Theme: Determination of various approaches in the field of Genomics, Proteomics and Bioinformatics
Conference Series LLC LTD invites all the participants from all over the world to attend International Conference on Proteomics, Genomics & Bioinformatics during August 22-23, 2022 Singapore City, Singapore. Which includes prompt keynote presentations, Oral talks, Poster presentations, and Exhibitions.
Proteomics 2021 is the premier event that brings together a unique and international mix of experts, researchers and decision makers both from academia and industry across the globe to exchange their knowledge, expertise and research innovations to build a world-class plant genomics conference.
It’s our greatest pleasure to welcome you to the official website of ‘International Conference On Proteomics, Genomics & Bioinformatics’ that aims at bringing together the Professors, Researchers, scientists, Program developers to provide an international forum for the dissemination of original research results, new ideas, and practical development experiences which concentrate on both theory and practices. The conference will be held on August 22-23, 2022 Singapore City, Singapore. The theme of the conference is around, “Determination of various approaches in the field of Proteomics, Genomics & Bioinformatics”.
Why to attend???
With members from around the world focused on learning about Proteomics and its advances; this is your best opportunity to reach the largest assemblage of participants from the Bioinformatics and Genomics community. Conduct presentations, distribute information, meet with current and potential scientists, make a splash with new advancements and developments, and receive name recognition at this 2-day event. World-renowned speakers, the most recent techniques, developments, and the newest updates in Proteomics are hallmarks of this conference.
- Genomics Students, Scientists
- Genomics Researchers
- Bioinformatics Faculty
- Genomics Colleges
- Machine learning in Bioinformatics
- Business Entrepreneurs
- Training Institutes
- Software developing companies
- Manufacturing Bioinformatics tool Companies
Proteomics is the study of proteomes on a vast scale. A proteome is a collection of proteins made by a living creature, system, or biological milieu. We can talk about a species' proteome (for example, Homo sapiens) or an organ's proteome (for example, the liver). The proteome is dynamic, varying from cell to cell and changing throughout time.
Proteomics is used to investigate:
- when and where proteins are expressed
- protein synthesis, degradation, and steady-state abundance rates
- how proteins are modified (for example, phosphorylation and other post-translational modifications (PTMs))
- protein transport between subcellular compartments
- proteins' involvement in metabolic pathways
- what happens when proteins come into contact with one another
Bioinformatics is an interdisciplinary science that develops methods and software tools for analysing biological data, particularly big and complicated data sets. Bioinformatics is an interdisciplinary discipline of research that analyses and interprets biological data by combining biology, computer science, information engineering, mathematics, and statistics. Bioinformatics has been utilised for mathematical and statistical in silico assessments of biological questions.
The structure, function, evolution, mapping, and editing of genomes are all studied in genomics, which is an interdisciplinary subject of biology. A genome is a full set of DNA that includes all of an organism's genes. In contrast to genetics, which focuses on individual genes and their functions in inheritance, genomics tries to characterise and quantify all of an organism's genes, as well as their interrelationships and effects on the organism as a whole. With the help of enzymes and messenger molecules, genes may direct the production of proteins. Proteins, in turn, are responsible for the formation of body structures such as organs and tissues, as well as the management of chemical reactions and the transmission of information between cell.
The linear sequence of amino acids in a peptide or protein is known as primary structure. The main structure of a protein is described from the amino-terminal end to the carboxyl-terminal end, as is customary. Ribosomes are the most frequent organelles in cells that perform protein production.
The goal of structural genomics is to describe the three-dimensional structure of each protein encoded by a genome. By combining experimental and modelling methodologies, this genome-based methodology provides for a high-throughput method of structure determination. The main distinction between structural genomics and standard structural prediction is that structural genomics tries to figure out the structure of every protein encoded by the genome rather than just one.
The science of using biological data to construct algorithms or models in order to understand biological systems and relationships is known as computational biology, which encompasses many areas of bioinformatics. Biologists did not have access to enormous amounts of data until recently. This information is now widely available, particularly in the fields of molecular biology and genomics. Researchers were able to establish analytical methods for analysing biological data, but they were unable to immediately communicate them with their peers.
The computer and mathematical analysis and modelling of complex biological systems is known as systems biology. It is a biology-based interdisciplinary branch of study that focuses on complex interactions within biological systems and employs a holistic approach to biological research (holism rather than reductionism).
The use of machine learning techniques to bioinformatics, such as genomics, proteomics, microarrays, systems biology, evolution, and text mining, is known as machine learning in bioinformatics. High-performance computing allows important breakthroughs in bioinformatics.
Prior to the invention of machine learning algorithms, bioinformatics programmes had to be explicitly designed by hand, which was incredibly difficult for tasks like protein structure.
Protein sequencing is the technique of determining the amino acid sequence of a protein or peptide in its entirety or in part. This could be used to identify the protein or define the post-translational alterations it has undergone. Partially sequencing a protein usually offers enough information (one or more sequence tags) to identify it using databases of protein sequences acquired via conceptual gene translation. Mass spectrometry and Edman degradation with a protein sequenator are the two most common direct methods of protein sequencing (sequencer). Although mass spectrometry is now the most extensively used approach for protein sequencing and identification, Edman degradation is still a useful tool for determining a protein's N-terminus.
