D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 37 Citations 7,065 96 World Ranking 4424 National Ranking 669

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Machine learning
  • Artificial intelligence

His main research concerns Statistics, Chemometrics, Data mining, Feature selection and Algorithm. His Statistics and Monte Carlo method, Cross-validation, Sampling and Partial least squares regression investigations all form part of his Statistics research activities. Chemometrics is a subfield of Chromatography that Qing-Song Xu tackles.

The concepts of his Data mining study are interwoven with issues in Robust regression, Quantitative structure–activity relationship, Small molecule and Cheminformatics. His biological study spans a wide range of topics, including Multivariate adaptive regression splines, Selection, Variables and Code. His research investigates the connection with Algorithm and areas like Calibration which intersect with concerns in Anomaly detection.

His most cited work include:

  • Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. (573 citations)
  • Monte Carlo cross validation (563 citations)
  • propy: a tool to generate various modes of Chou’s PseAAC (296 citations)

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

Qing-Song Xu focuses on Artificial intelligence, Feature selection, Data mining, Statistics and Partial least squares regression. His Artificial intelligence study incorporates themes from Machine learning and Pattern recognition. His Feature selection research includes themes of Selection and Regression.

His research in Data mining intersects with topics in Quantitative structure–activity relationship and Drug discovery. Statistics is represented through his Monte Carlo method, Cross-validation, Mean squared error, Linear regression and Sampling research. Qing-Song Xu works mostly in the field of Partial least squares regression, limiting it down to concerns involving Algorithm and, occasionally, Calibration, Model selection and Overfitting.

He most often published in these fields:

  • Artificial intelligence (28.77%)
  • Feature selection (23.29%)
  • Data mining (21.23%)

What were the highlights of his more recent work (between 2016-2021)?

  • Partial least squares regression (19.18%)
  • Feature selection (23.29%)
  • Statistics (21.92%)

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

The scientist’s investigation covers issues in Partial least squares regression, Feature selection, Statistics, Artificial intelligence and Pattern recognition. His Partial least squares regression research incorporates elements of Explained sum of squares, Covariate, Projection, Regression and Dimensionality reduction. His Feature selection research integrates issues from Data modeling, Selection, Sorting, Algorithm and Interpretability.

As part of his studies on Statistics, he often connects relevant areas like Random forest. His work in Random forest addresses issues such as High dimensional, which are connected to fields such as Data mining. His research on Artificial intelligence frequently links to adjacent areas such as Machine learning.

Between 2016 and 2021, his most popular works were:

  • Prediction of Radix Astragali Immunomodulatory Effect of CD80 Expression from Chromatograms by Quantitative Pattern-Activity Relationship (125 citations)
  • libPLS: An integrated library for partial least squares regression and linear discriminant analysis (109 citations)
  • A selective review and comparison for interval variable selection in spectroscopic modeling (27 citations)

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

  • Statistics
  • Machine learning
  • Artificial intelligence

His primary areas of study are Feature selection, Partial least squares regression, Algorithm, Projection and Artificial intelligence. Qing-Song Xu interconnects Total least squares, Iteratively reweighted least squares, Generalized least squares, Linear discriminant analysis and Robust regression in the investigation of issues within Partial least squares regression. His Algorithm research includes elements of Genetic algorithm and Overfitting.

His Projection research is multidisciplinary, incorporating elements of Calibration, Selection, Mathematical optimization, Interval and Dimensionality reduction. The study incorporates disciplines such as Data modeling, Homogeneity, Small number and Pattern recognition in addition to Artificial intelligence. His Pattern recognition study integrates concerns from other disciplines, such as Interpretability, Data mining, Explained sum of squares and Simple linear regression.

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

Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration.

Hongdong Li;Yizeng Liang;Qingsong Xu;Dongsheng Cao.
Analytica Chimica Acta (2009)

982 Citations

Monte Carlo cross validation

Qing-Song Xu;Yi-Zeng Liang.
Chemometrics and Intelligent Laboratory Systems (2001)

850 Citations

propy: a tool to generate various modes of Chou’s PseAAC

Dong-Sheng Cao;Qing-Song Xu;Yi-Zeng Liang.
Bioinformatics (2013)

442 Citations

Support vector machines and its applications in chemistry

Hongdong Li;Yizeng Liang;Qingsong Xu.
Chemometrics and Intelligent Laboratory Systems (2009)

356 Citations

Uniform design and its applications in chemistry and chemical engineering

Yi-zeng Liang;Kai-tai Fang;Qing-song Xu.
Chemometrics and Intelligent Laboratory Systems (2001)

307 Citations

Monte Carlo cross-validation for selecting a model and estimating the prediction error in multivariate calibration

Qing-Song Xu;Yi-Zeng Liang;Yi-Ping Du.
Journal of Chemometrics (2004)

244 Citations

Random frog: An efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification

Hong-Dong Li;Qing-Song Xu;Yi-Zeng Liang.
Analytica Chimica Acta (2012)

218 Citations

protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences

Nan Xiao;Dong-Sheng Cao;Min-Feng Zhu;Qing-Song Xu.
Bioinformatics (2015)

193 Citations

Prediction of Radix Astragali Immunomodulatory Effect of CD80 Expression from Chromatograms by Quantitative Pattern-Activity Relationship

Michelle Chun-har Ng;Tsui-yan Lau;Kei Fan;Qing-song Xu.
BioMed Research International (2017)

186 Citations

Determination of total antioxidant capacity in green tea by near-infrared spectroscopy and multivariate calibration.

M.H. Zhang;J. Luypaert;J.A. Fernández Pierna;Q.S. Xu.
Talanta (2004)

175 Citations

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