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World Congress on Genomics & Bioinformatics, will be organized around the theme “Exceeding the Vision in Genomics & Bioinformatics”
Genomics Congress 2019 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in Genomics Congress 2019
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Genomics is an interdisciplinary field of science focusing on the structure, function, evolution, mapping, and editing of genomes. A genome is an organism's complete set of DNAs, including all of its genes. In contrast to genetics, which refers to the study of individual genes and their roles in inheritance, genomics aims at the collective characterization and quantification of genes, which direct the production of proteins with the assistance of enzymes and messenger molecules. In turn, proteins make up body structures such as organs and tissues as well as control chemical reactions and carry signals between cells. Genomics also involves the sequencing and analysis of genomes through uses of high throughput DNA sequencing and bioinformatics to assemble and analyze the function and structure of entire genomes. Advances in genomics have triggered a revolution in discovery-based research and systems biology to facilitate understanding of even the most complex biological systems such as the brain.
Proteomics is the large-scale study of proteins. Proteins are vital parts of living organisms, with many functions. The proteome is the entire set of proteins that are produced or modified by an organism or system. Proteomics has enabled the identification of ever-increasing numbers of protein. This varies with time and distinct requirements, or stresses, that a cell or organism undergoes. Proteomics is an interdisciplinary domain that has benefitted greatly from the genetic information of various genome projects, including the Human Genome Project. It covers the exploration of proteomes from the overall level of protein composition, structure, and activity. It is an important c component of functional genomics.
Bioinformatics is both an umbrella term for the body of biological studies that use computer programming as part of their methodology, as well as a reference to specific analysis "pipelines" that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidate’s genes and single nucleotide polymorphisms (SNPs). Often, such identification is made with the aim of better understanding the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. In a less formal way, bioinformatics also tries to understand the organizational principles within nucleic acid and protein sequences, called proteomics.
Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule intermediates and products of metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. One of the challenges of systems biology and functional genomics is to integrate genomics, transcriptomic, proteomic, and metabolomic information to provide a better understanding of cellular biology.
Pharmacogenomics is the study of the role of the genome in drug response. Its name (pharmaco- + genomics) reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of an individual affects his/her response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with pharmacokinetics (drug absorption, distribution, metabolism, and elimination) and pharmacodynamics (effects mediated through a drug's biological targets). The term pharmacogenomics is often used interchangeably with pharmacogenetics. Although both terms relate to drug response based on genetic influences, pharmacogenetics focuses on single drug-gene interactions, while pharmacogenomics encompasses a more genome-wide association approach, incorporating genomics and epigenetics while dealing with the effects of multiple genes on drug response
Evolutionary Biology is the subfield of biology that studies the evolutionary processes that produced the diversity of life on Earth, starting from a single common ancestor. These processes include natural selection, common descent, and speciation.
Current research has widened to cover the genetic architecture of adaptation, molecular evolution, and the different forces that contribute to evolution including sexual selection, genetic drift and biogeography. The newer field of evolutionary developmental biology ("evo-devo") investigates how embryonic development is controlled, thus creating a wider synthesis that integrates developmental biology with the fields covered by the earlier evolutionary synthesis.
The goal of functional genomics is to understand the function of larger numbers of genes or proteins, eventually all components of a genome. A more long-term goal is to understand the relationship between an organism's genome and its phenotype. The term functional genomics is often used broadly to refer to the many technical approaches to study an organism's genes and proteins, including the "biochemical, cellular, and/or physiological properties of each and every gene product" while some authors include the study of nongenic elements in his definition. Functional genomics may also include studies of natural genetic variation over time (such as an organism's development) or space (such as its body regions), as well as functional disruptions such as mutations.
The promise of functional genomics is to generate and synthesize genomic and proteomic knowledge into an understanding of the dynamic properties of an organism. This would provide a more complete picture than studies of single genes. Integration of functional genomics data is also the goal of systems biology.
