World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9547
World Ranking
4392
National Ranking
20

Overview

Xin Gao is affiliated with King Abdullah University of Science and Technology in Saudi Arabia. Their research primarily focuses on the field of Biochemistry, Genetics, and Molecular Biology, with a significant emphasis on Molecular Biology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cancer Research, and Computer Vision and Pattern Recognition.

The scientist's work spans multiple main topics including RNA and protein synthesis mechanisms, Genomics and Phylogenetic Studies, Radiomics and Machine Learning in Medical Imaging, Computational Drug Discovery Methods, RNA modifications and cancer, Topic Modeling, and Bioinformatics and Genomic Networks.

Xin Gao has contributed to a number of recent papers, including:

  • Opportunities and challenges for ChatGPT and large language models in biomedicine and health (2023), Briefings in Bioinformatics
  • Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024 (2023), Nucleic Acids Research
  • Towards artificial general intelligence via a multimodal foundation model (2022), Nature Communications
  • A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis (2020), IEEE Transactions on Medical Imaging
  • A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics (2023), Nature Communications

Frequent co-authors collaborating with Xin Gao include:

  • Juexiao Zhou
  • Takashi Gojobori
  • Haoyang Li
  • Bin Zhang
  • Xiaopeng Xu

Xin Gao has published extensively in certain venues, with the most publications in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Communications
  • SSRN Electronic Journal
  • Briefings in Bioinformatics

In addition to journal articles, Xin Gao has contributed to book publications, including the title Analysing Religious Discourse (2021) published by Cambridge University Press.

Best Publications

  • Deep learning in bioinformatics: Introduction, application, and perspective in the big data era.

    Yu Li;Chao Huang;Lizhong Ding;Zhongxiao Li

  • DEEPre: sequence-based enzyme EC number prediction by deep learning

    Yu Li;Sheng Wang;Ramzan Umarov;Bingqing Xie

  • Bioinformatics clouds for big data manipulation.

    Lin Dai;Xin Gao;Yan Guo;Jingfa Xiao

  • A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis

    Longxi Zhou;Zhongxiao Li;Juexiao Zhou;Haoyang Li

  • Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

    Abdul-Hamid M. Emwas;Raja Roy;Ryan T. McKay;Danielle Ryan

  • Machine learning and deep learning methods that use omics data for metastasis prediction

    Somayah Albaradei;Somayah Albaradei;Maha A. Thafar;Maha A. Thafar;Asim Alsaedi;Asim Alsaedi;Christophe Marc Van Neste

  • Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine.

    Abdul-Hamid M. Emwas;Edoardo Saccenti;Xin Gao;Ryan T. McKay

  • Non-negative matrix factorization by maximizing correntropy for cancer clustering

    Jim Jing-Yan Wang;Xiaolei Wang;Xin Gao

  • Semantic similarity and machine learning with ontologies

    Maxat Kulmanov;Fatima Zohra Smaili;Xin Gao;Robert Hoehndorf

  • OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction.

    Fatima Zohra Smaili;Xin Gao;Robert Hoehndorf

  • Multiple graph regularized nonnegative matrix factorization

    Jim Jing-Yan Wang;Halima Bensmail;Xin Gao

  • Learning from Weak and Noisy Labels for Semantic Segmentation

    Zhiwu Lu;Zhenyong Fu;Tao Xiang;Peng Han

  • DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques

    Maha A. Thafar;Maha A. Thafar;Rawan S. Olayan;Haitham Ashoor;Somayah Albaradei;Somayah Albaradei

  • Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations.

    Fatima Zohra Smaili;Xin Gao;Robert Hoehndorf

  • GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization

    Peng Han;Peng Yang;Peilin Zhao;Shuo Shang

  • Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence

    Yu-An Huang;Zhu-Hong You;Xin Gao;Leon Wong

  • mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning.

    Zhenzhen Zou;Shuye Tian;Xin Gao;Yu Li

  • Computer-aided drug repurposing for cancer therapy: Approaches and opportunities to challenge anticancer targets

    Carla Mottini;Francesco Napolitano;Zhongxiao Li;Xin Gao

  • A deep learning framework to predict binding preference of RNA constituents on protein surface

    Jordy Homing Lam;Jordy Homing Lam;Yu Li;Lizhe Zhu;Lizhe Zhu;Ramzan Umarov

  • DeepSimulator: a deep simulator for Nanopore sequencing.

    Yu Li;Renmin Han;Chongwei Bi;Mo Li

  • Promoter analysis and prediction in the human genome using sequence-based deep learning models.

    Ramzan Umarov;Hiroyuki Kuwahara;Yu Li;Xin Gao

  • Notice of Violation of IEEE Publication Principles Bag-of-Features Based Medical Image Retrieval via Multiple Assignment and Visual Words Weighting

    Jingyan Wang;Yongping Li;Ying Zhang;Chao Wang

  • Multimodal Machine Learning for Automated ICD Coding

    Keyang Xu;Mike Lam;Jingzhi Pang;Xin Gao

Frequent Co-Authors

Takashi Gojobori
Takashi Gojobori King Abdullah University of Science and Technology
Vladimir B. Bajic
Vladimir B. Bajic King Abdullah University of Science and Technology
Robert Hoehndorf
Robert Hoehndorf King Abdullah University of Science and Technology
Stefan T. Arold
Stefan T. Arold King Abdullah University of Science and Technology
Ivan Mijakovic
Ivan Mijakovic Chalmers University of Technology
Jinbo Xu
Jinbo Xu Toyota Technological Institute at Chicago
Ying Xu
Ying Xu University of Georgia
Peilin Zhao
Peilin Zhao Tencent (China)
Le Song
Le Song Mohamed bin Zayed University of Artificial Intelligence
Xiangliang Zhang
Xiangliang Zhang University of Notre Dame

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

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

As the demand for technology and STEM professionals grows, many students consider online study options that offer flexibility and affordability. Pursuing an online computer science degree is a popular choice, opening doors to careers in software development, AI, cybersecurity, and more.

Engineering pathways are also available online. For instance, earning an environmental engineer degree online can prepare you for roles tackling sustainability and environmental challenges. Students looking for budget-friendly options might consider the cheapest mechanical engineering degree online, which offers skills needed in industries like automotive, aerospace, and manufacturing.

If you have a passion for science, several accredited programs allow you to study online physics degrees. These pathways can lead to jobs in research labs, technology development, or education. Exploring these online degree options can help you find a program that matches your interests and supports your long-term career goals in STEM fields.

Best Scientists Citing Xin Gao

Trending Scientists