Applications of genomics and proteomics ppt
genomics and proteomics ppt
in the field of health genomics and proteomics ppt
oncology ppt
biomedical application of genomics and proteomics ppt
agriculture application of genomics and proteomics ppt
proteomics in agriculture ppt
diagnosis of infectious disease ppt
personalized medicine ppt
What is Genome,Genome mapping,types of Genome mapping,linkage or genetic mapping,Physical mapping,Somatic cell hybridization
Radiation hybridization ,Fish( =fluorescence in - situ hybridization),Types of probes for FISH,applications,Molecular markers,Rflp(= Restriction fragment length polymorphism),RFLPs may have the following Applications;Advantages of rflp,disAdvantages of rflp, Rapd(=Random amplification of polymorphic DNA),Process of rapd, Difference between rflp &rapd
The study of nucleic acids began with the discovery of DNA, progressed to the study of genes and small fragments, and has now exploded to the field of genomics. Genomics is the study of entire genomes, including the complete set of genes, their nucleotide sequence and organization, and their interactions within a species and with other species. The advances in genomics have been made possible by DNA sequencing technology. [Source: https://opentextbc.ca/biology/chapter/10-3-genomics-and-proteomics/]
What is Genome,Genome mapping,types of Genome mapping,linkage or genetic mapping,Physical mapping,Somatic cell hybridization
Radiation hybridization ,Fish( =fluorescence in - situ hybridization),Types of probes for FISH,applications,Molecular markers,Rflp(= Restriction fragment length polymorphism),RFLPs may have the following Applications;Advantages of rflp,disAdvantages of rflp, Rapd(=Random amplification of polymorphic DNA),Process of rapd, Difference between rflp &rapd
The study of nucleic acids began with the discovery of DNA, progressed to the study of genes and small fragments, and has now exploded to the field of genomics. Genomics is the study of entire genomes, including the complete set of genes, their nucleotide sequence and organization, and their interactions within a species and with other species. The advances in genomics have been made possible by DNA sequencing technology. [Source: https://opentextbc.ca/biology/chapter/10-3-genomics-and-proteomics/]
Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...Prasenjit Mitra
This set of slides gives an overview regarding the various omics technologies available and how they can be used for improvement in clinical setting or research
Introduction
Transcriptome analysis
Goal of functional genomics
Why we need functional genomics
Technique
1. At DNA level
2.At RNA level
3. At protein level
4. loss of function
5. functional genomic and bioinformatics
Application
Latest research and reviews
Websites of functional genomics
Conclusions
Reference
STS stands for sequence tagged site which is short DNA sequence, generally between 100 and 500 bp in length, that is easily recognizable and occurs only once in the chromosome or genome being studied.
Introduction to Applications of Proteomics Science,
Proteomics- Techniques, Applications of proteomics
Presented by
A. Harsha Vardhan Naidu
Department of Pharmacology
Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...Prasenjit Mitra
This set of slides gives an overview regarding the various omics technologies available and how they can be used for improvement in clinical setting or research
Introduction
Transcriptome analysis
Goal of functional genomics
Why we need functional genomics
Technique
1. At DNA level
2.At RNA level
3. At protein level
4. loss of function
5. functional genomic and bioinformatics
Application
Latest research and reviews
Websites of functional genomics
Conclusions
Reference
STS stands for sequence tagged site which is short DNA sequence, generally between 100 and 500 bp in length, that is easily recognizable and occurs only once in the chromosome or genome being studied.
Introduction to Applications of Proteomics Science,
Proteomics- Techniques, Applications of proteomics
Presented by
A. Harsha Vardhan Naidu
Department of Pharmacology
Pharmacogenomics is new science about how the systematic identification of all the human genes, their products, interindividual variation, intraindividual variation in expression and function over time affects drug response/metabolism, etc.
Improve drug safety and reduce ADRs. The presentation explained the advantages of pharmacogenomics. Explained Goals of Pharmacogen(etics)omics.
Application of Proteomic Science and Immunotherapeutics.pptxShraddhaRaut43
This presentation will give you overall information about the application in Proteomic Science and Immunotherapeutics. It covers Proteomics, Genomics, Metabolomics, Functionomics, Nutrigenomics and Types of Immunotherapeutics, Humanized Antibody Therapy, Immunotherapeutics in Clinical Practice.
Gene therapy is emerging branch of healthcare, we can see that with the possible development it has potential to treat multiple genetic as well as other conditions and disease
hope young scholar can find this presentation useful and i am open to any suggestions
iCAAD London 2019 - Antonio Metastasio - PERSONALISED MEDICINE IN THE TREATM...iCAADEvents
Personalised medicine is considered the next frontier of health care. The role of genetic testing in psychiatry and in addictions medicine, however, has been recently critically reviewed. Are genetic tests helpful in assessing and managing these conditions?
