Citation metrics

441Citations
11h-index
11i10-index
3
2018
0
2019
9
2020
37
2021
55
2022
74
2023
79
2024
127
2025
52
2026

Source: Google Scholar, updated 2026-06-08. View profile ↗

* corresponding author. Bold = R. Prabakaran.

★ Selected publications


  1. Prabakaran, R*, Bromberg, Yana*, (2026) "Quantifying uncertainty in protein representations across models and tasks." Nature Methods,23:796-804. doi ↗ 9 citations
  2. Prabakaran, R*, Bromberg, Yana*, (2025) "Deciphering enzymatic potential in metagenomic reads through DNA language models." Nucleic Acids Research,53(16):gkaf836. doi ↗ 3 citations
  3. Bromberg, Yana, Prabakaran, R, Kabir, Anowarul, Shehu, Amarda, (2024) "Variant effect prediction in the age of machine learning." Cold Spring Harbor Perspectives in Biology,16(7):a041467. doi ↗ 30 citations
  4. Prabakaran, R, Rawat, Puneet, Kumar, Sandeep, Gromiha, M Michael, (2021) "Evaluation of in silico tools for the prediction of protein and peptide aggregation on diverse datasets." Briefings in Bioinformatics,22(6):bbab240. doi ↗ 18 citations
  5. Prabakaran, R, Rawat, Puneet, Thangakani, A Mary, Kumar, Sandeep, Gromiha, M Michael, (2021) "Protein aggregation: in silico algorithms and applications." Biophysical reviews,13:71-89. doi ↗ 68 citations
  6. Prabakaran, R, Rawat, Puneet, Kumar, Sandeep, Gromiha, M Michael, (2021) "ANuPP: a versatile tool to predict aggregation nucleating regions in peptides and proteins." Journal of molecular biology,433(11):166707. doi ↗ 74 citations
  7. Prabakaran, R, Goel, Dhruv, Kumar, Sandeep, Gromiha, M Michael, (2017) "Aggregation prone regions in human proteome: Insights from large‐scale data analyses." Proteins: Structure, Function, and Bioinformatics,85(6):1099-1118. doi ↗ 32 citations

All publications


  1. Prabakaran, R*, Bromberg, Yana*, (2026) "Quantifying uncertainty in protein representations across models and tasks." Nature Methods,23:796-804. doi ↗ 9 citations
  2. Prabakaran, R*, Bromberg, Yana*, (2025) "Deciphering enzymatic potential in metagenomic reads through DNA language models." Nucleic Acids Research,53(16):gkaf836. doi ↗ 3 citations
  3. Rawat, Puneet, Crescioli, Silvia, Prabakaran, R, Sharma, Divya, Greiff, Victor, Reichert, Janice M, (2025) "YAbS: The Antibody Society’s antibody therapeutics database." mAbs,17(1):2468845. doi ↗ 7 citations
  4. Prabakaran, R, Bromberg, Yana, (2025) "Functional profiling of the sequence stockpile: a protein pair-based assessment of in silico prediction tools." Bioinformatics,41(2):btaf035. doi ↗ 3 citations
  5. Bromberg, Yana, Prabakaran, R, Kabir, Anowarul, Shehu, Amarda, (2024) "Variant effect prediction in the age of machine learning." Cold Spring Harbor Perspectives in Biology,16(7):a041467. doi ↗ 30 citations
  6. Rawat, Puneet, Sharma, Divya, Prabakaran, R, Ridha, Fathima, Mohkhedkar, Mugdha, Janakiraman, Vani, Gromiha, M Michael, (2022) "Ab-CoV: a curated database for binding affinity and neutralization profiles of coronavirus-related antibodies." Bioinformatics,38(16):4051-4052. doi ↗ 13 citations
  7. Prabakaran, R, Rawat, Puneet, Yasuo, Nobuaki, Sekijima, Masakazu, Kumar, Sandeep, Gromiha, M Michael, (2022) "Effect of charged mutation on aggregation of a pentapeptide: Insights from molecular dynamics simulations." Proteins: Structure, Function, and Bioinformatics,90(2):405-417. doi ↗ 7 citations
  8. Prabakaran, R, Jemimah, Sherlyn, Rawat, Puneet, Sharma, Divya, Gromiha, M Michael, (2021) "A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19." Scientific reports,11(1):24073. doi ↗ 28 citations
  9. Prabakaran, R, Rawat, Puneet, Kumar, Sandeep, Gromiha, M Michael, (2021) "Evaluation of in silico tools for the prediction of protein and peptide aggregation on diverse datasets." Briefings in Bioinformatics,22(6):bbab240. doi ↗ 18 citations
  10. Rawat, Puneet, Prabakaran, R, Kumar, Sandeep, Gromiha, M Michael, (2021) "AbsoluRATE: An in-silico method to predict the aggregation kinetics of native proteins." Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics,1869(9):140682. doi ↗ 17 citations
  11. Rawat, Puneet, Prabakaran, R, Kumar, Sandeep, Gromiha, M Michael, (2021) "Exploring the sequence features determining amyloidosis in human antibody light chains." Scientific Reports,11(1):13785. doi ↗ 40 citations
  12. Prabakaran, R, Rawat, Puneet, Thangakani, A Mary, Kumar, Sandeep, Gromiha, M Michael, (2021) "Protein aggregation: in silico algorithms and applications." Biophysical reviews,13:71-89. doi ↗ 68 citations
  13. Prabakaran, R, Rawat, Puneet, Kumar, Sandeep, Gromiha, M Michael, (2021) "ANuPP: a versatile tool to predict aggregation nucleating regions in peptides and proteins." Journal of molecular biology,433(11):166707. doi ↗ 74 citations
  14. Rawat, Puneet, Prabakaran, R, Kumar, Sandeep, Gromiha, M Michael, (2020) "AggreRATE-Pred: a mathematical model for the prediction of change in aggregation rate upon point mutation." Bioinformatics,36(5):1439-1444. doi ↗ 25 citations
  15. Rawat, Puneet, Prabakaran, R, Sakthivel, R, Mary Thangakani, A, Kumar, Sandeep, Gromiha, M Michael, (2020) "CPAD 2.0: a repository of curated experimental data on aggregating proteins and peptides." Amyloid,27(2):128-133. doi ↗ 50 citations
  16. Prabakaran, R, Nikam, Rahul, Kumar, Sandeep, Gromiha, M Michael, (2017) "Influence of Amino Acid Properties for Characterizing Amyloid Peptides in Human Proteome." Intelligent Computing Theories and Application,10362:541-548. doi ↗ 1 citations
  17. Prabakaran, R, Goel, Dhruv, Kumar, Sandeep, Gromiha, M Michael, (2017) "Aggregation prone regions in human proteome: Insights from large‐scale data analyses." Proteins: Structure, Function, and Bioinformatics,85(6):1099-1118. doi ↗ 32 citations