Laboratory for Structural Biology of Membrane Proteins, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India.
Central Council for Research in Homoeopathy, Ministry of Ayush, Govt. of India, New Delhi, Delhi, India.
Adv Protein Chem Struct Biol. 2024;139:221-261. doi: 10.1016/bs.apcsb.2023.11.006. Epub 2024 Feb 15.
Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.
生物信息学是一门相互关联的科学学科，涉及生物学、化学、物理学、统计学、数学和计算机科学等多个领域，这些领域是解决复杂生理问题的关键领域。生物信息学的主要目的是存储、分析、组织和检索有关基因组、蛋白质组、转录组、代谢组以及生物体的重要信息，以研究生物系统及其动态。生物信息学的结果取决于提供的原始数据的类型、数量和质量，以及用于分析相同数据的算法。尽管有几种已批准的药物可用，但心血管疾病 (CVD) 和癌症仍然是人类死亡的两个主要原因。了解这两种非传染性疾病的未知事实是不可避免的，这是为了发现新的途径，寻找新的药物靶点，并最终成功地开发出更新的药物。由于所有这些目标都涉及对人体各种类型的大分子和小分子的复杂研究和处理，因此生物信息学在这些过程中起着关键作用。这些研究的结果具有直接的人类应用，因此我们将这个领域称为转化生物信息学。当前的章节涉及到转化生物信息学的广泛应用，以寻找治疗、诊断和理解 CVD 和癌症的机制。开发用于解决这些问题的复杂但小或长的算法在转化生物信息学中很常见。基于结构的药物发现或人工智能指导的新型抗体的发明，具有超高的准确性、速度和涉及相对较低的投资，这是转化生物信息学及其在 CVD 和癌症领域的应用的一些惊人特点。
