Preface
Page: iii-iii (1)
Author: Anupam Nath Jha, Sandeep Swargam and Indu Kumari
DOI: 10.2174/9789815165616123010003
About the Editors
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Author: Anupam Nath Jha, Sandeep Swargam and Indu Kumari
DOI: 10.2174/9789815165616123010004
An Introduction to the Integration of Systems Biology and OMICS data for Animal Scientists
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Author: Sandeep Swargam* and Indu Kumari*
DOI: 10.2174/9789815165616123010006
PDF Price: $15
Abstract
Systems biology integrates the data of all the omics studies and provides the
avenues to understand the biology of an organism at higher levels like at tissue, organ
or organism level. In the last decade, studies of genomics, transcriptomics, proteomics
and metabolomics have been carried out. Only a limited amount of this big data has
been analyzed, which is mainly focused on the genotype (single nucleotide
polymorphism) level like minor allele frequency, copy number variation and structural
variants. The analysis in transcriptomics is limited to differentially expressed genes and
their ontology. Proteomics is focused on virulent factors, proteins involved in the
disease progression and immunomodulation. However, in the case of livestock animals,
there is a need to develop pipelines for the analysis of the omics data. With the
integration of omics data into systems biology studies, there is a need to develop
algorithms to carry out gene interaction and protein interaction studies and to build
interaction networks. The pathway analysis of a system requires the well-defined
interacting hub and edges of the protein system of an organism. Developing AI-ML
models for drug discovery is required to target the pathogens of livestock animals. In
the present era, the research is moving towards single-cell sequencing of the cells and
tissues to explore the genetic heterogeneity in the micro-environment of the tissue and
spatial biology of the tissue. This chapter will introduce the reader to different aspects
of omics technology and its role in systems biology for better livestock management.
Application of Multi-scale Modeling Techniques in System Biology
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Author: Shweta Sharma* and Dinesh Kumar
DOI: 10.2174/9789815165616123010007
PDF Price: $15
Abstract
Systems biology intends to portray as well as comprehend biology around
the globe, where biological processes are acknowledged as the outcome of complex
mechanisms which occur on multiple dimensions beginning with the molecular level
and reaching to ecosystem level. Biological information in systems biology comes
from overlying but distinct scientific areas, each with its own style of expressing the
events under research. Simulation and modeling are computer-aided methods that are
precious for the quantitative and integrative description, prediction, and exploration of
these mechanisms. In addition, Multi-level and hybrid models have been developed to
meet both improved accuracy and capability of making good knowledge bases, which
turned out to be a valuable tool in computational systems biology. Various methods,
including the silicon model, have been developed in many scientific disciplines for
solving multi-scale problems, which is appropriate to continuum-based modeling
strategies. The association between system properties is depicted using continuous
mathematical equations in which heterogeneous microscopic elements, such as persons,
are modelled using individual units. We summarized multi-scale methodologies and
their application in biotechnology and drug development applications in view of
emphasizing the importance of studying systems as a whole with the role of artificial
intelligence and biostatistical aspects in this review.
The Perspective of Physiome Modelling in Systems Biology: New Horizon
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Author: Prachi P. Parvatikar*, Shrilaxmi Bagali, Pallavi S. Kanthe, Aravind V. Patil and Kusal K. Das
DOI: 10.2174/9789815165616123010008
PDF Price: $15
Abstract
Scientific understanding has rapidly expanded in the new biological age,
with the rapid advancement of genomic science and molecular biology, It is a challenge
to reintegrate the enormous quantity of information and data that was generated from
works related to genomics, transcriptomics, proteomics, and metabolomics in order to
effectively explain the organism and connect molecular processes with higher-level
biological phenomena. Scientific understanding has expanded quickly in the new
biological age due to the rapid advancement of genomic science and molecular biology.
