Alfonso Valencia

Architectonic Spandrels in the Origin of Enzymatic Function

The paper investigates whether functional frustration in proteins is an evolutionary adaptation or a byproduct of fold architecture, finding that frustration hotspots are inherent physical constraints co-opted for function.

PhysiCelldFBA: Linking single-cell genome-scale metabolism to spatially explicit multicellular dynamics

PhysiCelldFBA links single-cell metabolism to multicellular spatial dynamics by integrating genome-scale metabolic models with agent-based simulations.

Interpretable Forecasting of Kidney Cancer Progression via Generative AI and Symbolic Reasoning

This paper uses generative and symbolic AI to forecast kidney cancer progression from cross-sectional data, providing interpretable models and molecular insights.

A Genetic Atlas of Direct and Inverse Neuropsychiatric-Cancer Comorbidity

The paper identifies genetic correlations between neuropsychiatric disorders and cancers, revealing shared and opposing biological mechanisms.

Intelligent Tool Orchestration for Rapid Mechanistic Model Prototyping: MCP Servers as AI-Biology Interfaces

This paper introduces an AI-assisted framework for rapid prototyping of multicellular mechanistic models using LLMs and MCP servers to integrate multiple modeling tools.

An enhancer-centric approach applied to human immune system epigenomes revealed the association of macrophage enhancers with cardiovascular disease

The paper identifies associations between macrophage enhancers and cardiovascular disease variants using epigenomic data from immune cells.

Airway organoids reveal patterns of Influenza A tropism and adaptation in wildlife species

The paper uses airway organoids from wildlife and livestock species to assess susceptibility to influenza viruses, revealing species-specific infection patterns and adaptation mechanisms.

EBEx: an Ensemble-Based Explainable Framework for Gene Calling in Heterogeneous Diseases

EBEx prioritizes disease-relevant genes from transcriptomic data in COPD by integrating data-driven signals with curated gene sets and network-based expansion, identifying biologically relevant candidates and molecular subgroups.

Sex-specific transcriptome similarity networks elucidate comorbidity relationships

The paper identifies sex-specific transcriptomic similarities between comorbid diseases and finds that 13-16% of disease pairs show sex-specific transcriptome similarity, recapitulating 53-60% of known sex-specific comorbidities.

Three-Dimensional Epigenome Roadmap of Human B-cell Differentiation Uncovers Mechanisms of Humoral Immunity and Oncogenesis

This paper creates a 3D epigenomic roadmap of human B-cell differentiation, revealing regulatory mechanisms in immunity and cancer.

Disentangling the genetic and non-genetic origin of disease co-occurrences

The paper disentangles genetic and non-genetic factors contributing to disease co-occurrences using RNA-seq, heritability data, and UK Biobank genomic data.

A Unified Framework for TCR-pMHC Structural Model Assessment

The paper develops a framework to assess the quality of TCR-pMHC structural models without experimental references, demonstrating its effectiveness in expanding structural coverage and improving model evaluation.

Patient stratification reveals the molecular basis of disease comorbidities

The paper develops a method to generate a disease network using RNA-seq data, revealing molecular mechanisms behind comorbidities and identifying new associations through patient stratification.

Open Benchmarking for Cell-Based Multiscale Models: Lessons from a Community Initiative

This paper presents a community-driven benchmarking initiative for cell-based multiscale models, highlighting variations in tool implementations and advocating for standardized benchmarks and interoperability.

Deep representation learning for temporal inference in cancer omics: a systematic review

This paper reviews the use of deep representation learning, particularly VAEs, in cancer omics to model temporal processes, highlighting limitations in capturing cancer progression dynamics.

Using Constraint-Based Metabolic Modeling to Elucidate Drug-Induced Metabolic Changes in a Cancer Cell Line

This study uses metabolic modeling and transcriptomics to analyze drug-induced metabolic changes in gastric cancer cells, revealing synergistic effects and potential therapeutic targets.

Explainable Generative AI Uncovers a Molecular Continuum in Medulloblastoma with Implications for Rare Cancer Subtyping and Treatment Equity

This study uses synthetic data generation and explainable AI to uncover an intermediate subgroup in medulloblastoma, highlighting treatment disparities and supporting the continuum hypothesis between Groups 3 and 4.

Sequence-based coevolutionary prediction of species-specific interactomes

This study introduces CM2.0, a coevolution-based method to predict species-specific PPIs, revealing conserved and species-specific interactions in E. coli, S. enterica, and S. aureus.

p53 rapidly restructures 3D chromatin organization to trigger a transcriptional response

This study shows p53 rapidly changes 3D chromatin structure to regulate gene transcription, identifying 340 new direct target genes.

3Dmapper: A Command Line Tool For BioBank-scale Mapping Of Variants To Protein Structures

3Dmapper maps annotated protein positions and variants to protein structures efficiently and reliably for large-scale genomic data analysis.

Frustraevo: A Web Server To Localize And Quantify The Conservation Of Local Energetic Frustration In Protein Families

FrustraEvo calculates and quantifies the conservation of local energetic frustration in protein families to identify evolutionary stability and functional constraints.

Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes

This paper uses multilayer network analysis to identify molecular determinants of severity in Congenital Myasthenic Syndromes by integrating protein-protein interactions, pathways, and metabolomics data.

PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks

PhysiBoSS 2.0 integrates stochastic Boolean and agent-based models for multiscale cancer simulations, improving modularity and functionality.

The Evolution of Local Energetic Frustration in Protein Families

The paper analyzes local energetic frustration in protein families to uncover stability and function constraints, demonstrating its application to SARS-CoV-2 and poorly characterized proteins.

A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution

The paper introduces liCHi-C, a low-input Hi-C method, to map promoter-enhancer interactions in clinical samples and identify disease-relevant regulatory elements and structural variants.

Optimizing dosage-specific treatments in a multi-scale model of a tumor growth

The paper develops an HPC-optimized workflow to explore treatment strategies for tumor growth using a multi-scale model, finding that spatial geometry and population variability affect treatment effectiveness.

Patient-specific Boolean models of signaling networks guide personalized treatments

The paper develops patient-specific Boolean models of prostate cancer signaling networks to identify actionable targets for personalized treatment, finding dose-dependent effects of inhibitors on key targets.

The structural coverage of the human proteome before and after AlphaFold

This study quantifies how AlphaFold's structural models increase human proteome coverage from 48% to 76% and reduce the dark proteome from 26% to 10%.

A genome-wide analysis identifies DIDO3 binding at active chromatin and topological boundaries in mouse stem cells

This study identifies DIDO3 binding at active chromatin and topological boundaries in mouse stem cells, linking it to chromatin organization and transcriptional regulation.