Assist Prof Dr. Chen Huang | Bioinformatics | Best Researcher Award

Assist Prof Dr. Chen Huang | Bioinformatics | Best Researcher Award

Assist Prof Dr. Chen Huang, Macau University of Science and Technology, Macau

Assist. Prof. Dr. Chen Huang is a distinguished researcher in the field of bioinformatics, known for his groundbreaking work in computational biology and data analysis. He currently serves as an Assistant Professor at a leading university, where he combines his expertise in computer science and molecular biology to advance research in genomics and personalized medicine. Dr. Huang has been recognized for his innovative approaches to solving complex biological problems, earning him the prestigious Best Researcher Award. His contributions have significantly impacted the understanding of genetic data and the development of novel bioinformatics tools, making him a leader in his field

Publication profile

Academic Qualification

Assist. Prof. Dr. Chen Huang holds a Ph.D. in Biomedical Sciences with a specialization in Bioinformatics from the Institute of Chinese Medical Sciences at the University of Macau, China (2012-2017). He also earned an M.E. in Bioinformatics from the Biological Information Science and Technology Institute at Harbin Medical University, China (2007-2010). Dr. Huang began his academic journey with a B.S. in Biotechnology, focusing on Biopharmaceuticals, from the College of Life Science at Nanchang University, China (2003-2007). His diverse educational background has laid a strong foundation for his pioneering research in bioinformatics.

Working Experiances

Assist. Prof. Dr. Chen Huang is currently serving as an Assistant Professor at the State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macao, a position he has held since 2020. Prior to this role, he completed a post-doctoral fellowship at the Faculty of Health Sciences, University of Macau, Macao, from 2017 to 2020. Before his post-doctoral tenure, Dr. Huang worked as an Analyst at the Beijing Genomics Institute in Shenzhen (BGI-Shenzhen) from 2010 to 2012.

Publication Top Notes

Lu, C., Huang, C., Qu, S., Lin, H., Zhong, H.-J., & Chong, C.-M. (2024). Oxyimperatorin attenuates LPS-induced microglial activation in vitro and in vivo via suppressing NF-ĪŗB p65 signaling. Biomedicine & Pharmacotherapy. https://doi.org/10.1016/j.biopha.2024.116379

Yang, X., Wu, Y., Chen, X., Qiu, J., & Huang, C. (2024). The transcriptional landscape of immune-response 3ā€²-UTR alternative polyadenylation in melanoma. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms25053041

Zhang, Y.-Z., Lai, H.-L., Huang, C., Jiang, Z.-B., Yan, H.-X., Wang, X.-R., Xie, C., Huang, J.-M., Ren, W.-K., Li, J.-X., Zhai, Z.-R., Yao, X.-J., Wu, Q.-B., & Leung, E. L.-H. (2024). Tanshinone IIA induces ER stress and JNK activation to inhibit tumor growth and enhance anti-PD-1 immunotherapy in non-small cell lung cancer. Phytomedicine. https://doi.org/10.1016/j.phymed.2024.155431

Cheng, X., Deng, M., Wang, Z., & Huang, C. (2024). MMP3C: An in-silico framework to depict cancer metabolic plasticity using gene expression profiles. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbad471

Wang, Z., Chen, X., Si, W., & Huang, C. (2023). Systemic pharmacology and bioinformatics: Exploring the modern biological mechanisms of rhubarb in the treatment of papillary thyroid carcinoma. MedComm – Future Medicine. https://doi.org/10.1002/mef2.69

Huang, C., Deng, M., Leng, D., Sun, B., Zheng, P., & Zhang, X. D. (2023). MIRS: An AI scoring system for predicting the prognosis and therapy of breast cancer. iScience. https://doi.org/10.1016/j.isci.2023.108322

Feng, Y., Chen, X., Zhang, X. D., & Huang, C. (2023). Metabolic pathway pairwise-based signature as a potential non-invasive diagnostic marker in Alzheimerā€™s disease patients. Genes. https://doi.org/10.3390/genes14061285

Cheng, T., Wu, Y., Liu, Z., Yu, Y., Sun, S., Guo, M., Sun, B., & Huang, C. (2022). CDKN2A-mediated molecular subtypes characterize the hallmarks of tumor microenvironment and guide precision medicine in triple-negative breast cancer. Frontiers in Immunology. https://doi.org/10.3389/fimmu.2022.970950

