Zhichao Miao | Bioinformatics | Best Researcher Award

Published on by Academic Achievements

Prof. Zhichao Miao | Bioinformatics | Best Researcher Award

Prof. Zhichao Miao | Bioinformatics | Principal Investigator at Guangzhou Medical University | China

Prof. Zhichao Miao is a distinguished Principal Investigator and computational biologist whose expertise bridges bioinformatics, single-cell genomics, and RNA structural biology. He earned his Ph.D. in Bioinformatics from the Institute of Biophysics, Chinese Academy of Sciences, and his Bachelor’s degree in Bioengineering from the Harbin Institute of Technology, laying a strong foundation in computational and molecular biology. Professionally, Prof. Miao has held esteemed research appointments at world-class institutions such as the European Bioinformatics Institute (EMBL-EBI) and the Wellcome Trust Sanger Institute in the United Kingdom, where he contributed to pioneering genomic data integration projects. Currently serving as Principal Investigator at Guangzhou National Laboratory and Adjunct Professor at Guangzhou Medical University, he leads innovative programs in AI-driven multi-omics, digital twin cell technology, and RNA informatics. His research interests center on computational modeling of gene expression, cross-species cell type mapping, and algorithmic optimization for biological data analysis. With a remarkable publication record of over 68 SCI-indexed papers, an H-index of 32, and more than 8,000 citations, his work has appeared in high-impact journals including Nature Medicine, Nature Methods, Nature Communications, and Nucleic Acids Research. His research skills encompass machine learning applications in biology, high-throughput data analysis, and integrative multi-omics visualization. Prof. Miao has been honored with several prestigious awards such as the Guangzhou Leading Talent Award, National Science Fund for Outstanding Young Scholars (Overseas), and recognition among the Top 10 Advances in Chinese Bioinformatics. Actively engaged in scientific leadership, he serves as a Council Member of the Guangdong Provincial Genetics Society and contributes to organizing international symposia like the RNA-Puzzles Challenge. In conclusion, Prof. Zhichao Miao stands out as an influential scientist whose interdisciplinary research and visionary leadership continue to advance global bioinformatics innovation and biological data science.

Profile: Google Scholar

Featured Publications

  1. Sungnak, W., Huang, N., Bécavin, C., Berg, M., Queen, R., Litvinukova, M., … & Miao, Z. (2020). SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes. Nature Medicine, 26(5), 681–687. Citations: 3006

  2. Polański, K., Young, M. D., Miao, Z., Meyer, K. B., Teichmann, S. A., & Park, J. E. (2020). BBKNN: fast batch alignment of single-cell transcriptomes. Bioinformatics, 36(3), 964–965. Citations: 843

  3. Popescu, D. M., Botting, R. A., Stephenson, E., Green, K., Webb, S., Jardine, L., … & Miao, Z. (2019). Decoding human fetal liver haematopoiesis. Nature, 574(7778), 365–371. Citations: 589

  4. Büttner, M., Miao, Z., Wolf, F. A., Teichmann, S. A., & Theis, F. J. (2019). A test metric for assessing single-cell RNA-seq batch correction. Nature Methods, 16(1), 43–49. Citations: 485

  5. Muus, C., Luecken, M. D., Eraslan, G., Sikkema, L., Waghray, A., Heimberg, G., … & Miao, Z. (2021). Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics. Nature Medicine, 27(3), 546–559. Citations: 381

  6. Miao, Z., Adamiak, R. W., Antczak, M., Batey, R. T., Becka, A. J., Biesiada, M., … & Westhof, E. (2017). RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme. RNA, 23(5), 655–672. Citations: 216

  7. Miao, Z., Westhof, E. (2017). RNA structure: advances and assessment of 3D structure prediction. Annual Review of Biophysics, 46(1), 483–503. Citations: 206

 

Mahsa Darbandi | Molecular Biology | Best Researcher Award

Published on by Academic Achievements

Dr. Mahsa Darbandi | Molecular Biology | Best Researcher Award

Postdoctoral | Hope generation foundation | Iran

Short Biography 🌟

Mahsa Sara Darbandi is a dedicated researcher in the field of reproductive biotechnology, renowned for her expertise in oxidative stress impacts on spermatozoa and genetic, epigenetic, and metabolite status. She holds a Ph.D. from the Avicenna Research Institute, Tehran, Iran, where her doctoral research focused on understanding these complex interactions. Mahsa has furthered her knowledge through international programs like the American Center for Reproductive Medicine (ACRM), enhancing her skills in proteomic analysis and artificial intelligence applications in medicine.

Profile:

ORCID

Education 📚

Mahsa earned her Bachelor of Science in Biology from the University of Tabriz, Iran, followed by a Master of Science in Biochemistry from the University of Mashhad. Her thesis investigated the effects of electro-acupuncture combined with a low-calorie diet on body weight and plasma leptin levels in obese individuals. Subsequently, she pursued her Ph.D. in Reproductive Biotechnology at the Avicenna Research Institute, where she explored the intricate relationship between oxidative stress and sperm biology.

Experience 💼

Her professional journey includes significant milestones such as the Summer Mentorship Program and ART Training Program at ACRM, Cleveland Clinic, OH, where she honed her skills in laboratory methods and quality assurance in human reproduction. As part of the ACRM Global Researcher Program, Mahsa engaged in meta-analysis projects focusing on male infertility, demonstrating her proficiency in data analysis and scientific writing.

Research Interest 🔬

Mahsa’s research interests encompass the application of artificial intelligence and machine learning in medical image processing and big data analysis, particularly in the context of early cancer detection and personalized medicine for breast and prostate cancers. Her current endeavors at the Hope Generation Foundation in Tehran aim to advance early detection techniques in oncology.

Awards 🏆

Throughout her career, Mahsa has been recognized for her contributions to reproductive biology and male infertility research. Her work has been published in prestigious journals and cited extensively, underscoring her impact on the field.

Publications 📄

  • Publication Title: “Impact of Oxidative Stress on Sperm DNA Integrity and Its Clinical Significance in Male Infertility”
    • Journal: Journal of Reproduction & Infertility
    • Summary: This study explores the detrimental effects of oxidative stress on sperm DNA integrity and its implications for male infertility. It discusses potential clinical interventions to mitigate these effects.
  • Publication Title: “Epigenetic Modifications in Spermatozoa: Potential Implications for Assisted Reproductive Technologies”
    • Journal: Andrologia
    • Summary: This paper reviews epigenetic changes in spermatozoa and their relevance to assisted reproductive technologies (ART). It discusses how these modifications could influence embryo development and reproductive outcomes.
  • Publication Title: “Metabolomic Profiling of Spermatozoa in Men with Varicocele-Associated Infertility”
    • Journal: Systems Biology in Reproductive Medicine
    • Summary: This research employs metabolomic profiling to identify metabolic alterations in spermatozoa from men with varicocele-associated infertility, offering insights into potential biomarkers and therapeutic targets.
  • Publication Title: “Application of Artificial Intelligence in Medical Image Processing for Early Detection of Breast Cancer”
    • Journal: Journal of Medical Imaging and Health Informatics
    • Summary: This article explores the application of artificial intelligence techniques in medical image processing specifically for early detection of breast cancer, highlighting the potential for improved diagnostic accuracy and patient outcomes.
  • Publication Title: “Genetic and Epigenetic Biomarkers in Prostate Cancer: Implications for Personalized Medicine”
    • Journal: Current Genomics
    • Summary: This review examines genetic and epigenetic biomarkers associated with prostate cancer, emphasizing their potential utility in personalized medicine approaches for diagnosis, prognosis, and treatment selection.