Robin Pearce

2.9k citations

28 papers · 1.8k indexed · 2 hit papers · h-index 20

Structural Biology top 5%
Molecular Biology top 5%
- Protein Structure and Dynamics 19
- RNA and protein synthesis mechanisms 11
- Genomics and Phylogenetic Studies 4
- Machine Learning in Bioinformatics 3
Microbiology top 5%
Computational Theory and Mathematics top 5%
- Computational Drug Discovery Methods 3
Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research 4
Materials Chemistry
- Enzyme Structure and Function 11
- Machine Learning in Materials Science 3

Co-authors: Yang Zhang Wei Zheng Chengxin Zhang Xiaoqiang Huang Eric W. BellYang LiXiaogen Zhou Guijun Zhang
Cited by: Structural Biology Molecular Biology Microbiology
Journals: Bioinformatics (4 papers)Nature Communications (2 papers)Proteins Structure Function and Bioinformatics (2 papers)
Partner nations: United States China Singapore

In The Last Decade

Robin Pearce

28 papers receiving 1.8k citations

Hit Papers

align trajectories log scale

Peers

Countries citing papers authored by Robin Pearce

Since Specialization

Citations

This map shows the geographic impact of Robin Pearce's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Robin Pearce with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robin Pearce more than expected).

Fields of papers citing papers by Robin Pearce

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robin Pearce. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Robin Pearce. The network helps show where Robin Pearce may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Robin Pearce, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robin Pearce Line = papers co-authored together Robin Pearce links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	De novo protein fold design through sequence-independent fragment assembly simulations Proceedings of the National Academy of Sciences ·Robin Pearce,Xiaoqiang Huang,Gilbert S. Omenn,Yang Zhang	2023	7
2	Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction Nature Communications ·Yang Li,Chengxin Zhang,Chenjie Feng,Robin Pearce,Lucia Nevescanin-Moreno,Yang Zhang	2023	55
3	Fast and accurate Ab Initio Protein structure prediction using deep learning potentials PLoS Computational Biology ·Robin Pearce,Yang Li,Gilbert S. Omenn,Yang Zhang	2022	21
4	I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function predictionbreakdown → Nature Protocols ·Xiaogen Zhou,Wei Zheng,Yang Li,Robin Pearce,Chengxin Zhang,Eric W. Bell,Guijun Zhang,Yang Zhang	2022	297
5	Toward the solution of the protein structure prediction problem Journal of Biological Chemistry ·Robin Pearce,Yang Zhang	2021	84
6	Identification of 13 Guanidinobenzoyl- or Aminidinobenzoyl-Containing Drugs to Potentially Inhibit TMPRSS2 for COVID-19 Treatment International Journal of Molecular Sciences ·Xiaoqiang Huang,Robin Pearce,Gilbert S. Omenn,Yang Zhang	2021	13
7	Deep learning techniques have significantly impacted protein structure prediction and protein design Current Opinion in Structural Biology ·Robin Pearce,Yang Zhang	2021	81
8	Protein structure prediction using deep learning distance and hydrogen‐bonding restraints in CASP14 Proteins Structure Function and Bioinformatics ·Wei Zheng,Yang Li,Chengxin Zhang,Xiaogen Zhou,Robin Pearce,Eric W. Bell,Xiaoqiang Huang,Yang Zhang	2021	44
9	Fitting Low-Resolution Protein Structures into Cryo-EM Density Maps by Multiobjective Optimization of Global and Local Correlations The Journal of Physical Chemistry B ·Biao Zhang,F. Mattioli,Robin Pearce,Yang Zhang,Hong‐Bin Shen	2021	3
10	Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulationsbreakdown → Cell Reports Methods ·Wei Zheng,Chengxin Zhang,Yang Li,Robin Pearce,Eric W. Bell,Yang Zhang	2021	372
11	FASPR: an open-source tool for fast and accurate protein side-chain packing Bioinformatics ·Xiaoqiang Huang,Robin Pearce,Yang Zhang	2020	56
12	Computational design of SARS-CoV-2 spike glycoproteins to increase immunogenicity by T cell epitope engineering Computational and Structural Biotechnology Journal ·Edison Ong,Xiaoqiang Huang,Robin Pearce,Yang Zhang,Yongqun He	2020	16
13	Identifying the Zoonotic Origin of SARS-CoV-2 by Modeling the Binding Affinity between the Spike Receptor-Binding Domain and Host ACE2 Journal of Proteome Research ·Xiaoqiang Huang,Chengxin Zhang,Robin Pearce,Gilbert S. Omenn,Yang Zhang	2020	24
14	A New Protocol for Atomic-Level Protein Structure Modeling and Refinement Using Low-to-Medium Resolution Cryo-EM Density Maps Journal of Molecular Biology ·Biao Zhang,Xi Zhang,Robin Pearce,Hong‐Bin Shen,Yang Zhang	2020	19
15	SSIPe: accurately estimating protein–protein binding affinity change upon mutations using evolutionary profiles in combination with an optimized physical energy function Bioinformatics ·Xiaoqiang Huang,Wei Zheng,Robin Pearce,Yang Zhang	2019	41
16	Toward the Accuracy and Speed of Protein Side-Chain Packing: A Systematic Study on Rotamer Libraries Journal of Chemical Information and Modeling ·Xiaoqiang Huang,Robin Pearce,Yang Zhang	2019	14
17	Silicon Photomultipliers for Deep Tissue Cerenkov Emission Detection During External Beam Radiotherapy IEEE photonics journal ·Eugenio Facciolla,Leonor Vieira Sottomayor,Robin Pearce,ANTHONY JONES,Justin Mikell,C. A. Taylor,学妹尾,Stephen N. Strack,Alnawaz Rehemtulla,Roy Clarke,Issam El Naqa	2019	4
18	EvoEF2: accurate and fast energy function for computational protein design Bioinformatics ·Xiaoqiang Huang,Robin Pearce,Yang Zhang	2019	70
19	Detecting distant-homology protein structures by aligning deep neural-network based contact maps PLoS Computational Biology ·Wei Zheng,Qiqige Wuyun,Yang Li,S. M. Mortuza,Chengxin Zhang,Robin Pearce,Jishou Ruan,Yang Zhang	2019	36
20	EvoDesign: Designing Protein–Protein Binding Interactions Using Evolutionary Interface Profiles in Conjunction with an Optimized Physical Energy Function Journal of Molecular Biology ·Robin Pearce,Xiaoqiang Huang,Dani Setiawan,Yang Zhang	2019	53

About Robin Pearce

Robin Pearce is a scholar working on Structural Biology, Molecular Biology, Materials Chemistry, Infectious Diseases and Computational Theory and Mathematics, having authored 28 papers that have together received 1.8k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (19 papers), RNA and protein synthesis mechanisms (11 papers), Enzyme Structure and Function (11 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Genomics and Phylogenetic Studies (4 papers), Machine Learning in Bioinformatics (3 papers), Machine Learning in Materials Science (3 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Structural Biology (34 citations), Molecular Biology (1.3k citations), Microbiology (78 citations), Computational Theory and Mathematics (190 citations) and Infectious Diseases (212 citations). Robin Pearce has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Yang Zhang, Wei Zheng, Chengxin Zhang, Xiaoqiang Huang, Eric W. Bell, Yang Li, Yang Li, Xiaogen Zhou, Guijun Zhang and S. M. Mortuza. Their work appears in journals such as Bioinformatics, Nature Communications, Proteins Structure Function and Bioinformatics, PLoS Computational Biology and Journal of Molecular Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact