Baldomero Oliva

ExoFILT uses transfer learning to automate exocytic event detection in single-particle tracking data, improving speed and consistency.

ModCRE-NN predicts transcription factor DNA-binding motifs by integrating structural and evolutionary data, showing improved performance under low similarity and uncertainty.

ModCRElib is a package for modeling cis-regulatory elements, offering tools for TF-DNA interaction analysis, binding motif prediction, and regulatory complex modeling.

The paper defines the DNA-binding syntax and chromatin remodeling capacities of bHLH transcription factors across cell differentiation, reprogramming, and cancer using integrated genomic and structural data.

The paper uses multimodal imaging to study the dynamic structure of the exocyst complex during exocytosis, revealing its conformational changes and tethering mechanism.

The paper identifies a 127-gene core network in human astrocytes linking aging to neurodegenerative and cardiovascular diseases through proteostasis and stress signaling.

This study identifies a novel GSK-3β-eIF2Bε-BACE1 axis that links stress response dysregulation to amyloidogenesis in Alzheimer's disease, independent of canonical eIF2 phosphorylation.

The paper investigates the role of CAT-CAT E-boxes in neurogenesis, showing their association with chromatin accessibility, DNA demethylation, and evolutionary constraint through ChIP-seq, scRNA-seq, ATAC-seq, and DNA methylation data.

This study integrates prostate tissue expression datasets with machine learning to identify biomarkers that improve Gleason scoring accuracy in prostate cancer, achieving a minimum precision of 0.80.

The paper develops two novel knowledge graph embedding algorithms, DLemb and BioKG2Vec, which outperform existing methods in predicting gene-disease associations, particularly for diseases with limited information.

The paper reconstructs and assays ancient enzymes to show that losing selenocysteine in GPX6 led to functional loss and convergent evolution in mammalian oxidoreductases.

Genopyc is a Python library for analyzing complex diseases' genetic basis, enabling integration and visualization of genomic data to uncover dysregulated pathways.

PyF2F measures fluorophore-to-fluorophore distances from PICT data, validated on a published dataset.

The paper identifies shared proteins and pathways between cardiovascular and cognitive diseases using protein interaction network analysis, highlighting oxidative and glycative stress mechanisms in vascular cognitive impairment.

This paper constructs a patient repository by integrating transcriptomics datasets to generate real-world data for clinical trialling, improving downstream biological conclusions by 45%.

The paper introduces a structure-based learning approach to predict TF binding preferences and model TF regulatory complexes, demonstrating its effectiveness over existing methods in cases of remote homology.

This paper identifies amino acid changes and genes associated with longevity across mammals, showing their potential to improve human lifespan heritability interpretation.

RADI improves the computational efficiency of direct-coupling analysis by reducing the alphabet size, achieving faster execution with comparable or better accuracy than traditional methods.

The paper develops a computational method to predict DNA-binding preferences of C2H2-ZF domains using structural models and applies it to predict CTCF's binding sites.

The paper introduces PepI-Covid19, a database of peptides targeting SARS-CoV-2 RBD-ACE2 interaction, designed using PiPreD method to preserve key interactions.

The paper uses TPMS to model drug mechanisms and identify biomarkers linked to macular degeneration as an adverse effect of heart failure treatment with sacubitril/valsartan.

The paper identifies mutations in the influenza A virus nucleoprotein that enable escape from importin-7 mediated nuclear import but reduce replicative fitness in human cells.

This study introduces PxEA, a network-based method to identify drugs targeting common pathways across diseases, demonstrating drug repurposing opportunities for autoimmune disorders and comorbid conditions like type 2 diabetes and Alzheimer's disease.