Chiara Ricci-Tam

The paper uses a genomic language model to cluster and annotate noncoding sequences in prokaryotic genomes, identifying structured RNAs and their potential functions.

State, a set-based transformer trained on over 100 million perturbed cells, predicts perturbation responses in new cellular contexts better than mean, linear and deep learning baselines.

A reasoning LLM combining ESM3 embeddings with GO-GPT term predictions produces protein function annotations that experts rated tie-or-better than UniProt in 79% of cases (SFT model).

SO_SCPLOWTACKC_SCPLOW is a foundation model trained on human single-cell data that enables in-context learning for predicting perturbation effects without fine-tuning.

This paper introduces PerturbSpace, a method combining CRISPR perturbations with spatially hashed single-cell multiomics to study gene function in tissue architecture.

This paper describes the engineering of IS622 bridge recombinases to enable efficient and specific DNA rearrangements in the human genome, including insertion, inversion, and excision of up to 0.93 megabases.

scBaseCount is a single-cell RNA sequencing database that automates metadata extraction and data processing using AI, offering a large, standardized collection of gene expression data across multiple organisms and tissues.

A 40B-parameter DNA model trained on 9.3 trillion tokens scores coding and noncoding variants zero-shot, exposes interpretable sequence features, and writes chromosome-scale sequences.

This study evaluates 2A peptides for polycistronic gene expression in Dictyostelium discoideum, finding P2A most effective despite strain-dependent expression reductions.

The paper identifies a dimmer-switch gene regulation mechanism in yeast by decoupling transcription factor expression and activity.

The paper investigates the HbP2 enhancer in Drosophila, showing that cooperative binding of Bcd is insufficient to explain its sharp expression pattern, and identifies other factors like pioneer factors and histone modifiers as key contributors.