Through multiple controlled processes, protein-coding genes are transcribed to pre messenger ribonucleic acid (pre-mRNA), then processed to messenger ribonucleic acid (mRNA), and finally translated into protein. Proteins can be further processed and changed post translationally, and they can form complexes with one another. The transcriptome is the whole set of coding and noncoding RNA molecules, while the proteome is the complete set of proteins expressed in an organelle, cell type, or tissue under specified conditions.
The study of the role of the genome in medication response is known as pharmacogenomics. The combination of pharmacology and genetics is reflected in the term (pharmaco- + genomics). Pharmacogenomics studies how a person's genetic composition influences their pharmacological reaction. It examines the impact of acquired and inherited genetic variation on drug response in patients by linking gene expression or single-nucleotide polymorphisms to pharmacokinetics (drug absorption, distribution, metabolism, and elimination) and pharmacodynamics (effects mediated by a drug's biological targets).
Immunogenetics, sometimes known as immunogenetics, is a branch of medical genetics that studies the link between genetics and the immune system. Autoimmune disorders, such as type 1 diabetes, are complicated hereditary features caused by immune system malfunctions.The word immunogenetics refers to all processes in an organism that are governed and impacted by the organism's genes on the one hand, and are significant in terms of the organism's immunological defence reactions on the other.
Epigenomics is the study of the epigenome, or the whole set of epigenetic alterations on a cell's genetic material. The field is comparable to genomics and proteomics, which examine a cell's genome and proteome. Reversible alterations to a cell's DNA or histones that affect gene expression without changing the DNA sequence are known as epigenetic modifications. Epigenomic maintenance is an ongoing process that contributes to the stability of eukaryotic genomes by participating in critical biological systems such as DNA repair.
Human gene therapy aims to alter the biological characteristics of living cells or adjust the expression of a gene for therapeutic purposes.
Gene therapy is a strategy for treating or curing disease by altering a person's DNA. Gene treatments can function in a variety of ways:
- Putting a healthy copy of a disease-causing gene in place of the disease-causing gene
- Inactivating a disease-causing gene that isn't working as it should
- To assist treat an illness, a new or modified gene is introduced into the body.
Proteomics has its origins in two-dimensional gel electrophoresis (2-DE), a technique developed more than twenty years ago. 2-DE has a high-resolution capacity, and was initially used primarily for separating and characterizing proteins in complex mixtures. 2-DE is still a useful method for identifying proteins, but it is now frequently used in conjunction with mass spectrometry (MS), a technique that has evolved significantly in recent years.
Because of the inherent complexity of signalling networks, as well as the quantity and variety of quantitative data, cell signalling systems and networks can be examined using system biology. Through cell signalling, a vast spectrum of stimulus-response behaviours is observed in cells, which is important to all of Biology. The primary function of cell signalling systems is to take information from the environment and generate an output response based on that input.
Quantitative Proteomics is a scientific technique for determining the amount of protein in a sample, which may then be used to compare diseased and healthy people. It also provides information on sample differences. Isotopic labelling of proteins or peptides can be differentiated using mass spectrometry. Other life science domains such as genomics, kinemics, transcriptomics, and metabolomics are increasingly using broad-scope analysis, and the quantitative Proteomic approach is in line with that. Quantitative Dot Blot (QDB) Electrospray Ionization 2DE-DIGE Mass Spectroscopy Optimizing LC-Ms/MS for Quantitative Proteomics.
Spectrophotometric methods can be used to determine the concentration of a specific protein in a sample. A spectrophotometer may be used to measure the OD at 280 nm of a protein, which can then be used in conjunction with a standard curve assay to quantify the content of Tryptophan, Tyrosine, and Phenylalanine.
Proteomics has arrived at a critical juncture in cardiovascular research. Analyses of cardiac and vascular illness at the organ, subcellular, and molecular levels have shown dynamic, complicated, and nuanced intracellular mechanisms. Proteomic analysis' power and flexibility, which make protein separation, identification, and characterisation easier, should speed up our understanding of these processes at the protein level. Proteomics, when used correctly, gives researchers with cellular protein "inventories" at precise points in time, making it excellent for recording protein alteration as a result of a specific disease, condition, or treatment.
Proteomics technologies are employed in the discovery of novel therapeutic medicines and for early identification and diagnosis of malignancies. With advancements in the science of proteomics and the use of mass spectrometry, breast cancer observation, prognosis, diagnosis, and treatment are now possible.
With the development of proteomics technology, researchers have been able to distinguish between disease and disease-free states linked with breast cancer. Proteins expressed or discovered in serum, plasma, and tumour cells employing novel approaches provide for a better understanding of cancer heterogeneity. Proteomics in Breast Cancer Proteomics in Skin Cancer Proteomics in Lung Cancer Proteomics in Ovarian Cancer Proteomics in Colorectal Cancer.
