Alejandro Sifrim

This study examines the low adoption of computational gene-panel-selection tools in targeted spatial transcriptomics, finding that most researchers still use manual or vendor panels.

This paper develops a modular click-chemistry strategy to modify CRISPR RNPs without disrupting their formation, enhancing DNA accessibility and enabling genome imaging.

LipoGrid quantifies lipidomic and transcriptomic changes across 143 gene knockouts, revealing gene-lipid relationships and compensatory feedback mechanisms.

FOCUS integrates spatial multi-omics data through preprocessing, alignment, and resolution-matching, producing a unified data object compatible with scverse tools.

This study identifies rare variants and digenic interactions associated with congenital heart disease using a large-scale exome case-control analysis.

SubCellSpace identifies and characterizes subcellular mRNA localization patterns in spatial transcriptomics data using a computational framework.

The paper creates a single-nucleus transcriptomic atlas of oligodendrocytes in ALS, identifying disease-associated activation states and potential biomarkers.

This paper introduces MIMA, a deep learning framework for multi-omics integration and batch correction, which effectively removes batch effects and preserves biological information across modalities.

The paper shows that different luminal nutrients activate distinct calcium responses in submucosal and myenteric neurons of the mouse small intestine.

This study examines the interactions between A{beta}, tau, LATE-NC, -synuclein, and APOE {varepsilon}4 in 480 post-mortem brains, finding that tau is the strongest predictor of neurodegeneration while LATE-NC primarily affects hippocampal neuron loss.

This study identifies two epigenetically-defined spatial niches in glioblastoma that influence cell state plasticity through local and long-range molecular signals.

This study investigates how fibroblasts respond to stretching during skin expansion and shows their role in coordinating epidermal stem cell self-renewal.

This paper introduces Gtag&T-seq, a low-cost single-cell multi-omics method that reveals cell state plasticity and treatment response in melanoma subclones.

The paper uses single-cell RNA sequencing to identify five distinct mast cell subsets in the human colon, revealing layer-specific distribution and functional profiles.

This study uses single-cell genome-and-transcriptome sequencing to analyze the impact of chromosome instability on cellular states and development in human preimplantation embryos.

InDelible detects cryptic structural variants in exome sequencing data, improving diagnostic yield for developmental disorders by identifying variants missed by standard methods.

The paper identifies 21 candidate haploinsufficient genes associated with congenital heart disease through integrative analysis of CNVs and DNMs in CHD cases and controls.

The paper analyzes X-linked coding variation in developmental disorders, finding similar rates in males and females and estimating pathogenicity of inherited variants.

The paper identifies calcium signalling defects as a novel cause of congenital heart disease through whole exome sequencing and functional validation in zebrafish.

The paper identifies retrotransposition events in developmental disorders using exome sequencing data from the DDD study and shows their evolutionary constraints.

The paper analyzes de novo mutations in developmental disorders using exome sequencing of 4,293 families, identifying 94 genes and estimating a birth prevalence of 0.22-0.47%.

The paper identifies de novo mutations in fetal-brain active regulatory elements as a cause of 1-3% of neurodevelopmental disorders in patients without coding variants.

The paper introduces MrMosaic, a method to detect structural mosaicism using sequencing data, finding that blood-only testing misses over 50% of mosaic rearrangements.