This inspired contemporary interest in systems biology, which investigates organisms
as integrated systems made up of dynamic and interconnected genetic, protein,
metabolic, and cellular components using biology, mathematics, biophysics,
biochemistry, bioinformatics, and computer science. Systems biology is the key
concept underlying Physiome, a mathematical measure of how an organism functions
in normal and pathologic states which is based on morphome. The simulation models
based on mathematical expressions and physics can aid in the interpretation and
encapsulation of biological phenomena in a computable and repeatable manner.
Researchers have created tools and standards to allow the reproducibility and reuse of
mathematical models of biological systems, as well as tools and guidelines to promote
semantic representation of computational models and repositories where models can be
archived, shared, and discovered.
A Systems Biology Approach in Fisheries Science
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Author: Kushal Thakur, Dixit Sharma, Disha Chauhan, Danish Mahajan, Kanika Choudhary, Bhavna Brar, Amit Kumar Sharma, Reshma Sinha, Ranjit Kumar, Sunil Kumar and Rakesh Kumar*
DOI: 10.2174/9789815165616123010009
PDF Price: $15
Abstract
Systems biology is concerned with complex interactions in biological
systems, employing a holistic manner in addition to classical reductionism. Systems
biology uses statistics, computational biology, and mathematical modelling to integrate
and analyse vast data sets to obtain a better knowledge of biology and predict the
behaviour of biological systems. It has gained attention in fisheries because of its
ability to uncover novel processes. It can generate a panorama of events that occur
within fish. In a systems biology approach, data from fish genomics, transcriptomics,
proteomics, and metabolomics are integrated, allowing for a comprehensive
understanding of dynamic systems with varying degrees of biological organisation.
Protein-protein interactions help us understand the systematic mechanisms underlying
overall growth, development, physiology, and disease in fish. Systems biology and
omics techniques are being applied in a variety of fisheries studies such as species
identification, understanding the processes of infection and stress tolerance, fishpathogen interactions, fish disease diagnostics and disease control, the impact of
environmental factors on fish, and determining the fish's response to these,
identification of gene sequences and biomarkers. Except for a few pioneering
applications of system biology to Fisheries, this approach to fisheries research is still in
its infancy stage. Systems biology has the potential to provide solutions to the diverse
issues of fisheries.
System Biology and Livestock Gut Microbiome
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Author: Shyamalima Saikia, Minakshi Puzari and Pankaj Chetia*
DOI: 10.2174/9789815165616123010010
PDF Price: $15
Abstract
With the recent advances in high throughput next-generation sequencing
technologies and bioinformatics approach, gut microbiome research, especially in
livestock species, has expanded immensely, elucidating the greatest potential to
investigate the unacknowledged understanding of rumen microbiota in host physiology
at the molecular level. The association of a complex aggregated community of
microbes to host metabolism is of great importance due to their crucial participation in
metabolic, immunological, and physiological tasks. The knowledge of this
sophisticated network of a symbiotic association of gut microbiota to host organisms
may lead to novel insights for improving health, enhancing production, and reducing
the risk of disease progression in livestock species necessary to meet the demands of the
human race. The full picture of microorganisms present in a particular area can be
achieved with the help of culture-independent omics-based approaches. The integration
of metagenomics, metatranscriptomics, metaproteomics, and meta-metabolomics
technologies with systems biology emphasizes the taxonomic composition,
identification, functional characterization, gene abundance, metabolic profiling, and
phylogenetic information of microbial population along with the underlying
mechanism for pathological processes and their involvement as probiotic. The rumen
secretions or partially digested feed particles, as well as fecal samples, are generally
employed for gut microbiome investigation. The 16S rRNA gene sequencing
amplicon-based technology is the most employed technique for microbiome profiling
in livestock species to date. The use of software and biological databases in the field of
gut microbiome research gives an accurate in-depth analysis of the microbial
population greatly.
Omics in Livestock Animals: Improving Health, Well-being and Production
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Author: Dixit Sharma, Disha Chauhan, Sunil Kumar, Ankita Sharma, Kushal Thakur, Kanika Choudhary, Jigmet Yangchan, Rakesh Kumar and Ranjit Kumar
DOI: 10.2174/9789815165616123010011
PDF Price: $15
Abstract
India has an extensive livestock wealth with a growing rate of 6% per
annum with a crucial role in the Indian economy. The livestock sector is one of the
important subsectors of agriculture, which contributes 25.6% of total agriculture GDP.
