World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
11901
World Ranking
7803
National Ranking
3377

Overview

Roger Perkins is affiliated with the United States Food and Drug Administration in the United States. Their research work spans across psychology and social sciences with a particular focus on mental health and patient involvement, biomedical text mining, and social issues such as homelessness.

Their recent publications cover a range of interdisciplinary topics and include contributions to both methodological advances and applied social science research. Notable papers by Roger Perkins are:

  • 'Will there ever be a stage in anybody's life where they're not thinking about what I did?': exploring the expectations of people convicted of sexual offences, regarding their release from medium and long-term custodial sentences, 2025, Psychology Crime and Law
  • Text Fingerprinting and Topic Mining in the Prescription Opioid Use Literature, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  • "Don't think about a pink elephant": collaboratively exploring the notion of desistance using the CoNavigator participatory tool, 2025, Journal of Criminal Psychology
  • Text Fingerprinting and Topic Mining in the Prescription Opioid Use Literature, 2021, Research Square (Research Square)
  • Understanding Asthma Heritability: A Systematic Review and Meta-analysis of Genome-wide Association Study Findings Across Ancestries and Ethnicities, 2025, American Journal of Respiratory and Critical Care Medicine

The scientist's work is represented in several publication venues: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Journal of Criminal Psychology, Research Square, American Journal of Respiratory and Critical Care Medicine, and Psychology Crime and Law.

Roger Perkins frequently collaborates with several co-authors, including Huyen Le, Junxiu Zhou, Weizhong Zhao, Weigong Ge, and Beverly Lyn-Cook. These collaborations reflect interdisciplinary integration especially in fields involving biomedical data mining and social sciences.

Their research areas engage with the following main fields and subfields of study:

  • Psychology
  • Social Sciences
  • Social Psychology
  • General Health Professions
  • Sociology and Political Science
  • Molecular Biology
  • Artificial Intelligence

Key topics explored in their publications include:

  • Mental Health via Writing
  • Biomedical Text Mining and Ontologies
  • Topic Modeling
  • Mental Health and Patient Involvement
  • Homelessness and Social Issues
  • Qualitative Research Methods and Ethics
  • Opioid Use Disorder Treatment

Best Publications

  • The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    Leming Shi;Laura H. Reid;Wendell D. Jones;Richard Shippy

  • The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

    Leming Shi;Gregory Campbell;Wendell D. Jones;Fabien Campagne

  • A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

    Zhenqiang Su;Paweł P. Łabaj;Sheng Li;Jean Thierry-Mieg

  • Structure-activity relationships for a large diverse set of natural, synthetic, and environmental estrogens.

    Hong Fang;Weida Tong;Leming M. Shi;Robert Blair

  • QSAR models using a large diverse set of estrogens

    Leming M. Shi;Hong Fang;Weida Tong;Jie Wu

  • A heuristic approach to determine an appropriate number of topics in topic modeling

    Weizhong Zhao;Weizhong Zhao;James J Chen;Roger Perkins;Zhichao Liu

  • The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

    Leming Shi;Wendell D. Jones;Roderick V. Jensen;Stephen C. Harris

  • Mold2, Molecular Descriptors from 2D Structures for Chemoinformatics and Toxicoinformatics

    Huixiao Hong;Qian Xie;Weigong Ge;Feng Qian

  • Quantitative comparisons of in vitro assays for estrogenic activities.

    Hong Fang;Weida Tong;Roger Perkins;Ana M. Soto

  • ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.

    Weida Tong;Xiaoxi Cao;Stephen Harris;Hongmei Sun

  • Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models

    Weida Tong;Huixiao Hong;Hong Fang;Qian Xie

  • Evaluation of Quantitative Structure−Activity Relationship Methods for Large-Scale Prediction of Chemicals Binding to the Estrogen Receptor†

    Weida Tong;David R. Lowis;Roger Perkins;Yu Chen

  • Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.

    Leming Shi;Weida Tong;Hong Fang;Uwe Scherf

  • Next-generation sequencing and its applications in molecular diagnostics

    Zhenqiang Su;Baitang Ning;Hong Fang;Huixiao Hong

  • An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    Zhenqiang Su;Zhenqiang Su;Hong Fang;Huixiao Hong;Leming Shi

  • Reproducible and reliable microarray results through quality control: good laboratory proficiency and appropriate data analysis practices are essential

    Leming Shi;Roger G Perkins;Hong Fang;Weida Tong

  • Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts.

    Huixiao Hong;Weida Tong;Hong Fang;Leming Shi

  • Assessment of Prediction Confidence and Domain Extrapolation of Two Structure–Activity Relationship Models for Predicting Estrogen Receptor Binding Activity

    Weida Tong;Qian Xie;Huixiao Hong;Leming Shi

  • Development of public toxicogenomics software for microarray data management and analysis.

    Weida Tong;Stephen Harris;Xiaoxi Cao;Hong Fang

  • Microarray scanner calibration curves: characteristics and implications

    Leming Shi;Weida Tong;Zhenqiang Su;Tao Han

  • Next-Generation Sequencing (NGS): A Revolutionary Technology in Pharmacogenomics and Personalized Medicine

    Huixiao Hong;Wenqian Zhang;Zhenqiang Su;Jie Shen

Frequent Co-Authors

Weida Tong
Weida Tong National Center for Toxicological Research
Hong Fang
Hong Fang National Center for Toxicological Research
Huixiao Hong
Huixiao Hong United States Food and Drug Administration
Leming Shi
Leming Shi Fudan University
Lei Guo
Lei Guo National Center for Toxicological Research
Raj K. Puri
Raj K. Puri US Food and Drug Administration
Quan Zhen Li
Quan Zhen Li The University of Texas Southwestern Medical Center
James C. Willey
James C. Willey University of Toledo
Feng Qian
Feng Qian Fudan University
Cesare Furlanello
Cesare Furlanello Fondazione Bruno Kessler

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