Analysis of Basic Clustering Algorithms for Numerical Estimation of Statistical Averages in Biomolecules. - Ramu Anandakrishnan; Alexey Onufriev (J. Comput. Biol., 2008)

An N log N approximation based on the natural organization of biomolecules for speeding up the computation of long range interactions. - Ramu Anandakrishnan; Alexey Onufriev (J. Comput. Chem., 2010)

H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations. - Ramu Anandakrishnan; Boris Aguilar; Alexey Onufriev (Nucleic Acids Res., 2012)

Multiscale Approximation with Graphical Processing Units for Multiplicative Speedup in Molecular Dynamics. - Ramu Anandakrishnan; Mayank Daga; Alexey Onufriev; Wu-chun Feng (BCB, 2016)

CAGm: a repository of germline microsatellite variations in the 1000 genomes project. - Nicholas Kinney; Kyle Titus-Glover; Jonathan D. Wren; Robin T. Varghese; Pawel Michalak; Han Liao; Ramu Anandakrishnan; Arichanah Pulenthiran; Lin Kang; Harold R. Garner (Nucleic Acids Res., 2019)

Estimating the number of genetic mutations (hits) required for carcinogenesis based on the distribution of somatic mutations. - Ramu Anandakrishnan; Robin T. Varghese; Nicholas Kinney; Harold R. Garner (PLoS Comput. Biol., 2019)

Scaling Out a Combinatorial Algorithm for Discovering Carcinogenic Gene Combinations to Thousands of GPUs. - Sajal Dash; Qais Al-Hajri; Wu-chun Feng; Harold R. Garner; Ramu Anandakrishnan (IPDPS, 2021)

Distributing Simplex-Shaped Nested for-Loops to Identify Carcinogenic Gene Combinations. - Sajal Dash; Mohammad Alaul Haque Monil; Junqi Yin; Ramu Anandakrishnan; Feiyi Wang (IPDPS, 2023)

Bigpicc: a graph-based approach to identifying carcinogenic gene combinations from mutation data. - Vladyslav Oles; Sajal Dash; Ramu Anandakrishnan (BMC Bioinform., 2025)