The arrival of deep sequencing technologies such as Next Generation Sequencing
(NGS) and Single Cell Sequencing (SCS) has produced huge sequence data that can be
exploited to advance well being, health, reproduction and yield of livestocks by
employment of integrated omics strategies. The current era of omics, i.e., genomics,
transcriptomics, proteomics, metabolomics, translatomics and single-cell sequencing,
has considerably improved researcher's understanding of livestock research at the gene
level and opened new avenues in terms of single-cell studies, which need to be carried
out in the near future. NGS plays a crucial role in understanding the genetic mechanism
of animal’s functions and its interaction with the environment. Furthermore, the SCS
will provide insight into the functions of cell types in livestock species. The data
generated using NGS and SCS approaches may help to discover novel molecular
markers from the complete genome and develop global diagnostic methods for the
detection of infectious diseases and their agents.
Livestock Viral Diseases and Insights into Systems Biology
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Author: Debajit Dey, Zaved Hazarika, Akhilesh Kumar Pandey and Subhomoi Borkotoky*
DOI: 10.2174/9789815165616123010012
PDF Price: $15
Abstract
With the increasing human population, livestock farming has been
intensified over the years to support different products from farm animals. Hence, the
requirement to monitor livestock diseases becomes critical. In particular, outbreaks due
to viral diseases are a major concern for the livestock industry worldwide. It has been
observed that close interaction of humans-livestock could lead to transboundary
diseases. Hence detection of potential viral pathogens requires a deeper understanding
of the livestock virome. The rapid development of bioinformatics and computational
tools, as well as advances in Next-Generation Sequencing (NGS) technologies, has
opened up new options for infectious disease surveillance in terms of both quality and
scale. The phrase “systems biology” has just been recently adopted to define cutting-edge cross-disciplinary biology research. Synthetic biology, integrative biology,
systems biomedicine, and metagenomics are some of the growing post-genomic
domains that intersect with systems biology. Systems biology represents a paradigm
shift in biology and medicine from many perspectives by incorporating a new culture
that acknowledges the dynamic and interdependent interactions of the complex
network of genes and their associated proteins in order to gain a systematic
understanding of biology, health, and disease. By enhancing our understanding of viral
disease development, diagnosis, prevention, and therapy, the application of systems
biology to human and veterinary medicine has the potential to transform healthcare.
The current chapter focuses on examples of various viral diseases associated with
livestock animals and the role of systems biology approaches to understand them.
Proteomics in Livestock Health and Diseases
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Author: Padmani Sandhu*, Indu Kumari and Sandeep Swargam
DOI: 10.2174/9789815165616123010013
PDF Price: $15
Abstract
Proteomics is a branch of science that allows us to study a whole expressed
protein pool from a cell or tissue. This has been helpful for many years in studying
microbial makeup, but in animals, this field has not been explored much due to factors
like the complexity and variation in genes of every cell depending upon their
specialized function and tissue organization. However, in recent years many new
techniques have been introduced in this area, which has added to the plethora of
knowledge about animal proteins and has made it easy to understand the diseases and
health-related aspects of livestock science. In this chapter, we will discuss the new
advancements in animal proteomics to discover the protein pool from the different
animal species of interest, branches of proteomics, and their role in livestock health and
diseases.
