H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Biology and Biochemistry D-index 44 Citations 6,379 185 World Ranking 13595 National Ranking 392

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Enzyme
  • Amino acid

His scientific interests lie mostly in Peptide sequence, Sequence analysis, Computational biology, Biochemistry and Protein sequencing. His Peptide sequence study incorporates themes from Proteases, Cysteine and Matthews correlation coefficient. His work deals with themes such as RNA splicing, Proteome, Autoimmunity and Data mining, which intersect with Computational biology.

The Protein sequencing study combines topics in areas such as Protein structure and Conserved sequence. He has included themes like Biological system, Support vector machine, Protein secondary structure and Protein folding in his Protein structure study. In Support vector machine, Jiangning Song works on issues like Feature selection, which are connected to Feature vector.

His most cited work include:

  • PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites (187 citations)
  • PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites (187 citations)
  • iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences. (172 citations)

What are the main themes of his work throughout his whole career to date?

Jiangning Song spends much of his time researching Computational biology, Artificial intelligence, Biochemistry, Protein structure and Bioinformatics. His research integrates issues of Sequence analysis, Proteome, Protein sequencing and Support vector machine in his study of Computational biology. His studies in Support vector machine integrate themes in fields like Genetics, Binding site, Ensemble forecasting and Encoding.

His work focuses on many connections between Artificial intelligence and other disciplines, such as Machine learning, that overlap with his field of interest in Identification. His Protein structure study integrates concerns from other disciplines, such as Protease, Target protein, Biological system and Protein secondary structure. He combines subjects such as Proteases, Cleavage, In silico and Protein folding with his study of Peptide sequence.

He most often published in these fields:

  • Computational biology (39.70%)
  • Artificial intelligence (25.84%)
  • Biochemistry (28.09%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (25.84%)
  • Machine learning (15.73%)
  • Computational biology (39.70%)

In recent papers he was focusing on the following fields of study:

His main research concerns Artificial intelligence, Machine learning, Computational biology, Deep learning and Feature. His Artificial intelligence study frequently draws connections to other fields, such as Identification. In the subject of general Machine learning, his work in Support vector machine, Feature engineering, Ensemble learning and Dimensionality reduction is often linked to Set, thereby combining diverse domains of study.

His study in Computational biology is interdisciplinary in nature, drawing from both Cleavage, Function, Pathogenic organism, Human leukocyte antigen and Sequence analysis. His work in Feature selection addresses issues such as Naive Bayes classifier, which are connected to fields such as Random forest. Jiangning Song works mostly in the field of Protein secondary structure, limiting it down to topics relating to Intrinsically disordered proteins and, in certain cases, Biological system, as a part of the same area of interest.

Between 2019 and 2021, his most popular works were:

  • iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data (83 citations)
  • A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction (42 citations)
  • DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites (35 citations)

In his most recent research, the most cited papers focused on:

  • Gene
  • Enzyme
  • Amino acid

His primary scientific interests are in Computational biology, Artificial intelligence, Feature selection, Machine learning and Feature. His Computational biology study combines topics in areas such as Cleave, Cleavage, Proteases, Proteolysis and Sequence analysis. The concepts of his Cleave study are interwoven with issues in Proteome, Protein secondary structure, Protease, Peptide bond and Protein structure.

His Feature selection research includes themes of Model interpretation and Regulation of gene expression. Within one scientific family, he focuses on topics pertaining to Encoding under Machine learning, and may sometimes address concerns connected to Artificial neural network, Robustness, Naive Bayes classifier, Support vector machine and Random forest. His studies deal with areas such as Representation, Scale and Identification as well as Feature.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites

Jiangning Song;Jiangning Song;Hao Tan;Andrew J. Perry;Tatsuya Akutsu.
PLOS ONE (2012)

230 Citations

iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences.

Zhen Chen;Pei Zhao;Fuyi Li;André Leier.
Bioinformatics (2018)

210 Citations

APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility

Jun-Feng Xia;Jun-Feng Xia;Xing-Ming Zhao;Jiangning Song;Jiangning Song;De-Shuang Huang.
BMC Bioinformatics (2010)

191 Citations

iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites

Jiangning Song;Yanan Wang;Fuyi Li;Tatsuya Akutsu.
Briefings in Bioinformatics (2019)

159 Citations

Cascleave: towards more accurate prediction of caspase substrate cleavage sites.

Jiangning Song;Hao Tan;Hongbin Shen;Khalid Mahmood.
Bioinformatics (2010)

158 Citations

Computational enzyme design approaches with significant biological outcomes: progress and challenges

Xiaoman Li;Ziding Zhang;Jiangning Song;Jiangning Song.
Computational and structural biotechnology journal (2012)

142 Citations

ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides.

Leyi Wei;Chen Zhou;Huangrong Chen;Jiangning Song.
Bioinformatics (2018)

138 Citations

Prediction of protein folding rates from primary sequence by fusing multiple sequential features

Hong-Bin Shen;Jiang-Ning Song;Kuo-Chen Chou.
Journal of Biomedical Science and Engineering (2009)

137 Citations

Production of octenyl succinic anhydride-modified waxy corn starch and its characterization.

Zhiqiang Liu;Yin Li;Fengjie Cui;Lifeng Ping.
Journal of Agricultural and Food Chemistry (2008)

122 Citations

GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome

Fuyi Li;Chen Li;Mingjun Wang;Geoffrey I. Webb.
Bioinformatics (2015)

119 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Jiangning Song

Kuo-Chen Chou

Kuo-Chen Chou

The Gordon Life Science Institute

Publications: 46

Quan Zou

Quan Zou

University of Electronic Science and Technology of China

Publications: 43

Wei Chen

Wei Chen

North China University of Science and Technology

Publications: 39

Lukasz Kurgan

Lukasz Kurgan

Virginia Commonwealth University

Publications: 36

Hao Lin

Hao Lin

University of Electronic Science and Technology of China

Publications: 29

Hong-Bin Shen

Hong-Bin Shen

Shanghai Jiao Tong University

Publications: 25

Zhu-Hong You

Zhu-Hong You

Chinese Academy of Sciences

Publications: 20

Bin Liu

Bin Liu

Nanjing University

Publications: 18

Leyi Wei

Leyi Wei

Shandong University

Publications: 16

Yaoqi Zhou

Yaoqi Zhou

Griffith University

Publications: 15

Charles N. Serhan

Charles N. Serhan

Harvard University

Publications: 14

Muhammad Nawaz Tahir

Muhammad Nawaz Tahir

Johannes Gutenberg University of Mainz

Publications: 14

Yu-Dong Cai

Yu-Dong Cai

Shanghai University

Publications: 14

Alok Sharma

Alok Sharma

Griffith University

Publications: 13

Jinyan Li

Jinyan Li

University of Technology Sydney

Publications: 12

De-Shuang Huang

De-Shuang Huang

Tongji University

Publications: 12

Something went wrong. Please try again later.