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13th International Conference on Proteomics, Genomics and Bioinformatics, will be organized around the theme “”

Proteomics 2020 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in Proteomics 2020

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Protein structure is the three-dimensional arrangement of atoms in a protein molecule. Proteins are polymers specifically polypeptides formed from sequences of amino acids, the monomers of the polymer. A single amino acid monomer may also be called a residue indicating a repeating unit of a polymer. Proteins form by amino acids undergoing condensation reactions, in which the amino acids lose one water molecule per reaction in order to attach to one another with a peptide bond. By convention, a chain of 30 amino acids is often identified as a peptide, rather than a protein. This is the topic of the scientific field of structural biology, which employs techniques such as X-ray crystallography, NMR spectroscopy, and dual polarisation interferometry to determine the structure of proteins.

 

 

  • Track 1-1Structure classification
  • Track 1-2Computational prediction of protein structure
  • Track 1-3 Protein structure databases
  • Track 1-4 Protein Sequence Analysis
  • Track 1-5 Protein structure determination
  • Track 1-6Protein stability
  • Track 1-7 Protein folding
  • Track 1-8 Protein dynamics
  • Track 1-9 Levels of protein structure

 Structural genomics seeks to depict the 3-dimensional structure of each protein encoded by a given genome. This genome-based approach takes into consideration a high-throughput technique for structure assurance by a combination of experimental and modelling approaches. The important contrast between structural genomics and traditional structure prediction is that structural genomics endeavors to decide the structure of each protein encoded by the genome, instead of concentrating on one specific protein. With full-genome arrangements accessible, structure prediction should be possible all the more rapidly through a combination of experimental and modelling approaches, particularly in light of the fact that the accessibility of expansive number of sequenced genomes and beforehand explained protein structures enables researchers to display protein structure on the structures of previously solved homologs

 

 

Systems biology is the computational and mathematical modelling of complex biological systems. An emerging engineering approach applied to biological scientific research, systems biology is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach (holism instead of the more traditional reductionism) to biological research. Computational biology involves the development and application of data-analytical and theoretical methods, mathematical modelling and computational simulation techniques to the study of biological, behavioural, and social systems. The field is broadly defined and includes foundations in computer science, applied mathematics, animation, statistics, biochemistry, chemistry, biophysics, molecular biology, genetics, homology, genomics, ecology, evolution, anatomy, neuroscience, and visualization.

 

 

 

  • Track 3-1Application of LC-MS in plant metabolomics
  • Track 3-2Xenobiotics

Electrospray ionization (ESI) is a technique used in mass spectrometry to produce ions using an electrospray in which a high voltage is applied to a liquid to create an aerosol. Liquid chromatography is an analytical chemistry technique that combines the physical separation capabilities of liquid chromatography (or HPLC) with the mass analysis capabilities of mass spectrometry (MS). Multidimensional Protein Identification Technology (MudPIT) is used to analyze the proteomes of organisms. Protein purification is a series of processes intended to isolate one or a few proteins from a complex mixture, usually cells, tissues or whole organisms. Imaging mass spectrometry (IMS) using matrix-assisted laser desorption ionization (MALDI) is a new and effective tool for molecular studies of complex biological samples such as tissue sections.

  • Track 4-1Protein identification
  • Track 4-2De novo (peptide) sequencing
  • Track 4-3 Protein quantitation
  • Track 4-4 Protein structure determination
  • Track 4-5 Proteogenomics

Biomedical research is in general simply known as medical research. It is the basic research, applied research, or translational research conducted to aid and supports the development of knowledge in the field of medicine. An important kind of medical research is clinical research, which is distinguished by the involvement of patients. Other kinds of medical research include pre-clinical research, for example on animals, and basic medical research, for example in genetics.

  • Track 5-1Critical use of clinical information
  • Track 5-2 Translational medicine
  • Track 5-3Conceptual frameworks from top-down
  • Track 5-4 Clinical product development
  • Track 5-5Identification by mass spectrometry

Molecular Interactions are attractive or repulsive forces between molecules and between non-bonded atoms. Molecular interactions are important in diverse fields of protein folding, drug design, material science, sensors, nanotechnology, separations, and origin of life. Molecular interactions are also known as non-covalent interactions or intermolecular interactions. Molecular interactions are not bonds.

