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Biology and Biochemistry
China
2023

D-Index & Metrics

Biology and Biochemistry

D-Index
84
Citations
21377
World Ranking
3384
National Ranking
94

Research.com Recognitions

  • 2023 - Research.com Biology and Biochemistry in China Leader Award

Overview

Hao Lin is affiliated with the University of Electronic Science and Technology of China. Their research spans extensive work within the fields of Biochemistry, Genetics, and Molecular Biology, with a particular focus on Molecular Biology as the primary subfield. Additional subfields of study include Cancer Research, Materials Chemistry, Computational Theory and Mathematics, and Surgery.

The scientist's research topics cover several specialized areas related to bioinformatics and molecular biology. These topics include:

  • Machine Learning in Bioinformatics
  • Genomics and Phylogenetic Studies
  • RNA and protein synthesis mechanisms
  • Cancer-related molecular mechanisms research
  • RNA modifications and cancer
  • Computational Drug Discovery Methods
  • Genomics and Chromatin Dynamics

Hao Lin has contributed multiple significant publications, some of which have garnered notable citations. Recent papers include:

  • "Attention is all you need: utilizing attention in AI-enabled drug discovery," 2023, published in Briefings in Bioinformatics
  • "Tumor cell plasticity in targeted therapy-induced resistance: mechanisms and new strategies," 2023, published in Signal Transduction and Targeted Therapy
  • "DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism," 2021, published in Nucleic Acids Research
  • "Design powerful predictor for mRNA subcellular location prediction in Homo sapiens," 2020, published in Briefings in Bioinformatics
  • "Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method," 2020, published in Briefings in Bioinformatics

The scientist frequently publishes in journals such as Briefings in Bioinformatics, International Journal of Molecular Sciences, arXiv (Cornell University), Computational and Structural Biotechnology Journal, and International Journal of Biological Macromolecules.

Collaboration emerges as a key aspect of Hao Lin's career, working often with coauthors such as Hao Lv, Fanny Dao, Kejun Deng, Hasan Zulfiqar, and Yuhe R. Yang.

Best Publications

  • iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition

    Wei Chen;Peng-Mian Feng;Hao Lin;Kuo-Chen Chou

  • iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.

    Hao Lin;En-Ze Deng;Hui Ding;Wei Chen

  • PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition.

    Wei Chen;Tian-Yu Lei;Dian-Chuan Jin;Hao Lin

  • iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition

    Shou-Hui Guo;En-Ze Deng;Li-Qin Xu;Hui Ding

  • iACP: a sequence-based tool for identifying anticancer peptides

    Wei Chen;Hui Ding;Pengmian Feng;Hao Lin

  • iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition.

    Wei Chen;Pengmian Feng;Hui Ding;Hao Lin

  • The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition

    Hao Lin

  • Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences

    Wei Chen;Hao Lin;Hao Lin;Kuo-Chen Chou

  • iRNA-PseU: Identifying RNA pseudouridine sites

    Wei Chen;Hua Tang;Jing Ye;Hao Lin

  • iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC.

    Zhen-Dong Su;Yan Huang;Zhao-Yue Zhang;Ya-Wei Zhao

  • iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC.

    Pengmian Feng;Hui Yang;Hui Ding;Hao Lin

  • iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition

    Peng-Mian Feng;Wei Chen;Hao Lin;Kuo-Chen Chou

  • iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.

    Pengmian Feng;Hui Ding;Hui Yang;Wei Chen

  • iTIS-PseTNC: a sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition.

    Wei Chen;Peng-Mian Feng;En-Ze Deng;Hao Lin

  • Embedding Temporal Network via Neighborhood Formation

    Yuan Zuo;Guannan Liu;Hao Lin;Jia Guo

  • iDNA4mC: identifying DNA N4-methylcytosine sites based on nucleotide chemical properties.

    Wei Chen;Hui Yang;Pengmian Feng;Hui Ding

  • Predicting Subcellular Localization of Mycobacterial Proteins by Using Chous Pseudo Amino Acid Composition

    Hao Lin;Hui Ding;Feng-Biao Guo;An-Ying Zhang

  • iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels.

    Hui Ding;En-Ze Deng;Lu-Feng Yuan;Li Liu

  • PseKNC-General: A cross-platform package for generating various modes of pseudo nucleotide compositions

    Wei Chen;Xitong Zhang;Jordan Brooker;Hao Lin

  • iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition

    Wei Chen;Peng-Mian Feng;Hao Lin;Kuo-Chen Chou

Frequent Co-Authors

Wei Chen
Wei Chen Chengdu University of Traditional Chinese Medicine
Hui Ding
Hui Ding University of Electronic Science and Technology of China
Kuo-Chen Chou
Kuo-Chen Chou The Gordon Life Science Institute
Junjie Wu
Junjie Wu Beihang University
Leopoldo G. Franquelo
Leopoldo G. Franquelo University of Seville
Ligang Wu
Ligang Wu Harbin Institute of Technology
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Jose I. Leon
Jose I. Leon University of Seville
Dong Xu
Dong Xu University of Missouri
Andrew H. Paterson
Andrew H. Paterson University of Georgia

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