Nabil Ibtehaz

MedicineBiochemistry, Genetics and Molecular BiologyComputer Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 11 papers. Top paper: “NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation”.

NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation

Nature Communications(2025)10.1038/s41467-025-56261-7

N/A

0.598DataRank · unranked

53 citations

Zicong Zhang, Nabil Ibtehaz, Xiao Wang, Tsukasa Nakamura, Pranav Punuru +2 more

Predicting transcriptional activation domain function using Graph Neural Networks

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.05.08.593266

N/A

0.104DataRank · unranked

1 citations

Bradley K. Broyles, Yuanyuan Zhang, Nabil Ibtehaz, Alexandre M. Erkine, Daisuke Kihara +1 more

Domain-PFP allows protein function prediction using function-aware domain embedding representations

Communications Biology(2023)10.1038/s42003-023-05476-9

N/A

0DataRank · unranked

35 citations

Yuki Kagaya, Daisuke Kihara, Nabil Ibtehaz

NuFold: A Novel Tertiary RNA Structure Prediction Method Using Deep Learning with Flexible Nucleobase Center Representation

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.09.20.558715

N/A

0DataRank · unranked

12 citations

Zicong Zhang, Nabil Ibtehaz, Xiao Wang, Tsukasa Nakamura, David Huang +2 more

ACC-UNet: A Completely Convolutional UNet model for the 2020s

arXiv (Cornell University)(2023)10.48550/arxiv.2308.13680

N/A

0DataRank · unranked

2 citations

Daisuke Kihara, Nabil Ibtehaz

GO2Sum: Generating Human Readable Functional Summary of Proteins from GO Terms

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.11.10.566665

N/A

0DataRank · unranked

1 citations

Nabil Ibtehaz, Daisuke Kihara, Swagarika Jaharlal Giri

Domain-PFP: Protein Function Prediction Using Function-Aware Domain Embedding Representations

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.08.23.554486

N/A

0DataRank · unranked

0 citations

Yuki Kagaya, Daisuke Kihara, Nabil Ibtehaz

GO2Sum: generating human-readable functional summary of proteins from GO terms

npj Systems Biology and Applications(2024)10.1038/s41540-024-00358-0

N/A

0DataRank · unranked

4 citations

Nabil Ibtehaz, Daisuke Kihara, Swagarika Jaharlal Giri

Application of Sequence Embedding in Protein Sequence-Based Predictions

arXiv (Cornell University)(2021)10.48550/arxiv.2110.07609

N/A

0DataRank · unranked

1 citations

Daisuke Kihara, Nabil Ibtehaz

Queryome: Orchestrating Retrieval, Reasoning, and Synthesis across Biomedical Literature

bioRxiv (Cold Spring Harbor Laboratory)(2025)10.64898/2025.12.22.696019

N/A

0DataRank · unranked

0 citations

Nabil Ibtehaz, Swagarika Jaharlal Giri, Harsha Srirangam, Emilia A Tugolukova, Daisuke Kihara +1 more

Differentiation and classification of bacterial endotoxins based on surface enhanced Raman scattering and advanced machine learning

Nanoscale(2022)10.1039/d2nr01277d

N/A

0DataRank · unranked

59 citations

Beibei Xu, James Haverstick, Nabil Ibtehaz, Artur Muszyński, Xianyan Chen +4 more