Daniele Merico

The paper introduces Rhaister, a perturbation-response predictor that uses summary statistics to predict drug responses, outperforming virtual-cell models in speed and accuracy.

ProteomeScan identifies protein targets for drug-like molecules through proteome-wide docking and analysis, showing improved accuracy over random baselines.

SigSpace uses an LLM to interpret drug response signatures from cancer cell lines, generating summaries that outperform random baselines in matching to drug identity or mechanism of action.

The paper introduces Tahoe-x1, a large-scale perturbation-trained single-cell foundation model with 3 billion parameters, achieving state-of-the-art performance in cancer-related tasks.

The paper identifies shared and divergent genetic mechanisms across psychiatric disorders using gene-set burden analysis of copy number variants.

A 100-million-cell atlas: 50 cancer lines pooled as spheroid villages, treated with 379 drugs at several doses, profiled by combinatorial-barcoding scRNA-seq and embedded with a 10-dimensional scVI model.

The paper curates a high-confidence set of pathogenic and likely pathogenic UTR variants and evaluates deep learning models for predicting their functional impact.

This study identifies somatic copy number variants (sCNVs) in schizophrenia cases, revealing their contribution to risk and specific NRXN1 disruptions.

The paper develops a genome-wide rare variant score linked to morphological subtypes of ASD and finds higher scores in dysmorphic ASD cases.

The paper investigates the association between gene copy number variation and mental health traits in children, finding links to ADHD, OCD, and cognitive biomarkers.

This study evaluates off-target effects of steric-blocking oligonucleotides using RNA-seq and finds that in silico methods have limited utility for predicting these effects.

This paper identifies ultra-rare variants in NOTCH1 and FLT4 associated with tetralogy of Fallot using burden analysis of genome sequences from 231 individuals.

This paper shows that the ATP7B variant c.1934T>G causes exon 6 skipping, leading to loss of function and confirming its pathogenicity in Wilson Disease.

Step-by-step protocol for interpreting omics gene lists via g:Profiler or GSEA enrichment testing, then grouping redundant enriched pathways into themes with Cytoscape Enrichment Map.

This study uses CRISPR to knockout 10 ASD-related genes in iPSCs, revealing reduced functional connectivity in neurons despite diverse gene functions.

The paper matches drug transcriptional signatures to synaptic gene network disruptions to identify known and novel candidate drugs for schizophrenia.

The paper benchmarks variant impact predictors using allele-specific binding ChIP-seq data, finding deep learning methods perform best but have room for improvement.

This study identifies eight genome-wide significant CNV loci associated with schizophrenia using a large cohort of 41,321 subjects.