Renzhi Cao

Molecular Biology · 2015–2019

A researcher in the Science corpus: 8 papers; trusts 48 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 136 citations into it; #1,489 of 17,773 by trust here, #5,968 by citations
• Materials Chemistry — 81 citations into it; #1,244 of 11,513 by trust here, #6,473 by citations
• Computational Biology & Bioinformatics — 61 citations into it
• Spectroscopy — 19 citations into it
• Computational Theory and Mathematics — 10 citations into it; #6,594 of 12,182 by trust here, #5,724 by citations
• Evaluation & Benchmarks — 7 citations into it

Whom Renzhi Cao trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yang Zhang
2. Jianlin Cheng
3. Liam J. McGuffin
4. Jeffrey Skolnick
5. Dong Xu
6. Björn Wallner
7. W. Kabsch
8. David C. Jones
9. Arlo Z. Randall
10. K. Simons

Who trusts Renzhi Cao overall

1. Jianlin Cheng
2. Jie Hou
3. Debswapna Bhattacharya
4. Bowen Jing
5. Karolis Uziela
6. Mikhail Karasikov
7. Riviera Maya
8. Sankar Basu
9. Badri Adhikari
10. Björn Wallner

Papers from Renzhi Cao's perspective

Ordered by how strongly the researchers Renzhi Cao trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
2. The Protein Data Bank.
3. Protein secondary structure prediction based on position-specific scoring matrices.
4. Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions.
5. A method to identify protein sequences that fold into a known three-dimensional structure.
6. Basic local alignment search tool.
7. Protein data bank
8. Hidden Markov models for detecting remote protein homologies
9. Scoring function for automated assessment of protein structure template quality
10. Scoring function for automated assessment of protein structure template quality

Their papers

• CONFOLD: Residue-Residue Contact-guided ab initio Protein Folding (2015) — 147 citations
• Large-scale model quality assessment for improving protein tertiary structure prediction (2015) — 69 citations
• Protein single-model quality assessment by feature-based probability density functions (2016) — 77 citations
• UniCon3D: de novo protein structure prediction using united-residue conformational search via stepwise, probabilistic sampling (2016) — 44 citations
• Integrated protein function prediction by mining function associations, sequences, and protein–protein and gene–gene interaction networks (2015) — 82 citations
• 3Drefine: an interactive web server for efficient protein structure refinement (2016) — 377 citations
• The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations
• Deep convolutional neural networks for predicting the quality of single protein structural models (2019) — 19 citations