COVID-19 Knowledge Graph: a computable, multi-modal, cause-and-effect knowledge model of COVID-19 pathophysiology. - Daniel Domingo-Fernández; Shounak Baksi; Bruce Schultz; Yojana Gadiya; Reagon Karki; Tamara Raschka; Christian Ebeling; Martin Hofmann-Apitius; Alpha Tom Kodamullil (Bioinform., 2021)

Ensembles of knowledge graph embedding models improve predictions for drug discovery. - Daniel Rivas-Barragan; Daniel Domingo-Fernández; Yojana Gadiya; David Healey (Briefings Bioinform., 2022)

SASC: A simple approach to synthetic cohorts for generating longitudinal observational patient cohorts from COVID-19 clinical data. - Takoua Khorchani; Yojana Gadiya; Gesa Witt; Delia Lanzillotta; Carsten Claussen; Andrea Zaliani (Patterns, 2022)

Causal reasoning over knowledge graphs leveraging drug-perturbed and disease-specific transcriptomic signatures for drug discovery. - Daniel Domingo-Fernández; Yojana Gadiya; Abhishek Patel; Sarah Mubeen; Daniel Rivas-Barragan; Chris W. Diana; Biswapriya B. Misra; David Healey; John C. Rokicki; Viswa Teja S. S. Colluru (PLoS Comput. Biol., 2022)

PEMT: a patent enrichment tool for drug discovery. - Yojana Gadiya; Andrea Zaliani; Philip Gribbon; Martin Hofmann-Apitius (Bioinform., 2023)

Exploring the known chemical space of the plant kingdom: insights into taxonomic patterns, knowledge gaps, and bioactive regions. - Daniel Domingo-Fernández; Yojana Gadiya; Sarah Mubeen; David Healey; Bryan H. Norman; Viswa Teja S. S. Colluru (J. Cheminformatics, 2023)

BioDataFuse: Enhancing data interoperability through modular queries and knowledge graph construction. - Tooba Abbassi-Daloii; Yojana Gadiya; Ammar Ammar; Egon L. Willighagen; Ana Claudia Sima; Hasan Balci (SWAT4HCLS, 2024)

MARS: A neurosymbolic approach for interpretable drug discovery. - Lauren Nicole Delong; Yojana Gadiya; Paola Galdi; Jacques D. Fleuriot; Daniel Domingo-Fernández (CoRR, 2024)

Curating, Collecting, and Cataloguing Global COVID-19 Datasets for the Aim of Predicting Personalized Risk. - Sepehr Golriz Khatami; Astghik Sargsyan; Maria Francesca Russo; Daniel Domingo-Fernández; Andrea Zaliani; Abish Kaladharan; Priya Sethumadhavan; Sarah Mubeen; Yojana Gadiya; Reagon Karki; Stephan Gebel; Ram Kumar Ruppa Surulinathan; et al. (Data, 2024)

Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning. - Yojana Gadiya; Olga Genilloud; Ursula Bilitewski; Mark Brönstrup; Leonie von Berlin; Marie Attwood; Philip Gribbon; Andrea Zaliani (J. Chem. Inf. Model., 2025)