Importance and Potential Applications of Nanobiotechnology and Systems Biology for Livestock Science
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Author: Zaved Hazarika, Upasana Hazarika, Babli Sharma and Anupam Nath Jha*
DOI: 10.2174/9789815165616123010014
PDF Price: $15
Abstract
Nano-materials were utilized as therapeutics and diagnostics agents in the
context of human medicine. However, the application of nanoparticles in the field of
livestock animals is still at a nascent stage. The proper utilization of nanoparticles in
livestock sciences, such as improvement in milk production, diagnosis of varied
diseases, delivery of nutrients and/or in their reproduction, offers prospective outcomes
which have direct implications to meet the ever-growing human populations. Further,
with the advent of high throughput omics technologies, noteworthy development in the
past decades has paved the way to advanced systems biology area. The high throughput
data handling from diverse omics methodologies and making a holistic interpretation
posed a challenge, moreover, to connect the dots and present a larger picture of the
intricate network level data, systems biology comes to the rescue. The design and
advancement in different algorithms of systems biology tools seldom help one to
integrate multi-layered data. Systems biology is applied to livestock animals and
poultry for their overall development and/or risk assessment for their diseases. In this
chapter, we discussed the implementation of nanobiotechnology and systems biology
approaches to livestock animals. We illustrated a few examples of how the application
of nanotech and systems biology improved some desired qualities in livestock. This
chapter summarizes the ongoing research and efforts of different groups, along with the
future prospects of innovative technologies in the area of nanotech and systems
biology.
Single Cell RNA-Sequencing and Its Application in Livestock Animals
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Author: Renu Verma, Parameswar Sahu, Aarti Rana, Sandeep Swargam* and Indu Kumari*
DOI: 10.2174/9789815165616123010015
PDF Price: $15
Abstract
Single cell RNA sequencing (ScRNAseq) is in its infancy. There are limited
studies in which this technique has been implemented to solve the scientific problem.
ScRNAseq involves well facilitated labs and high end computing facilities. The
ScRNAseq studies were mainly carried out in the clinical and biomedical areas. These
studies are carried out in cancer research, which involves the role of immune genes or
immunotherapy for cancer treatment. The human cell atlas programme is going on and
atlases for different human cells are being released as it is completed. However, in the
case of livestock animals, it has just started. In India, there are few ScRNAseq studies
that have focused on the different developmental stages of buffalo. The experimental
and bioinformatics analysis ScRNAseq involves various steps. Among this, the
alignment of reads to reference genome/transcriptome is important. There is a need to
develop a standardized reference genome/transcriptome for each type of cell present in
different domestic/commercial livestock. Once we have all the valuable information
from ScRNAseq, then this data can be integrated with system biology approaches to
understand the cellular processes at a larger scale. This integration of interdisciplinary
sciences will enhance the production, quality and health of the livestock animals and
may help for sustainable management of livestock.
AI-ML and System Biology for Drug Discovery in Livestock
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Author: Parameswar Sahu and Dibyabhaba Pradhan*
DOI: 10.2174/9789815165616123010016
PDF Price: $15
Abstract
Advanced research methods have enhanced the productivity and problem
solving abilities of scientific development in the field of drug designing and discovery.
Various diseases have been problematic for the survival of human civilisation and
livestock. Available methods that can provide results for diseases include; computer
aided drug designing, system biology, and machine learning. Due to the diversity of
livestock and multiple disease types, robust methods are required for drug discovery.
Artificial intelligence has paved the way for faster problem solving innovations and
discoveries in multiple aspects, such as economics, engineering, and healthcare.
Systems biology plays a pivotal role in the biological evaluation of living beings.
System-level understanding of livestock animals is the need of the hour for effective
drug discovery, which includes genomic, proteomic, enzymatic, and metabolic
pathways involved in a biological system. Livestock deaths due to diseases are reported
worldwide, which creates a demand for drug discovery solutions. Multiple diseases for
various livestock have been investigated, and drug discovery has been a great relief for
those specific diseases. In this context, we have communicated about the integration of
all the above mentioned aspects (artificial intelligence, machine learning, systems
biology, drug discovery) to come up with a better resolution for the livestock in terms
of drug development.