 

  • Track 6-1Determining amino acid composition
  • Track 6-2C-terminal amino acid analysis
  • Track 6-3 Edman degradation
  • Track 6-4 N-terminal amino acid analysis
  • Track 6-5Identification by mass spectrometry
  • Track 6-6 Predicting from DNA/RNA sequences

The proteome of each living cell is dynamic, altering in response to the individual cell's metabolic state and reception of intracellular and extracellular signal molecules, and many of the proteins which are expressed will be post-translationally altered. Thus if the purpose of the proteome analysis is to aid the understanding of protein function and interaction, then it is the identification of the proteins in their final state which is required: for this mass spectrometric identification of individual proteins, indicating site and nature of modifications, is essential.

 

 

 

  • Track 7-1Gel based proteomics
  • Track 7-2Shotgun proteomics
  • Track 7-3 Salinity Tolerance
  • Track 7-4 Photosynthesis
  • Track 7-5Late-Embryogenesis Abundant (LEA) Proteins
  • Track 7-6 Oxidative Stress/Antioxidants

Machine learning is closely related to computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning.

 

  • Track 8-1 Microarrays
  • Track 8-2Stroke Diagnosis
  • Track 8-3 Text mining

Immunogenetics has a critical part in the examination of single characteristics of genes and their part in the manner in which traits or conditions are passed beginning with one time then onto the following. The examination of the atomic and cell parts that include the protected structure, including their ability and association turns into the central craft of immunology. Immune system infections, for example, type 1 diabetes, are complex genetic characteristics which result from defects in the immune system Distinguishing proof of qualities characterizing the insusceptible deformities may recognize new target qualities for remedial methodologies. Then again; genetic assortments can in like manner describe the immunological pathway provoking illness.

  • Track 9-1 Granulocyte Immunology
  • Track 9-2Genes and Immunity
  • Track 9-3Vasculitis and Autoimmune Disease
  • Track 9-4Genetics of Allo Antigens
  • Track 9-5Genetic control of immune cell activation
  • Track 9-6 Chronic Inflammation
  • Track 9-7 Immunogenicity
  • Track 9-8 Image processing
  • Track 9-9Diagnostics and disease profiling

Current transcriptomic profiling techniques include DNA microarray, cDNA amplified fragment length polymorphism (cDNA-AFLP), expressed sequence tag (EST) sequencing, serial analysis of gene expression (SAGE), massive parallel signature sequencing (MPSS), RNA-seq etc. The most recent technology for transcriptomic profiling is RNA-Seq which is considered as a revolutionary tool for this purpose. Eukaryotic transcriptomic profiles are primarily analyzed with this technique and it has been already applied for transcriptomic analysis of several organisms including Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, mouse and a human cell.

  • Track 10-1Isolation of RNA
  • Track 10-2Expressed sequence tags
  • Track 10-3Human and pathogen transcriptomes
  • Track 10-4 Diagnostics and disease profiling
  • Track 10-5Image processing

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 proteomeof a cell.  Epigenetic modifications are reversible modifications on a cell’s DNA or histones that affect gene expression without altering the DNA sequence. Epigenetics are stable heritable traits (or "phenotypes") that cannot be explained by changes in DNA sequence. Epigenetics often refers to changes in a chromosome that affect gene activity and expression but can also be used to describe any heritable phenotypic change that doesn't derive from a modification of the genome, such as prions. Such effects on cellular and physiological phenotypic traits may result from external or environmental factors, or be part of the normal developmental program. The standard definition of epigenetic requires these alterations to be heritable, either in the progeny of cells or of organisms.

  • Track 11-1 DNA methylation
  • Track 11-2 Histone modification
  • Track 11-3 ChIP-Chip and ChIP-Seq
  • Track 11-4 Genome wide approaches
  • Track 11-5 Direct detection

Pharmacogenomics is the study of the role of the genome in drug response. Its name (pharmacy + genomics) reflects it’s 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).

 

  • Track 12-1Drug-metabolizing enzymes
  • Track 12-2Predictive prescribing
  • Track 12-3Clinical implementation
  • Track 12-4Polypharmacy
  • Track 12-5Drug labeling

\r\n The high demand for low-cost sequencing has driven the development of high-throughput sequencing, which also goes by the term next-generation sequencing (NGS). Thousands or millions of sequences are concurrently produced in a single next-generation sequencing process. Next-generation sequencing has become a commodity. With the commercialization of various affordable desktop sequencers, NGS has become within the reach of traditional wet-lab biologists. As seen in recent years, the genome-wide scale computational analysis is increasingly being used as a backbone to foster novel discovery in biomedical research.