Structural genomics seeks to describe the 3-dimensional structure of every protein encoded by a given genome. This genome-based approach allows for a high-throughput method of structure determination by a combination of experimental and modeling approaches. The principal difference between structural genomics and traditional structural prediction is that structural genomics attempts to determine the structure of every protein encoded by the genome, rather than focusing on one particular protein.
Epigenomics is the study of the complete set of epigenetic modifications on the genetic material of a cell, known as the epigenome. The field is analogous to genomics and proteomics, which are the study of the genome and proteome of a cell. Epigenetic modifications are reversible modifications on a cell’s DNA or histones that affect gene expression without altering the DNA sequence. Epigenomic maintenance is a continuous process and plays an important role in the stability of eukaryotic genomes by taking part in crucial biological mechanisms like DNA repair. Plant flavones are said to be inhibiting epigenomic marks that cause cancers. Two of the most characterized epigenetic modifications are DNA methylation and histone modification. Epigenetic modifications play an important role in gene expression and regulation and are involved in numerous cellular processes such as in differentiation/development and tumorigenesis. The study of epigenetics on a global level has been made possible only recently through the adaptation of genomic high-throughput assays.
Pathogen infections are among the leading causes of infirmity and mortality among humans and other animals in the world. Until recently, it has been difficult to compile information to understand the generation of pathogen virulence factors as well as pathogen behavior in a host environment. The study of pathogenomics attempts to utilize genomic and metagenomics data gathered from high through-put technologies (e.g. sequencing or DNA microarrays), to understand microbe diversity and interaction as well as host-microbe interactions involved in disease states. The bulk of pathogenomics research concerns itself with pathogens that affect human health; however, studies also exist for plant and animal infecting microbes.
Immunomics is the study of immune system regulation and response to pathogens using genome-wide approaches. With the rise of genomic and proteomic technologies, scientists have been able to visualize biological networks and infer interrelationships between genes and/or proteins; recently, these technologies have been used to help better understand how the immune system functions and how it is regulated. Two thirds of the genome are active in one or more immune cell types and less than 1% of genes are uniquely expressed in each type of cell. Therefore, it is critical that the expression patterns of these immune cell types be deciphered in the context of a network, and not as an individual, so that their roles be correctly characterized and related to one another. Defects of the immune system such as autoimmune diseases, immunodeficiency, and malignancies can benefit from genomic insights on pathological processes. For example, analyzing the systematic variation of gene expression can relate these patterns with specific diseases and gene networks important for immune functions.
Oncogenomics is a sub-field of genomics that characterizes cancer-associated genes. It focuses on genomic, epigenomic and transcript alterations in cancer.
Cancer is a genetic disease caused by accumulation of DNA mutations and epigenetic alterations leading to unrestrained cell proliferation and neoplasm formation. The goal of oncogenomics is to identify new oncogenes or tumor suppressor genes that may provide new insights into cancer diagnosis, predicting clinical outcome of cancers and new targets for cancer therapies. The success of targeted cancer therapies such as Gleevec, Herceptin and Avastin raised the hope for oncogenomics to elucidate new targets for cancer treatment
Computational biology involves the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, ecological, behavioral, and social systems. The field is broadly defined and includes foundations in biology, applied mathematics, statistics, biochemistry, chemistry, biophysics, molecular biology, genetics, genomics, computer science and evolution.
Computational biology is different from biological computing, which is a subfield of computer science and computer engineering using bioengineering and biology to build computers, but is like bioinformatics, which is an interdisciplinary science using computers to store and process biological data.
Phylogenetics is the study of the evolutionary history and relationships among individuals or groups of organisms. These relationships are discovered through phylogenetic inference methods that evaluate observed heritable traits, such as DNA sequences or morphology under a model of evolution of these traits. The result of these analyses is a phylogeny a diagrammatic hypothesis about the history of the evolutionary relationships of a group of organisms. The tips of a phylogenetic tree can be living organisms or fossils, and represent the "end", or the present, in an evolutionary lineage. Phylogenetic analyses have become central to understanding biodiversity, evolution, ecology, and genomes.
