Emerging Technologies: Gateway
to Understand Molecular Insight
of Diseases, Newer Drugs, Their Design,
and Targeting
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R. C. Sobti, Mamtesh Kumari, Mandakini Singhla,
and Ranjana Bhandari
Abstract
In the present time, our understanding of disease pathogenesis has changed
significantly due to the advent of newer technology and recent scientific
breakthroughs. The network models consisting of the genomic regions are
being prepared by combining the developed molecular phenotyping profiling
with deep clinical phenotyping, which can influence the levels of transcripts,
proteins, and metabolites and can be exploited in various ways in diagnosing
diseases and personalized drug development. Digital biomarkers (BM) can sup-
port in disease diagnosis in multiple ways, including patient identification to
treatment recommendation. The use of “omics” technology and large sample
sizes has resulted in vast data sets, providing a wealth of knowledge about
different illnesses and their links to intrinsic biology. The analysis of such
extensive data requires sophisticated computational and statistical methods.
New data can be converted into usable knowledge to allow for faster diagnosis
and treatment choices using these advanced technologies, such as artificial
intelligence, machine learning algorithms, computational biology, and digital
BMs. As a result, it is expected that such advancements would aid in the fight
R. C. Sobti
Department of Biotechnology, Panjab University, Chandigarh, India
e-mail: rcsobti@pu.ac.in
M. Kumari (*)
Department of Zoology, Radhe Hari Post Graduate College, Kashipur, Uttarakhand, India
e-mail: Mamteshkumari2016@gmail.com
M. Singhla
Department of Zoology, Panjab University, Chandigarh, India
R. Bhandari
University Institute of Pharmaceutical Sciences, Panjab University, Chandigarh, India
# The Author(s), under exclusive license to Springer Nature Singapore Pte
Ltd. 2022
R. C. Sobti, N. S. Dhalla (eds.), Biomedical Translational Research,
https://doi.org/10.1007/978-981-16-9232-1_1
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