In the past, cancer and various diseases were primarily treated with a focus on alleviating symptoms. However, with the rise and development of Next Generation Sequencing (NGS) technology and molecular biology, there has been a more fundamental understanding and recognition of diseases and medicine. For example, targeted therapies that focus on specific signaling pathways to assist chemotherapy and surgical treatment of cancer, or precision medicine that administers different drugs based on the genetic sequences of individuals.
The cost-effectiveness and high-throughput capabilities of next-generation sequencing have made it possible to apply whole-exome sequencing in clinical settings. Coupled with AI technology and various statistical analysis techniques, this opens up new treatment directions for many previously difficult-to-treat or unknown diseases, providing patients and their families with hope.
This is the dawn of a new generation, and may we harness the immense potential of algorithms to assist in advancing medicine and biotechnology!
Especially in recent years, as deep learning and universal parallel computing architectures have matured, the field of bioinformatics has increasingly adopted these technologies to develop a wide range of applications. This allows for the effective utilization of the vast amounts of data generated by next-generation sequencing. It’s akin to having a divine perspective in the battle between individuals and diseases, enabling us to obtain crucial information about diseases and offering people more choices and hope.
Therefore, we aim to fully leverage multi-omics data to participate in the next generation of biological and medical transformation. By combining data science and engineering techniques, we seek to identify meaningful signals from biological samples or clinical care, ranging from the analysis and processing of raw data from next-generation sequencing to various forms of broad single-cell analysis.
Ming Han Yang
NEXT Generation / Founder
www.next-bioinfo.tw
A passionate bioinformatician focuses on the next generation of medical science and biotechnology.
With over 4 years of experience in Hi-C and Hi-ChIP data analysis, Specializing in various NGS data processing and machine learning modeling.
For any project related to bioinformatics, including NGS, scRNA-Seq, Hi-C, research collaborations, or consulting needs, can email me at: whuang022@gmail.com.
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