Wu, L., Hou, X., Luo, W., Hu, H., Zheng, X., Chen, Y., Cheng, Z., Huang, C., & Sun, B. (2022). Three patterns of sensitization to mugwort, timothy, birch, and their major allergen components revealed by latent class analysis. Molecular Immunology. https://doi.org/10.1016/j.molimm.2022.03.009

Cheng, T., Chen, P., Chen, J., Deng, Y., & Huang, C. (2022). Landscape analysis of matrix metalloproteinases unveils key prognostic markers for patients with breast cancer. Frontiers in Genetics. https://doi.org/10.3389/fgene.2021.809600

Siddiq Ur Rahman | Bioinformatics | Best Paper Award

Assist Prof Dr. Siddiq Ur Rahman | Bioinformatics | Best Paper Award

Assist Prof Dr. Siddiq Ur Rahman, Khushal Khan Khattak University, Karak, Pakistan

Assist. Prof. Dr. Siddiq Ur Rahman is a driven and dedicated academic specializing in bioinformatics. He earned his Ph.D. in Bioinformatics (2015-2018) and M.Sc. (Hons) in Biochemistry and Molecular Biology (2013-2015) from Northwest A&F University, China, excelling with top grades. Dr. Rahman also holds a B.S. (Hons) in Biotechnology from the University of Malakand, Pakistan. Fluent in Chinese, he completed a Chinese Language Course and the HSK language test. Known for his ambition and teamwork, he thrives in challenging environments, aiming to excel and contribute significantly to his field. šŸŒ±šŸ“ŠšŸ‘Øā€šŸŽ“

Publication profile

Scopus

Google Scholar

Education

Ph.D. (Bioinformatics): Northwest A&F University China (2015-2018), 81%, A1 grade

M.Sc. (Hons) (Biochemistry and Molecular Biology): Northwest A&F University China (2013-2015), 82%, A1 grade

Chinese Language Course: Northwest A&F University China (2012-2013), 80%, A1 grade

B.S. (Hons) (Biotechnology): University of Malakand, Pakistan (2007-2011), 74%, A grade

Intermediate (Pre-Medical): Govt: Post Graduate Jahanzeb College Swat / BISE Swat (2004-2007), 75%, A grade

Matric: Malakand Public School Dargai / BISE Malakand (2003-2004), 72%, A grade

HSK (Chinese Language Test): Beijing Language Center (2013), 70%, A grade

Research Focus

Dr. SU Rahman’s research encompasses multiple fields, including environmental botany, plant physiology, virology, and microbial biotechnology. His work on drought stress and nutrient management in Catalpa bungei and Populus species explores plant responses to environmental stressors šŸŒ±. Additionally, Dr. Rahman investigates codon usage bias and evolutionary patterns in viruses like Crimean-Congo hemorrhagic fever and Zika virus šŸ¦ . He also examines microbial degradation of lignocellulosic biomass for biotechnological applications šŸŒ¾. His diverse research portfolio highlights the intersection of plant science, environmental sustainability, and molecular biology, contributing valuable insights into plant adaptation, pathogen evolution, and microbial ecology. šŸ§¬

 

Publication Top Notes

 

  • Morphological and physiological responses to cyclic drought in two contrasting genotypes of Catalpa bungei šŸŒ± (64, 2017)
  • Physiological and transcriptional responses of Catalpa bungei to drought stress under sufficient- and deficient-nitrogen conditions šŸŒ³ (58, 2017)
  • Phosphorus influence Cd phytoextraction in Populus stems via modulating xylem development, cell wall Cd storage and antioxidant defense šŸŒæ (44, 2020)
  • Analysis of codon usage bias of Crimean-Congo hemorrhagic fever virus and its adaptation to hosts šŸ¦  (38, 2018)
  • Phytoextraction of Pb and Cd; the effect of Urea and EDTA on Cannabis sativa growth under metals stress šŸŒ¾ (28, 2014)
  • Codon usage bias analysis of bluetongue virus causing livestock infection šŸ„ (27, 2020)
  • Influence of nitrogen availability on Cd accumulation and acclimation strategy of Populus leaves under Cd exposure šŸƒ (27, 2019)
  • Polymorphism in promoter of SIX4 gene shows association with its transcription and body measurement traits in Qinchuan cattle šŸ‚ (27, 2018)
  • A Novel Strategy for Detecting Recent Horizontal Gene Transfer and Its Application to Rhizobium Strains šŸ§¬ (20, 2018)
  • Microbial degradation of lignocellulosic biomass: discovery of novel natural lignocellulolytic bacteria šŸ”¬ (20, 2018)