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  • Track 13-1Illumina (Solexa) sequencing
  • Track 13-2Roche 454 sequencing
  • Track 13-3Ion Torrent: Proton / PGM sequencing

Genetic Counselling is the procedure by which the patients or relatives at risk of an acquired disorder (or might convey a kid at risk) are advised with the outcomes and nature of the disorder, the likelihood of creating or transmitting it, and the choices open to them in management and family planning. This mind boggling procedure can be isolated into indicative (the real estimation of hazard) and supportive aspects.

 

 

  • Track 14-1Gene Polymorphism
  • Track 14-2Regenerative Medicine
  • Track 14-3 Gene Editing and CRISPR Based Technologies
  • Track 14-4Viral Gene Therapy
  • Track 14-5Ethical issues Related to Gene Therapy
  • Track 14-6Advanced Therapy production

The nanomaterial has admired qualities to equilibrate boss components which pick biocatalysts proficiency, including a particular surface territory, mass exchange confirmation and productive compound stacking. This review displays the current circumstance and frameworks in compound immobilization. A couple of methods are used which are capable to join proteins/synthetic substances with nanoparticles. Immobilization process is to overhaul the operational execution of an impetus for mechanical applications. So far different cross sections have been portrayed in the written work to improve the execution of the immobilized proteins. With the incident to nanotechnology, the nanomaterial due to their one of a kind physical - substance properties constitute novel and charming frameworks for compound immobilization.

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  • Track 15-1Enzyme nanoparticles
  • Track 15-2DNA nanotechnology
  • Track 15-3Nanotechnology products
  • Track 15-4DNA microarray
  • Track 15-5Nanopolymers
  • Track 15-6Nanotechnology in targeted drug delivery
  • Track 15-7Immobilization using nanoparticles
  • Track 15-8Nanotechnology enabled enzyme activity

Proteins are a primary constituent of living things and one of the chief classes of molecules studied in biochemistry. Proteins provide most of the molecular machinery of cells. Many are enzymes or subunits of enzymes. Other proteins play structural or mechanical roles, such as those that form the struts and joints of the cytoskeleton. Each protein is linear polymers built of amino acids.

 

 Computational Biology involves the improvement and application of statistics-analytical and theoretical methods, mathematical modelling and computational simulation techniques to the study of organic, behavioural, and social structures. The field is widely described and includes foundations in biology, applied mathematics, data, biochemistry, chemistry, biophysics, molecular biology, genetics, genomics, pc technological know-how and evolution.Computational biology is different from biological computing, that's a subfield of computer technology and computer engineering using bioengineering and biology to build computer systems but is just like bioinformatics, that is an interdisciplinary science using computer systems to store and system biology information.

 

  • Track 17-1Data mining and Machine Learning
  • Track 17-2 Computational anatomy
  • Track 17-3Artificial Intelligence
  • Track 17-4 Computational biomodeling

Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyse and interpret biological data.

  • Track 18-1Protein sequence databases and their use
  • Track 18-2Protein sequence data in UniProt
  • Track 18-3Protein sequence data in UniProt
  • Track 18-4Post-translational modifications
  • Track 18-5Standardisation of proteomics data
  • Track 18-6 MS proteomics repositories and the Proteomexchange consortium
  • Track 18-7 PRIDE and PRIDE-related tools
  • Track 18-8 Proteogenomics

Genomics refers to the study of the genome in contrast genetics which refers to the study of genes and their roles in inheritance. Genomics can be considered a discipline in genetics. It applies recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble and analyse the function and structure of genomes (the complete set of DNA within a single cell of an organism). Advances in genomics have triggered a revolution in discovery-based research to understand even the most complex biological systems such as the brain. The field includes efforts to determine the entire of DNA sequence organisms and fine-scale genetic mapping.

 

  • Track 19-1Functional genomics
  • Track 19-2Structural genomics
  • Track 19-3Epigenomics
  • Track 19-4Metagenomics
  • Track 19-5Model systems