immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking. - Cédric R. Weber; Rahmad Akbar; Alexander Yermanos; Milena Pavlovic; Igor Snapkov; Geir Kjetil Sandve; Sai T. Reddy; Victor Greiff (Bioinform., 2020)

The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. - Milena Pavlovic; Lonneke Scheffer; Keshav Motwani; Chakravarthi Kanduri; Radmila Kompova; Nikolay Vazov; Knut Waagan; Fabian L. M. Bernal; Alexandre Almeida Costa; Brian Corrie; Rahmad Akbar; Ghadi S. Al Hajj; et al. (Nat. Mach. Intell., 2021)

Advancing protein language models with linguistics: a roadmap for improved interpretability. - Mai Ha Vu; Rahmad Akbar; Philippe A. Robert; Bartlomiej Swiatczak; Victor Greiff; Geir Kjetil Sandve; Dag Trygve Truslew Haug (CoRR, 2022)

ImmunoLingo: Linguistics-based formalization of the antibody language. - Mai Ha Vu; Philippe A. Robert; Rahmad Akbar; Bartlomiej Swiatczak; Geir Kjetil Sandve; Dag Trygve Truslew Haug; Victor Greiff (CoRR, 2022)

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. - Philippe A. Robert; Rahmad Akbar; Robert Frank 006; Milena Pavlovic; Michael Widrich; Igor Snapkov; Andrei Slabodkin; Maria Chernigovskaya; Lonneke Scheffer; Eva Smorodina; Puneet Rawat; Brij Bhushan Mehta; et al. (Nat. Comput. Sci., 2022)

Progress and challenges for the application of machine learning for neglected tropical diseases. - Chung Yuen Khew; Rahmad Akbar; Norfarhan Mohd. Assaad (F1000Research, 2023)

Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database. - Ahmad Al-Khdhairawi; Danish Sanuri; Rahmad Akbar; Su Datt Lam; Shobana Sugumar; Nazlina Ibrahim; Sylvia Chieng; Fareed Sairi (Comput. Biol. Chem., 2023)

Linguistically inspired roadmap for building biologically reliable protein language models. - Mai Ha Vu; Rahmad Akbar; Philippe A. Robert; Bartlomiej Swiatczak; Geir Kjetil Sandve; Victor Greiff; Dag Trygve Truslew Haug (Nat. Mac. Intell., 2023)

Predictability of antigen binding based on short motifs in the antibody CDRH3. - Lonneke Scheffer; Eric Emanuel Reber; Brij Bhushan Mehta; Milena Pavlovic; Maria Chernigovskaya; Eve Richardson; Rahmad Akbar; Fridtjof Lund-Johansen; Victor Greiff; Ingrid Hobæk Haff; Geir Kjetil Sandve (Briefings Bioinform., 2024)

Linguistics-based formalization of the antibody language as a basis for antibody language models. - Mai Ha Vu; Philippe A. Robert; Rahmad Akbar; Bartlomiej Swiatczak; Geir Kjetil Sandve; Dag Trygve Truslew Haug; Victor Greiff (Nat. Comput. Sci., 2024)

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data. - Robert Frank 006; Michael Widrich; Rahmad Akbar; Günter Klambauer; Geir Kjetil Sandve; Philippe A. Robert; Victor Greiff (CoRR, 2025)