Michal Linial B

Spliceosomal miR-99b Regulates SPACA6-AS1 Pre-mRNA Levels and Promotes Malignant Phenotypes in Breast Cancer

This study identifies miR-99b's nuclear role in regulating SPACA6-AS1 pre-mRNA splicing and its contribution to breast cancer progression.

OTRec: Deep learning recommender for prospective druggable disease-target associations

OTRec is a deep learning model that recommends druggable disease-target associations, outperforming existing methods in both retrospective and cross-validation settings.

DJ-1/PARK7 Determines miRNA Network Plasticity During Genotoxic Stress

This study shows DJ-1/PARK7 influences miRNA network plasticity during genotoxic stress by altering miRNA abundance and regulatory machinery.

Signatures of Micropeptides Encoded by lncRNAs in Cancer Progression and Metastasis

This study identifies micropeptides encoded by lncRNAs in cancer, showing they have distinct sequence features and structural potential, suggesting they may serve as biomarkers and therapeutic targets.

A conserved regulatory atlas reveals enhancers critical for mouse and human gonadal development

The paper constructs a comparative regulatory atlas of gonad development using mouse and human data, identifies a conserved enhancer critical for gonadal development, and prioritizes non-coding variants in DSD patients.

On the state of protein function prediction: a report on the fourth CAFA challenge

This paper reports on the fourth CAFA challenge, showing improvements in Gene Ontology term prediction but highlighting challenges in new evaluation settings.

MAGI: Mechanistic Consequences of Genetic Variants via Genomic Foundation Models

MAGI provides mechanistic insights into genetic variants by integrating genomic data and clinical annotations to improve variant interpretation and generate testable hypotheses.

Manipulating PARK7/DJ-1 Levels by Genotoxic Stress Alters Noncoding RNAs and Cellular Homeostasis

This study shows that altering DJ-1 levels changes non-coding RNA expression and cellular homeostasis after X-ray exposure.

Integrative Gene-Centric Analysis of Breast Cancer: High-Confidence Germline Predisposition Genes from Population-Scale Cohorts

The paper identifies high-confidence breast cancer predisposition genes using multi-ethnic genomic data and integrates GWAS, TWAS, and PWAS to refine the genetic architecture of heritable breast cancer.

Deciphering the mechanistic basis for the pathological effect of the Gαo E246K mutation in neurodevelopmental disorder

The paper investigates the molecular mechanism of the Gαo E246K mutation in neurodevelopmental disorders, showing it disrupts the GTPase cycle by impairing Gβγ dissociation, leading to dominant-negative effects.

Temporal shifts in microRNAs signify the inflammatory state of primary murine microglial cells

This study identifies miRNA expression changes in activated microglia, showing their role in inflammation and potential as biomarkers for neurodegenerative diseases.

Transitional lncRNA Signatures Reveal Distinct Stages of Cancer Progression and Metastasis

This study identifies transitional lncRNAs (Tr-lncRNAs) associated with cancer progression stages and metastasis using TCGA data, revealing cancer-type specific and shared lncRNA signatures.

Patient-Specific Pharmacogenomics unveils xCT Regulation Pathways in Colon Cancer

This study identifies xCT regulation pathways in colon cancer using patient-specific models and reveals potential therapeutic targets for chemotherapy resistance.

PWAS Hub: Exploring Gene-Based Associations of Common Complex Diseases

PWAS Hub identifies gene-disease associations for 99 common diseases using proteome-wide association analysis, with sex-specific insights and comparison to GWAS results.

Knockdown of DJ-1 Resulted in a Coordinated Activation of the Innate Immune Antiviral Response in HEK293 Cell Line

This study shows that knocking down DJ-1 in HEK293 cells activates an antiviral innate immune response and affects RNA metabolism and mitochondrial functions.

Transcription network of SLC7A11 (xCT) in colon cancer provides clinical targets for metabolic regulation and cell proliferation

The paper analyzes RNA-seq data from CRC patients to identify SLC7A11's role in metabolic regulation and cell proliferation, linking it to clinical outcomes and therapeutic responses.

DROP-DEEP: Dimensionality Reduction for Polygenic Risk Score Using Deep Learning Approach

DROP-DEEP improves polygenic risk score prediction by using deep learning for dimensionality reduction, outperforming traditional methods on hypertension and other traits.

Protein Language Models Expose Viral Mimicryand Immune Escape

The paper uses protein language models to distinguish human and viral proteins, identifying immune escape mechanisms through error analysis.

Detecting Anomalous Proteins Using Deep Representations

This paper uses deep learning to detect anomalous proteins by identifying unusual properties in function, phylogenetic families, and sequence segmentation.

Profiles and Dynamics of the Transcriptome of Microglial Cells Reveal their Inflammatory Status

This study examines how microglia respond to LPS and bzATP activation, finding that only combined treatment leads to a sustained inflammatory gene expression profile.

Disease-associated programming of cell memory in glycogen storage disorder type 1a

This paper shows that GSD1a patient fibroblasts retain a reversible disease phenotype in vitro, driven by epigenetic and transcriptional changes, and that a drug can reverse these effects.

Selecting Covariates for Genome-Wide Association Studies

This paper evaluates covariate selection in GWAS for 36 UK-Biobank traits, proposing guidelines to improve power and reduce computational burden.

The Etiology of Hypothyroidism Is Revealed by Alternative Genetics Association Study Methodologies

The paper uses proteome-wide association study (PWAS) and other methods to identify genes associated with hypothyroidism, revealing different facets of its etiology including autoimmunity and sex-related gene enrichment.

Inferring microRNA regulation: A proteome perspective

The paper predicts miRNA-regulated genes using a protein-based machine learning framework, showing better performance than genomic approaches and identifying exceptions like GPCRs.

Recessive and sex-dependent genetic effects in primary hypertension

This study uses proteome-wide association study (PWAS) to identify genes associated with hypertension, finding sex-dependent genetic effects and recessive inheritance.

ProteinBERT: A universal deep-learning model of protein sequence and function

A ~16M-parameter protein language model, pretrained on ~106M UniRef90 proteins by denoising sequences and Gene Ontology annotations, rivals larger TAPE models using linear-cost global attention.

Recessive effects in cancer predisposition exposed by genome-wide and proteome-wide association studies

This study uses GWAS and PWAS on UK Biobank data to identify 137 cancer risk loci, highlighting recessive effects and cancer-type specificity.

Evolutionary and Functional Lessons from Human-Specific Amino-Acid Substitution Matrices

The paper constructs human-specific amino-acid substitution matrices from genetic variation data to better represent proteomic variation within the human population and reveal new evolutionary insights.

Structural analysis of de novo STXBP1 mutation in complex with syntaxin 1A reveals a major alteration in the interaction interface in a child with developmental delay and spasticity

The paper identifies a de novo STXBP1 mutation in a child with developmental delay and spasticity, showing how it disrupts the STXBP1-syntaxin 1A interaction through structural analysis.

PWAS: Proteome-Wide Association Study

PWAS detects protein-coding genes associated with phenotypes by analyzing proteomic context and using machine learning, showing improved detection of causal genes and new associations.