Urine metabolomics emerged in response to a specific disease or therapeutic intervention for the discovery of non-invasive biomarkers that can detect small metabolic abnormalities. Urine is distinguished from other biofluids by its ease of collection, abundance of metabolites, and capacity to reflect abnormalities in all metabolic pathways within the body. To quench any biogenic and/or non-biogenic chemical processes, urine samples for metabolomic analysis must be quickly refrigerated.
Metabolomics is used to investigate a variety of human diseases, improve their assurance and repugnance, and design better accommodating systems. Novel biomarkers and mechanisms of cardiovascular disease danger have been identified using metabolomic profiling. Sustenance and Metabolism Center and Center for Human Genetics at Duke University where the examination is proceeding with National Institutes of Health grants . Metabolomics can give certain inclinations in regard to other "omics" progressions (genomics, transcriptomics, proteomics) in diabetes look into. CEDAM (Center for Endocrinology, Diabetes and Metabolism) investigation is centered around a seat to-bedside approach, taking examination through from key science divulgence to clinical application. This is energized by recurring pattern MRC Experimental Medicine and Biomarker Grants and enhanced by the close-by region of lab workplaces.
Novel indicators and components of cardiovascular infection risk have been identified using metabolomic profiling. Metabolomics requirements for bioinformatics include information and data management, raw scientific data preparation, metabolomics measures and metaphysics, factual examination and data mining, data incorporation, and numerical demonstrating of metabolic systems within a framework of frameworks science.
Metabolomics, or the post-genomic investigation of the particles and strategies that make up the absorption framework, looks to be a potentially revolutionary new way of looking at science and disease. Accuracy Medicine is a method of locating and manufacturing medications and antibodies that provides patients with unparalleled outcomes by combining clinical and sub-nuclear data to determine the natural occurrence of contamination. Pharmacometabolomics complements and educates pharmacogenomics, and the two combined provide the foundation for Quantitative and Systems Pharmacology.
Pharmacometabolomics is a field in which massive biochemical data capturing the effects of the genome, gut microbiota, and condition exposures is being used to find data on metabotypes and treatment outcomes, and metabolic markings are being developed as new potential biomarkers. The Precision Medicine Initiative gives the National Cancer Institute $70 million to research tumour genomic drivers, identify those goals, and develop new treatments. Exactness Medicine refers to tailoring restorative treatment to each patient's unique characteristics. It doesn't necessarily imply the creation of one-of-a-kind medications or therapeutic devices for each patient, but rather the ability to divide people into subpopulations that differ in their susceptibility to a specific illness, in the science or potential visualisation of the ailments they may cause, or in their response to a specific treatment.
Instead of treating patients with a "one size fits all" approach, customised drug programmes allow doctors to adapt medications to achieve the greatest results for individual patients. Customized prescription, additionally named exactness pharmaceutical, is a medicinal methodology that isolates patients into various gatherings—with restorative choices, practices, mediations as well as items being custom-made to the individual patient in view of their anticipated reaction or danger of malady.
Metabolomics is a new science that combines sophisticated analytical techniques for identifying and quantifying cellular metabolites with statistical and multivariant methods for information extraction and data interpretation. The study of tiny metabolites is known as metabolomics. Bioinformatics, proteomics, systems biology, analytical techniques such as NMR, GC-MS, LC-MS, and CE-MS, Lipidomic, Metabolic Modelling, Metabolic Profiling, Clinical Metabolomics, Translational sciences, Mass spectrometry, Metabolomics Syndrome, HPLC and CE based metabolomics, and more are all covered at the Metabolomics Conference. Metabolomics, the new "omics," is a fast-growing area that combines genomes, transcriptomics, and proteomics to provide an integrative framework for drug discovery and development. In spite of the fact that metabolomics is still at an early evolutionary stage it is conjecture that throughout the following decade the biopharma business will apply this innovation all the more generally in drug development and information.
'The Future of Metabolomics' provides a thorough overview of how metabolomics can be used to improve drug discovery, preclinical development, and clinical trials. The application of metabolomics in maximising and maintaining post-marketing revenues, as well as in the development of clinical diagnostics, is also highlighted in the report.
Importance & Scope:
Metabolomics is now widely employed for biomarker and drug discovery in the pharmaceutical and biotechnology industries; the pharmaceutical and biotechnology industries are predicted to grow rapidly in the next years, boosting the market's growth.
The global proteomics market was valued at $21,122.32 million in 2019, and is projected to reach $49,978.8 million by 2027 at a CAGR of 12.2% from 2020 to 2027.
- Protein Structure
- Structural Genomics
- Computational Biology
- System Biology
- Machine learning in Bioinformatics
- Protein Sequencing
- Integrating Transcriptomics & Proteomics
- Immunogenetics and Immunology
- Gene Therapy
- Proteomics in Biomedical Applications
- Protein Interactions in Biology
- Quantitative Proteomics
- Cardiovascular Proteomics
- Cancer Proteome and Biomarkers
- Urine Metabolomics
- Metabolic Syndrome
- Metabolomics in Precision Medicine
- Proteomics and its Medicinal Research
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