Demo Data from VLDB 2026 / reviewers in the wild / expert
Jie Zhang 0035
dblp:84/6889-35
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Bioinformatics and computational biology · 75% Computational science and engineering · 25% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
structural biology |
0.1 | 1 | 2012 | DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol · Bioinform. 2012 |
Bioinformatics and computational biology › statistical genetics
variant effect prediction |
0.1 | 1 | 2012 | Predicting folding free energy changes upon single point mutations · Bioinform. 2012 |
Computational science and engineering › scientific software
web server |
0.1 | 1 | 2012 | DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol · Bioinform. 2012 |
High-performance computing
scientific computing systems |
0.0 | 1 | 2012 | DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
poisson-boltzmann electrostatics · 0.3jmol visualization · 0.3molecular mechanics generalized born · 0.1in silico mutagenesis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocolabstractUNLABELLED: A new edition of the DelPhi web server, DelPhi web server v2, is released to include atomic presentation of geometrical figures. These geometrical objects can be used to model nano-size objects together with real biological macromolecules. The position and size of the object can be manipulated by the user in real time until desired results are achieved. The server fixes structural defects, adds hydrogen atoms and calculates electrostatic energies and the corresponding electrostatic potential and ionic distributions. AVAILABILITY AND IMPLEMENTATION: The web server follows a client-server architecture built on PHP and HTML and utilizes DelPhi software. The computation is carried out on supercomputer cluster and results are given back to the user via http protocol, including the ability to visualize the structure and corresponding electrostatic potential via Jmol implementation. The DelPhi web server is available from http://compbio.clemson.edu/delphi_webserver. Shawn Witham, Subhra Sarkar, Jie Zhang 0035, Lin Li 0003, Chuan Li 0003, Emil Alexov |
Bioinform. | 4 |
| 2012 | Predicting folding free energy changes upon single point mutationsabstractMOTIVATION: The folding free energy is an important characteristic of proteins stability and is directly related to protein's wild-type function. The changes of protein's stability due to naturally occurring mutations, missense mutations, are typically causing diseases. Single point mutations made in vitro are frequently used to assess the contribution of given amino acid to the stability of the protein. In both cases, it is desirable to predict the change of the folding free energy upon single point mutations in order to either provide insights of the molecular mechanism of the change or to design new experimental studies. RESULTS: We report an approach that predicts the free energy change upon single point mutation by utilizing the 3D structure of the wild-type protein. It is based on variation of the molecular mechanics Generalized Born (MMGB) method, scaled with optimized parameters (sMMGB) and utilizing specific model of unfolded state. The corresponding mutations are built in silico and the predictions are tested against large dataset of 1109 mutations with experimentally measured changes of the folding free energy. Benchmarking resulted in root mean square deviation = 1.78 kcal/mol and slope of the linear regression fit between the experimental data and the calculations was 1.04. The sMMGB is compared with other leading methods of predicting folding free energy changes upon single mutations and results discussed with respect to various parameters. AVAILABILITY: All the pdb files we used in this article can be downloaded from http://compbio.clemson.edu/downloadDir/mentaldisorders/sMMGB_pdb.rar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Jie Zhang 0035, Maxim Zhenirovskyy, Emil Alexov |
Bioinform. | 4 |