1 Introduction
This decade has been witnessing a major shift in technologies which have been
used in various sectors ranging from social media, agriculture, services, to science
and technology. In the current age, new advances are being made in the field of
satellites, robotics, micro- and nanotechnologies as well as revolution in computing.
The stream of science has been impacted by this revolution. All disciplines of
science have been generating and building newer technologies and different
approaches for scientifically accurate experimentation. All these developments in
various scientific disciplines are also changing our social life, health, environment,
etc. One of the major streams of science is life sciences, which has been strongly
affected and accelerated due to all these advancements in techniques and
technologies.
Various technologies like next-generation sequencing (NGS) in genomics,
high-throughput assays, and supramolecular chemistry are revolutionizing the life
sciences and applied areas of human health, agriculture, livestock, and many more
[1–4]. The robotics-based automation is generating volumes of data from various
experiments and characterization techniques. The next-generation biology has been
driven heavily by wet laboratory experimentation as well as dry laboratory
computation.
Technologies like next-generation sequencing (NGS) enable sequencing of
genomes of thousands of species in plants and animals at an extremely rapid rate
[5–7]. Today, many genome sequencing centers are producing data of about terabytes per week. This results in petabytes of data of sequencing information per
year. The figure is expected to grow exponentially and very soon will be facing
challenges of storage and analysis of exabytes of sequence data [5–7]. To extend
this further, there is already a race to sequence the genomes of all living species on
the planet including humans, plants, animals, microbes to name a few. It is expected
that this gigantic exercise will result in zetabytes to yottabytes of sequence data.
Such large volumes of sequence data will be the genomic ocean of tomorrow [7–9].
Similarly, structural database of biomolecules like protein, nucleic acids, lipids,
and membranes is also growing rapidly (shown in Fig. 1) due to methods like cryo
crystallization, high-frequency NMR, and other characterization techniques along
with computational modeling techniques [10]. Computational modeling and simulation of biomolecules have been drastically improving due to the advancement in
high-performance computing (HPC) [11] and development of advanced enhanced
sampling methods [12, 13]. It has paved the way for mimicking long timescale
events occurring in different biological systems more efficiently. Owing to the better
computing paradigm, today structural data generation is no more the major challenge, but analyzing this huge data has become one. Computer simulations help to
determine mechanism of action of biomolecules in a cell, thereby suggesting their
implication in various diseases and discovering their potential use in therapeutics.
Hence, the computational techniques generate biomolecular structural and
dynamical data via very long time scale simulations. Likewise, detailed and
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R. R. Joshi et al.
This decade has been witnessing a major shift in technologies which have been
used in various sectors ranging from social media, agriculture, services, to science
and technology. In the current age, new advances are being made in the field of
satellites, robotics, micro- and nanotechnologies as well as revolution in computing.
The stream of science has been impacted by this revolution. All disciplines of
science have been generating and building newer technologies and different
approaches for scientifically accurate experimentation. All these developments in
various scientific disciplines are also changing our social life, health, environment,
etc. One of the major streams of science is life sciences, which has been strongly
affected and accelerated due to all these advancements in techniques and
technologies.
Various technologies like next-generation sequencing (NGS) in genomics,
high-throughput assays, and supramolecular chemistry are revolutionizing the life
sciences and applied areas of human health, agriculture, livestock, and many more
[1–4]. The robotics-based automation is generating volumes of data from various
experiments and characterization techniques. The next-generation biology has been
driven heavily by wet laboratory experimentation as well as dry laboratory
computation.
Technologies like next-generation sequencing (NGS) enable sequencing of
genomes of thousands of species in plants and animals at an extremely rapid rate
[5–7]. Today, many genome sequencing centers are producing data of about terabytes per week. This results in petabytes of data of sequencing information per
year. The figure is expected to grow exponentially and very soon will be facing
challenges of storage and analysis of exabytes of sequence data [5–7]. To extend
this further, there is already a race to sequence the genomes of all living species on
the planet including humans, plants, animals, microbes to name a few. It is expected
that this gigantic exercise will result in zetabytes to yottabytes of sequence data.
Such large volumes of sequence data will be the genomic ocean of tomorrow [7–9].
Similarly, structural database of biomolecules like protein, nucleic acids, lipids,
and membranes is also growing rapidly (shown in Fig. 1) due to methods like cryo
crystallization, high-frequency NMR, and other characterization techniques along
with computational modeling techniques [10]. Computational modeling and simulation of biomolecules have been drastically improving due to the advancement in
high-performance computing (HPC) [11] and development of advanced enhanced
sampling methods [12, 13]. It has paved the way for mimicking long timescale
events occurring in different biological systems more efficiently. Owing to the better
computing paradigm, today structural data generation is no more the major challenge, but analyzing this huge data has become one. Computer simulations help to
determine mechanism of action of biomolecules in a cell, thereby suggesting their
implication in various diseases and discovering their potential use in therapeutics.
Hence, the computational techniques generate biomolecular structural and
dynamical data via very long time scale simulations. Likewise, detailed and
348
R. R. Joshi et al.