Computer and molecular biology at cellular levels. Human biological

Computer Science
and Systems Biology have heralded remarkable technological advances in
understanding the complex biological systems including human biochemical,
molecular and neural pathways and networks. Systems biology integrates the
computer applications and experimental biology in modelings, predictions and
characterizations of complex and dynamic properties of biological systems.
Particularly, multi-omics studies, high-throughput sequencing techniques and
microarray techniques made possible the generation of large datasets from
biological systems that could help in understanding the comprehensive molecular
pathways, systems functions and behaviors. In the last decade, the computer
science and systems biology approaches increased the interest in pathway based
biomarker identification, identifying disease genes and drug targets,
generation of global genetic interaction maps, and development of new diagnosis
and therapeutics methods for deadly diseases and contemporary outbreaks. In
this letter, I summarize the breakthroughs of the decade and future challenges
in uncover the complex components of biological systems.

The integration
of basic sciences with computer science and technological approaches is a
revolutionary event in human life. The basic and applied biological techniques
provided morphological and anatomical understanding, which is not quite enough
to study the basis of biochemistry and molecular biology at cellular levels.
Human biological systems are composed of complex biochemical and molecular
pathways. Hence, uncover the 3-dimentional (3-D) architecture of the cell was
the biggest challenge before the integration of biology and computational
approaches. Before the collaboration, however, basic analytical techniques
helped in identifying various biomolecules, many questions unanswered due to
the lack of availability of large scale data analysis.  Computer aided concepts led to the new
direction in biological sciences, which provided insights into understanding biomolecules,
genes and networks. The inception of bioinformatics paved a new path towards
the development of DNA, RNA and protein databases, where the large sets of data
can be stored. Further research advancements in biological systems opened doors
for a new branch of integrated science, named ‘Systems Biology’ that provided updated
knowledge about networks of biological systems, genetics, gene products,
genomics and the 3-D architecture of cell.

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The integrated
studies established a framework in intelligent systems, data mining, and
visualization. Moreover, the development of large data sets of disease causing
genes, pathogenic process allowed identifying disease markers, drug targets,
which further provided insights into drug design models, novel diagnosis and
therapeutic strategies. In addition, improved mathematical and mechanism based
modeling, simulation studies, and quantitative system studies, combined with
data-driven analytics increased the interest in drug discovery, validation and
optimization of clinical development. A fast-growing area developed from
integration of bioinformatics and systems biology is system medicine, which
provide integrated treatment options at individual level. As of now the
clinical applications are limited; however, it is believed that the continuous
efforts in analyzing physiological networks, data from multiple sources and
highly monitored biological changes would change the pace of development in
system medicine. In future, in precision medicine, accumulation of data points
from individual makes each person as a longitudinal study.

Indeed, there
are remarkable breakthroughs witnessed, significant challenges limiting the
progression of computational and systems biology in changing directions towards
the development in personalized medicine. Of course, the large data sets are
available for modeling and comparative studies, the curation of large data sets
and creating a global infrastructure to access the data is a major challenge.
Creation of high level information models is on great demand to map the
biological systems. As systems biology is multi-dimensional area, matter of
community (an engineer, a biochemist, a computer scientist, and a physician) is
another biggest challenge; in fact, it is much bigger than technical aspects
related to clinical studies. Establishing worldwide collaborations to transfer
the knowledge and technology and creating space to analyze global data, is
another challenge. In recent time, data science (big data) artificial
intelligence (neural networks) becoming more powerful tools in the study of
biological systems by using informatics approaches; hence, availability of
expertise in these emerging dimensions are also significant. 

In summary, the
future in biological science, integrated with computational biology will create
more opportunities to the researchers to understand all biological systems at
deeper levels. It is expected that there will be a large shift towards
mathematical, computational aided biology that eventually improve the
healthcare and quality of life of human beings. 

Journal of Computer Science and Systems Biology a
Decade move-on

Owing to the
benefits of open access publishing in disseminating knowledge across various
fields including science, medicine and technology, I would appreciate efforts
made by the editors, reviewers and contributors of Journal of Computer Science
and Systems Biology on its successful completion of 10 years in open access
publishing. In the highly competitive open access market, it is difficult to
attract the contributors and readers by publishing high quality original works
and reviews in timely fashion. Journal of Computer Science and Systems Biology
showed the commitment in selecting papers and maintaining history of quality publication
over a decade. The survival of such committed publications is becoming
questionable now-a-days, because of the commercial perspectives of many
emerging publishers. The communities from computer sciences, systems biology
are looking for the decades ahead and expected endless efforts from the editor
of the journal to continue the legacy. 

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