Nanobiotechnology
process of self assembly and self organization
organization of bacterial s-layer
self organization of virus
self organization of phospholipid membrane
carbon nanotubes key building block for future nanotechnological application
graphene
the inorganic nanomaterial
quantum dots
introduction to Nanobiotechnology
what is nanotechnology
bionanotechnology
classical biotechnology industrial production using biological system
modern biotechnology from industrial processes to noval therapeutics
modern biotechnology immunological enzymatic and neucleic acid based technology
Dna based technology
self assembly and supramolecular chemistry
formation of ordered structure at nano scale
definition of Mitochondrial gene expression
structure of mitochondrial dna
requirment for transcriptional activity
transcription elongation and termination
post transcriptional modification
translation of mitochondrial transcripts
Dna methylation ppt
definition of Dna methylation ppt
discovery of Dna methylation ppt
types of Dna methylation ppt
history of Dna methylation ppt
process of Dna methylation ppt
mechanism of Dna methylation ppt
methylation in cancer
cytosine methylation
genomic imprinting
Control of microorganism ppt
physical method Control of microbes
chemical method Control of microbes
types of Control of microbes
pasteurization Control of microbes
sterilization
disinfection
sanitization
Carbon cycle ppt
definition of Carbon cycle ppt
types of Carbon cycle ppt
discovery of Carbon cycle ppt
importance of Carbon cycle ppt
steps of Carbon cycle ppt
carbon cycle in water
harmful effect of Carbon cycle ppt
Absorption of proteins ppt
composition of protein ppt
digestion of protein ppt
Absorption of protein ppt
absorption of amino acid ppt
function of protein ppt
amino acid ppt
role enzyme ppt
Digestion and absorption of lipids ppt
what is lipid ppt
digestion of lipid ppt
phase of digestion and absorption ppt
phases of lipids ppt
digestion in mouth and stomach ppt
digestion in small intestine ppt
secretion of lipids ppt
enzyme involved in lipid digestion ppt
transportation phases of lipids ppt
principles of lipid digestion ppt
Action on xenobiotics ppt
biodegradation enhance biodegradation
definition of xenobiotic compounds
hazards of xenobiotics
biodegradation ppt
biodegradation of xenobiotics
discovery of xenobiotics
process of xenobiotics
aerobic biodegradation and much more
Control of gene expression ppt
definition of gene expression
inducible gene expression
repressible gene expression
control of gene expression in eukaryotics .all the in information about this topic is include .
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
2. INTRODUCTION
GENOMICS:
• Genomics is the field of genetics that attempts to
understand the content, organization, function, and
evolution of genetic information contained in whole
genome.
• PROTEOMICS:
• The study of the structure and function of proteins,
including the way they work and interact with each other
inside the cells.
4. IN FIELD OF HEALTH
• ONCOLOGY
• Study of tumor cells is known as oncology.
• Proteomic technologies have been used for
the study of biology of cancer of various
organs .
5. Example:
Blood proteins to detect brain tumor:
• Glioblastoma multiforme (GBM) is a fast
growing , high grade brain tumor.
.
• Glioma brain tumors are caused due to an
uncontrolled increase in certain cells known
as glial cells.
6. CONTINUED…
• It is possible to detect GBM by analysis of proteins
in the blood serum.
• Using proteins to detect diseases is part of
proteomics.
• Researches found almost 55 differently expressed
proteins in GBM patients. Of these, 4 proteins are
more important because of their contribution to
tumor gr0wth.
7. Bio-medical applications
• The study of interactions between microbial pathogens
and their hosts is called infect omics.
• It is very interesting area in proteomics. It deals with the
fundamentals of the infections origin and their effect on
organs.
• The main aim of this research is to prevent or cure
disease at starting level.
8. Agricultural applications
• Genomics can reduce the trials and failures
involved in scientific research , which could
improve the quality and quantity of crop yields
in agriculture.
• Linking traits to genes or gene signatures helps
to improve crop breeding to generate hybrids
with the most desirable qualities.
9. Cont…..
• Genomics can improve the quality and quantity of
agricultural production.
• For example, scientist could use desirable traits to
create a useful product or enhance an existing
product, such making a drought-sensitive crop more
tolerant of the dry season.
10. Proteomics in agriculture
• Proteomics is used to know plant-insect interactions
that help identify candidate genes involved in the
defensive response of plants to herbivore.
11. FORENSIC ANALYSIS
• Information and clues obtained from DNA samples
found at crime sites have been used as evidence in
court cases, and genetic markers have been used in
forensic analysis.
12. Diagnosis of infectious diseases
• Sequencing the genomes of microorganisms which cause human
infection can identify the exact organism causing symptoms, help
to trace the cause of infectious outbreaks, and give information
as to which antibiotics are most likely to be effective in treatment.
13. Genomics in microbial vaccine
development
• Vaccination is one of the most effective tools for the
prevention of infectious diseases.
• The availability of complete genome sequences,
together with the progression of high-throughput
technologies such as functional and structural
genomics, has led to a new paradigm in vaccine
development.
14. Personalized medicines
• As the exact DNA sequence of the genome of each
human is unique to them, we will all have unique
disease susceptibilities and treatment responses.
• Personalised medicine describes the use of our
genetic information to tailor health care intervention
to our own individual need.
15. Pharmacogenetics and targeted therapy
• Genetics information may be used to predict whether a person
will respond to a particular drug, how well they will respond to
that drug and whether they are likely to get any side effects from
the use of a specific drug.
• In some cases, such as cancer, the genetic drivers of disease and
then give drugs which specifically target that pathway, this is
known as targeted therapy.
16. Gene therapy
• Gene therapy involves the administration of DNA or
RNA in order to correct a genetic abnormality , or
modify the expression of genes.
• Genome editing:
• Genome editing uses molecular techniques to modify the
genome –genome editing can add in, cut out, or replace
sections of the DNA sequence.
