Arpan Sarkar

PhD candidate in the Eddy Lab @Harvard interested in protein ML for modeling protein domains and predicting homology

[Lucas Urbisaia @LMUrbisaia]

@OfficialLoganK Have you tried @PraxosInc?

[Arpan Sarkar @arpsark]

Excited to be a part of this team! Check out our work investigating scientific problem solving in LLMs!

[Alan Li @alanli2020]

1/9 🚀 New paper: Demystifying Scientific Problem-Solving in LLMs — How does reasoning enhancement affect knowledge recall, and do LLMs benefit from external knowledge complimentary to reasoning?

Tldr;
📊 SciReas: holistic and efficient evaluation suite for scientific reasoning
🧠 KRUX: a novel framework to study knowledge vs reasoning in LLMs
🔑 Findings: knowledge is a bottleneck; reasoners + in-context knowledge help; long CoT helps knowledge recall/utilization

[Liana Merk @BacteriYay]

(1/7) Very excited to share my first PhD preprint on the interactions of two of my favorite mobile genetic elements: phages and group II introns!

https://t.co/99pFYIYl4r

[Dr. Jenny Chen @jjennychenn]

Super excited to share my postdoc work investigating how mating and parental behaviors evolve using wild species of mice combined with single nucleus RNA-sequencing of the hypothalamus 🐭🧠🧬!
https://t.co/tYSFCfOqwP

[Arpan Sarkar @arpsark]

@sokrypton It's also important to look at the homology between any domain in any seq in test to any domain in any seq in training, and I think we do a good job of assessing performance at various domain-level max % identity thresholds in our work on PSALM (https://t.co/80WSlT0uMp)

[Arpan Sarkar @arpsark]

We're excited to share PSALM -- keep an eye out for subsequent releases!

[Arpan Sarkar @arpsark]

PSALM annotates sequences with greater sensitivity and specificity than profile HMM-based methods (on identical training sets). PSALM has a very low residue-level FPR, benefits strongly from additional examples, and annotates clans even at low percent identity to training data

[Arpan Sarkar @arpsark]

PSALM uses a hierarchical approach that considers both individual protein domain families and clans (determined by Pfam). Modeling clans is an interpretable intermediate step that helps identify functional regions that lack clear family-level annotations

[Arpan Sarkar @arpsark]

We propose PSALM, which extends ESM-2 to predict *residue*-level protein sequence annotations. PSALM accurately annotates domain boundaries, multi-domain proteins, and even domains that are currently unannotated in sequence databases

[Arpan Sarkar @arpsark]

Excited to share our new work (with @KumareshSpikes): "Protein Sequence Domain Annotation using Language Models" (PSALM)

https://t.co/80WSlT0uMp