqhAKM

HF Space:
https://t.co/KndH9SdtQV

[Harvard Data Science Initiative @harvard_data]

🦷 @dental_harvard is seeking a #Research #DataAnalyst!

💼 This position will involve working with PI Dr. Hawazin Elani on various #healthpolicy and #MachineLearning projects focused on disparities in oral #health.

📝 Learn more + apply now: https://t.co/EXrzMtvbkN

[Harvard Data Science Initiative @harvard_data]

🗞️ Read the last HDSI weekly newsletter until Fall 2024: https://t.co/U5Szj0EAXn

😎 We look forward to seeing you in the new academic year. Have a safe + fun rest of your summer!

[Harvard Data Science Initiative @harvard_data]

🎉 @TheHDSR anniversary celebration recordings are now available on our YouTube channel!

🦾 Day 1: #AI and #DataScience: Integrating Artificial and Human Ecosystems
🥂 Day 2: Vine to Mind: Decanting Wine's Future With Data Science + AI

🎞️ Watch now: https://t.co/elAyvKD593

[Kempner Institute at Harvard University @KempnerInst]

Are you attending #ICML2024? Be sure to check out our posters, workshops & presentations from the #KempnerInstitute community!

@AdaFang_ @blake__bordelon @CPehlevan @SimmonsEdler @nsaphra @KanakaRajanPhD @brandfonbrener @rosieyzh @EranMalach @RyanPaulBadman1 @marinkazitnik

[Soroush Saghafian @Soroush_Saghaf]

𝓠𝓾𝓮𝓼𝓽𝓲𝓸𝓷: How can #AI revolutionize #healthcare? Why it has not been as impactful?
See some answers below and learn more about our work @PIASLab 👇👇👇

[Harvard Statistics Department @HarvardStats]

How are AI and Generative AI tools changing the landscape for research discovery and summarization? Find out in Senior Lecturer Mark Glickman and PhD student Yi Zhang’s paper in @TheHDSR : https://t.co/rDvG5NNQWG

[Harvard Data Science Initiative @harvard_data]

👋 Don't miss last week's newsletter!

🗞️ Recent news featuring HDSI Faculty Affiliates @zittrain, @tedsvo, @AndrewLBeam, @rema_nadeem
💰 Funding opportunities from @HarvardCID + @DataDotOrg
🗓️ Upcoming events w/ @HarvardCGA, @HarvardBiostats, + more!
https://t.co/uujCyIf5zo

[Harvard Kennedy School @Kennedy_School]

Can a bad debate performance shift voter preference?

New research by HKS's Matthew Baum and colleagues evaluates the impact of the first Trump-Biden presidential debate https://t.co/STL2wMoog3

[Berkman Klein Center for Internet & Society @BKCHarvard]

ICYMI, the full exposition of this talk by @zittrain on renegade #AI agents is now available as an op-ed in @TheAtlantic:

https://t.co/FER4nDfrPF

[Harvard Statistics Department @HarvardStats]

Imai & Li's paper (forthcoming in the Journal of Causal Inference) demonstrates that Neyman's methodology can be used to experimentally evaluate the efficacy of individualized treatment rules (ITRs), which are derived by modern causal ML algorithms: https://t.co/5Igug4ycHw

[NEJM AI @NEJM_AI]

Introducing a new artificial intelligence-enabled Perspective series that summarizes and extracts insights from the 𝘕𝘌𝘑𝘔 𝘈𝘐 Grand Rounds podcast episodes. Read the full editorial by Drs. @arjunmanrai and @AndrewLBeam: https://t.co/igFhJJ9e4U

[Harvard Data Science Initiative @harvard_data]

👩🏻‍💻 Join this comprehensive two-part series moderated by HDSI Faculty Affiliate @Satchit_Balsari to delve into the #science of extreme heat + understand its impact: https://t.co/TCvsHWnmaf #heatwave @MittalInstitute

☝️ Part I: Thursday, July 18
✌️ Part II: Thursday, July 25

[Harvard CID @HarvardCID]

“Cash transfers have large potential to help those in urban areas, particularly refugees, with basic necessities: food shelter, transport, [because] cities have very well-functioning markets.” @rema_nadeem
#Refugees #CIDFacultyAffiliate
https://t.co/0UWlwdePLm

[Harvard Data Science Initiative @harvard_data]

@CNTR4growth @DataDotOrg 💙

[Harvard Data Science Initiative @harvard_data]

🤝 Together, we can drive inclusive growth with #AI! Apply for the #AI2AI Challenge to be part of the global movement to leverage AI for #socialimpact.

☎️ Calling for applications from teams using #AIforImpact by July 18, 2024: https://t.co/MOxnT0H64R

datadotorg + @CNTR4growth

[Teddy Svoronos @tedsvo]

My colleague ⁦@danmlevy⁩ and Angela Perez have published an excellent book on teaching with ChatGPT. If you benefitted from Dan’s book on teaching with Zoom in 2020, you’ll definitely want to get this one. Lots of great insights and practical ideas! https://t.co/bno5oTuMSB

[Harvard Data Science Initiative @harvard_data]

⛱️ Looking for good books to read this summer?

📚 Check out this #AI and #Democracy Summer Reading List from @HarvardAsh: https://t.co/3LjrmiRUFO