A bioinformatics workflow management system is a specialized form of workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, that relate to bioinformatics.
There are currently many different workflow systems. Some have been developed more generally as scientific workflow systems for use by scientists from many different disciplines like astronomy and earth science. All such systems are based on an abstract representation of how a computation proceeds in the form of a directed graph, where each node represents a task to be executed and edges represent either data flow or execution dependencies between different tasks. Each system typically provides a visual front-end, allowing the user to build and modify complex applications with little or no programming expertise.
Structural bioinformatics is the branch of bioinformatics which is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structure such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, and binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology
Bioinformatics is the science that combines the fields of computer science and biology; to apply computational methods and techniques in biological processes to facilitate in data analysis and management. Bioinformatics has its applications in life sciences including genomics, proteomics, systems biology, molecular biology, etc. Drug design and development is an important area in life sciences as with the ever-changing times, the diseases have also greatly advanced in terms of severity and number causing more harm than ever. Drug development is the process of testing a drug against a target that has been selected/identified by drug discovery. However, this whole process is classified under modern drug development approaches
There has been a great explosion of genomic data in recent years. This is due to the advances in various high-throughput biotechnologies such as RNA gene expression microarrays. These large genomic data sets are information-rich and often contain much more information than the researchers who generated the data may have anticipated. Such an enormous data volume enables new types of analyses, but also makes it difficult to answer research questions using traditional methods. Analysis of these massive genomic data has several unprecedented challenges
Next-generation sequencing (NGS), also known as high-throughput sequencing, is the catch-all term used to describe several different modern sequencing technologies including:
- Illumina (Solexa) sequencing
- Roche 454 sequencing
- Ion torrent: Proton / PGM sequencing
- SOLiD sequencing
These recent technologies allow us to sequence DNA and RNA much more quickly and cheaply than the previously used Sanger sequencing, and as such have revolutionized the study of genomics and molecular biology
Molecular modelling encompasses all methods, theoretical and computational, used to model or mimic the behaviour of molecules. The methods are used in the fields of computational chemistry, drug design, computational biology and materials science to study molecular systems ranging from small chemical systems to large biological molecules and material assemblies. The simplest calculations can be performed by hand, but inevitably computers are required to perform molecular modelling of any reasonably sized system. The common feature of molecular modelling methods is the atomistic level description of the molecular systems. This may include treating atoms as the smallest individual unit (a molecular mechanics approach), or explicitly modelling electrons of each atom (a quantum chemistry approach).
Genomics & Bioinformatics has a key role to play in areas like agriculture where it can be used for increasing the nutritional content, increasing the volume of the agricultural produce and implanting disease resistance etc. There are large number of applications of genomics & bioinformatics in the fields of medicine, microbial genome applications and agriculture. Using them will allow researchers to reach a new height in their experiments. Major discoveries can be made faster and more efficiently. Today, every large molecular or systems biology project has a bioinformatics component. Genomics & Bioinformatics applications will allow biologists to extend expertise far more efficiently and effectively for data analysis and planning of experiments.
- Track 21-1Microbial Genome Applications
- Track 21-2Molecular Medicine
- Track 21-3Personalized Medicine
- Track 21-4Preventative Medicine
- Track 21-5Gene Therapy
- Track 21-6Antibiotic Resistance
- Track 21-7Waste Cleanup
- Track 21-8Biotechnology
- Track 21-9Climate Change Studies
- Track 21-10Alternative Energy Sources
- Track 21-11Crop Improvement
- Track 21-12Forensic Analysis
- Track 21-13Bio-weapon Creation
- Track 21-14Insect Resistance
- Track 21-15Improve Nutritional Quality
- Track 21-16Veterinary Science