Genomics to Systems Biology in Livestock Management: its Applications and Future Perspective
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Author: Bheemshetty S. Patil*, Pallavi S. Kanthe, Prachi P. Parvatikar and Aravind V. Patil
DOI: 10.2174/9789815165616123010017
PDF Price: $15
Abstract
The recurrent and comprehensive study of biological systems as a single
entity in response to stimuli is known as systems biology. The introduction of high-throughput technology for studying an animal's DNA, proteome, and metabolome was
a blow to reductionism in livestock science. It is based on ideas formalized in models
derived from global functional genomics investigations of the genome, transcriptome,
proteome, metabolome, and other complex biological systems. The mapping of entire
sets of genes, transcripts, proteins, and metabolites from a variety of organisms has
driven the creation of novel '-omic' technologies for gathering and analyzing vast
amounts of data. This widely defined systems approach is being used to address a wide
range of issues and organizational scales, along with several elements of livestock
research. It is well established that the tools that relate genetic variations to their
cellular activities, pathways, and other biological roles will become even more essential
in the future. For each animal genomics research issue, a vision, current state of the art,
research needed to progress the field, expected outputs, and partnerships are required.
Modern computational tools capable of finding functional implications and biologically
meaningful networks complement the ever-increasing ability to generate massive
molecular, microbial, and metabolite data sets. The intricate inter-tissue responses to
physiological status and nutrition can now be seen at the same time. The knowledge
acquired from the application of functional analysis of systems biology data sets to
livestock management in order to improve productivity, quality, and yield.
Applications and Future Perspectives of Computational Approaches in Livestock Animals
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Author: Upasana Pathak, Abhichandan Das, Pranjal Kumar Bora and Sanchaita Rajkhowa*
DOI: 10.2174/9789815165616123010018
PDF Price: $15
Abstract
Livestock is regarded as a critical point of access for enhanced food and
nutrition. With the population explosion, an increase in the successful fulfillment of
livestock production, including meat and dairy products, is necessary in the most
ethical way. Fundamentally keeping the overall nutrition intact along with the health of
both human and livestock animals is vital. Although there is an increment in
production, it contributes to rising greenhouse gas (methane) emissions, thus damaging
the environment. Inheriting novel technologies will not only help in the surplus
upliftment of livestock products but also the emission of greenhouse gases. Omics and
Systems Biology are such approaches. Omics is a combination of different aspects
dealing with complete molecular levels ranging from DNA to protein, protein to
metabolites, whereas Systems Biology is the analysis of both mathematical and
computational along with biological system modeling. Omics gives a broad overview
of both pathways and traits controlling various characters. Thus, showing detailed links
between genotype-phenotype. It can yield an enormous amount of data with incredible
speed. In addition, Systems Biology lines up to give an overview of the complete
biological system rather than just examining a single biological molecule. It combines
mathematical modelling, statistics, and bioinformatics for a better grip and
understanding of the enormous data sets. In this chapter, we discuss the latest cutting-edge technologies in the field of livestock and how omics can be implemented in
creating disease resistant livestock animals without hampering the quality of the
products. The chapter also discusses the various applications and future scopes
involving computational approaches towards animal science.
Subject Index
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Author: Anupam Nath Jha, Sandeep Swargam and Indu Kumari
DOI: 10.2174/9789815165616123010019
Introduction
This book explores the intricate world of livestock sciences and production through the lens of systems biology. Offering a comprehensive exploration of both fundamental and advanced aspects, it unearths the potential of systems biology in the realm of livestock. The book presents 13 edited chapters on cutting-edge knowledge about systems biology and omics technology, showcasing genomics, transcriptomics, proteomics, metabolomics, and more. It illuminates the role of systems biology in livestock and disease management. Readers will learn about power of technologies that merge computational biology, nanobiotechnology, artificial intelligence, and single-cell sequencing. Each chapter is written by scientific experts and includes references for further reading. The book covers 4 key themes: Introduction to Systems Biology in Livestock Science: Uncover the foundation of integrating systems biology with omics data for animal scientists. Multi-scale Modeling Techniques: Explore how multi-scale modeling is shaping the future of system biology. Livestock Viral Diseases: Gain insights into how systems biology is revolutionizing our understanding of livestock viral diseases. Single Cell RNA-Sequencing: Understand the potential of this advanced technique in studying livestock animals at a cellular level. This book is a timely resource for students and researchers, offering a pathway to comprehend the crucial role systems biology plays in sustainable livestock production and management.