Proteomics ppt pdf

Single On Purpose: Redefine Everything. Find Yourself First. John Kim. Gundry, MD. Permission to Dream Chris Gardner. So you do not need to waste the time on rewritings. Normig de Salas , Docente. Escuela de Medicina. Deeksha Kumari. Riya Raghav. Ayesha Khan. Kishore Ravi. Thomas College Ruabandha Bhilai at St. Thomas College Ruabandha Bhilai. Saood Malik. Himanshi Soni. Show More. Views Total views. Actions Shares. No notes for slide. Proteomics 1. Proteomics Protein identification using mass spectrometry www.

Principles Of Proteomics. Wikimedia Foundation, Inc. Why proteomics? Quantification strategies Domon B, Aebersold R.

Top down or bottom up? Proteomic strategies Domon B, Aebersold R. Annu Rev Biomed Eng. How does proteomics help to Identify genes involved in important diseases? An example in Human Genetics. Genomics Databases contains the information to identify the candidate genes involved in human diseases More than one candidate gene. Analysis of Genomics, Microarrays gene expression and proteomics data contained in public databases can identify the gene involved in a particular human disease 2D gel.

The first sequence in of a viral genome of base pairs highlights the unique insights that can be obtained into gene structure, function and genome organization when a vast amount of genetic information is generated by sequencing. In Gilbert and others launched the genomic area by improving the existing DNA sequencing technology towards intensive automation In full automation were obtained for an integrated machine that could produce factory-like DNA sequences The latest sequencing machines can decode 1.

Started officially in , but followed discussion about the DNA sequencing technologies started in Objective was to obtained the genome in 15 years In two versions of the draft constituted of 3 billions of bases were available by the biotech company celera and the human genome sequencing consortium. In the process tools and methodology were obtained to sequence other genomes genome to date. The entire RNA and protein output encoded by the genome can be made available in public databases to facilitate hypothesis driven science and global analysis.

The HGP pushed the development of highthroughput tools for sequencing which are currently driving the creation of other methodologies related to gene expression such as micorarray and proteomics such as mass spectrometry for the analysis of other related biological information, such as RNA, proteins and molecular interactions.

Digital Nature of Biological Information The value of genome sequence is that we can study a biological system with a precise digital core of information. The challenge is to find which information is encoded within the digital code. The genome encode the protein and RNA machine of life and the regulatory network that specify how these genes are expressed in time, space and amplitude. The evolution of the regulatory network and not the genes themselves play a critical role in making organism different from one another.

Digital Nature of Biological Information The digital information operates in three diverse time spans: Evolution: tens to million years Development: hours to ten of years Physiology: milliseconds to weeks Regulatory network are composed of two components: Transcription factors and their DNA sites representing control regions of genes. Control regions serves as information processor to control the concentration of different transcription factors into signals that mediate gene expression to carry out developmental or physiological functions.

Digital Nature of Biological Information Biology has evolved several different types of information into a hierarchical structure. First a regulatory hierarchy of gene network defining the relationship of a set of transcription factors and regulatory elements controlling particular aspect of development Second an evolutionary hierarchy defining an ordered sets of relationship arising from the duplication of genes. For example the Duplication of a gene to generate a gene family.

Third Molecular machine may be assembled into structural hierarchies by an ordered assembly process. The ribosome is assembled by more than 50 different proteins Finally informational theory describe the flow of a gene to environment according to the following scheme:. Digital Nature of Biological Information Informational theory describe the flow of a gene to environment according to the following scheme:. Systems approaches to biology Human starts as a single cell get fertilized and develop into an adult made of trillion of cells and thousands of cell types.

During this process two type of digital information are used. Information can be predetermined deterministic or random stochastics Example: Antibody diversity is generated by stochastic signal following the exposure to an Antigen. Expansion in number of B cells secreting antibody is directly related to the affinity of the antigen to the antibody.

Higher the affinity of the antibody to the antigen is higher the cells producing this antibody will be selected for survival and proliferation. What is Proteomics? Why Expressional Proteomics? Concerned with the display, measurement and analysis of global changes in protein expression Monitors global changes arising from application of drugs, pathogens or toxins Monitors changes arising from developmental, environmental or disease perturbations Applications in medical diagnostics and 21 therapeutic drug monitoring.

Why Functional Proteomics? Concerned with the identification and classification of protein functions, activities locations and interactions at a global level To compare organisms at a global level so as to extract phylogenetic information To understand the network of interactions that take place in a cell at a molecular level To predict the phenotypic response of a cell or organism to perturbations or mutations.

Structural Proteomics High Throughput protein structure determination via Xray crystallography, NMR spectroscopy or comparative molecular modeling Structural Proteomics: The Motivation 0 Protein Structure Initiative Organize all known protein sequences into sequence families Select family representatives as targets.

Solve the 3D structures of these targets by X-ray or NMR Build models for the remaining proteins via comparative homology modeling Protein Structure Initiative Organize and recruit interested structural biologists and structure biology centres from around the world. Coordinate target selection Develop new kinds of high throughput techniques Solve, solve, solve, solve. How to compare one proteome with another? How to extract functional motifs from sequence data? How to predict phenotype from proteotype?

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MS based proeomics. Ravi Kumar Follow.