Mohieddin Jafari

Conjunctive Targeting Links Drug Synergy to Emergent Proteome Structural States

This paper introduces CoPPRA, a structural proteomics method to analyze drug combinations in AML, revealing peptide-level accessibility changes linked to conjunctive targeting.

Chemical Proteomics of Residual Acute Myeloid Leukemia Cells Reveals Therapeutic Vulnerabilities

This study uses CoPISA and proteomics to analyze venetoclax-azacitidine response in AML cells, identifying adaptive vulnerabilities like NRP2.

DORSSAA: Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay

DORSSAA provides a platform for analyzing stability and solubility alteration data to identify drug-protein interactions and therapeutic targets.

Shifting Beyond Classical Drug Synergy in Combinatorial Therapy through Solubility Alterations

This paper introduces CoPISA, a proteomics workflow that identifies combination-specific protein targets in AML, revealing conjunctional targeting mechanisms beyond classical drug synergy.

CoPISA: Combinatorial Proteome Integral Solubility/Stability Alteration analysis

CoPISA provides a proteomics dataset profiling protein solubility and stability responses to single and combined drug treatments in AML cell lines, enabling analysis of combinatorial drug effects.

Informative Missingness in Nominal Data: A Graph-Theoretic Approach to Revealing Hidden Structure

The paper presents a graph-theoretic approach to analyze missing data in nominal datasets, revealing hidden structures by treating missingness as informative signals.

SOORENA: Self-lOOp containing or autoREgulatory Nodes in biological network Analysis

SOORENA identifies autoregulatory mechanisms in biological networks by analyzing PubMed abstracts, finding 97,657 protein-specific records and generating a curated database.

Targeting AML Resistance with Two Novel Combinations Demonstrate Superior Efficacy in TP53, HLA-B, MUC4 and FLT3 mutations

This study evaluates two drug combinations for AML treatment, showing improved efficacy over venetoclax-based therapy in specific mutation profiles.

Facilitating the design of combination therapy in cancer using multipartite network models: Emphasis on acute myeloid leukemia

This study uses multipartite network models to predict effective drug combinations and patient subclasses in acute myeloid leukemia using drug response data.

NIMAA: an R/CRAN package to accomplish NomInal data Mining AnAlysis

NIMAA is an R package for nominal data mining that provides tools for graph construction, clustering, and visualization, applied to a biological dataset.

Network-based modeling of herb combinations in Traditional Chinese Medicine

This study uses a network-based method to quantify interactions in TCM herb pairs, finding that frequently used pairs have shorter network distances, suggesting therapeutic effects through protein interactions.

Can we assume the gene expression profile as a proxy for signaling network activity?

This study evaluates whether gene expression profiles can reliably infer signaling network activity and finds they are not more coherent with causal relationships than random data.

An insight to HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) pathogenesis; evidence from high-throughput data integration and meta-analysis

This study identifies key genes involved in HAM/TSP pathogenesis through high-throughput data integration and meta-analysis, revealing differential expression of STAT1, TAP1, and PSMB8.

IMMAN: an R/Bioconductor package for Interolog protein network reconstruction, Mapping and Mining ANalysis

IMMAN is an R/Bioconductor package that reconstructs interolog protein networks by integrating PPINs and enables conservation analysis across species for protein function prediction.

CINNA: An R/CRAN package to decipher Central Informa-tive Nodes in Network Analysis

CINNA compares centrality measures to identify the most informative nodes in networks using dimensionality reduction.

A systematic survey of centrality measures for protein-protein interaction networks

The paper systematically evaluates centrality measures in yeast protein-protein interaction networks to identify which measures best predict influential proteins.

A Rational Drug Combination Design to Inhibit Epithelial-Mesenchymal Transition in a Three-Dimensional Microenvironment

The paper designs a drug combination to inhibit EMT in a 3D microenvironment by targeting histone deacetylases, SRC, and IKBK, showing effectiveness in a microfluidic model.

A Logic-Based Dynamic Modeling Approach to Explicate the Evolution of the Central Dogma of Molecular Biology

This paper modifies and mathematically models the Central Dogma of molecular biology using Boolean networks to show increased complexity and robustness in biological systems.

Systems Biomedicine of Rabies Delineates the Affected Signaling Pathways

This study identifies signaling pathways affected by rabies virus using systems biomedicine approaches, revealing potential drug targets through network analysis of gene expression data.