Bioinformatics is the interdisciplinary field that combines biology, computer science, and information technology to analyze and interpret biological data. It involves developing algorithms and software to solve complex biological problems, like analyzing DNA and protein sequences. Key areas of bioinformatics include computational biology, medical informatics, cheminformatics, genomics, proteomics, pharmacogenomics, and pharmacogenetics. The field emerged as new technologies enabled the digitization and analysis of genetic and molecular data on a large scale.
The document summarizes the Human Genome Project which aimed to sequence and map the entire human genome. The project was launched in 1990 and completed in 2003. Its goals were to identify all human genes, determine the sequences of DNA base pairs, make the data widely available, and address ethical issues. The sequencing process involved isolating DNA, cloning fragments, and using shotgun sequencing. The project has applications in medicine like diagnosing diseases, pharmacology, and gene therapy. It also has applications in agriculture, forensics, evolution studies, and more. Both pros and cons are discussed. Ethical, legal and social issues around areas like privacy, discrimination, and commercialization were also important considerations of the project.
The human genome project vlad mike mike leo duffguest73a974
The Human Genome Project was a 13-year international scientific research project that aimed to determine the sequence of chemical base pairs that make up DNA and identify and map all the genes in the human genome. It was coordinated by the U.S. Department of Energy and National Institutes of Health, starting in 1990 and completing in 2003. The project mapped all the approximately 20,000-25,000 genes in human DNA, with the information being made publicly available.
This document provides information about genetics and genomics. It defines genetics as the study of genes, heredity, and trait inheritance. It then summarizes the history of genetics discoveries from Mendel's work in 1866 to cloning of Dolly the sheep in 1996. The document outlines different areas of genetics research including classical, molecular, behavioral, clinical, and population genetics as well as genomics. It compares genetics and genomics, describing genomics as the study of entire genomes and gene interactions. Several major genomics projects and their goals are summarized such as the Human Genome Project, Cancer Genome Atlas, HapMap, and UK10K.
The Human Genome Project began in 1990 with the goal of mapping all the genes in human DNA to better understand human health and disease. Over 13 years and $3 billion, an international team sequenced the entire human genome, identifying all 3 billion DNA base pairs and approximately 30,000 genes located on human chromosomes. The project was completed in 2003 and its results are stored in public databases, allowing scientists to better diagnose, treat and prevent genetic disorders.
The sequencing of the complete human genome has led to three key outcomes:
1) It has allowed for improved forensics like identifying suspects through DNA evidence and exonerating those wrongly convicted.
2) It has enabled advances in molecular medicine such as improving gene therapy and developing earlier detection methods for genetic diseases.
3) It has facilitated better risk assessment including evaluating health risks from radiation exposure and carcinogens.
The Human Genome Project was an international effort to determine the DNA sequence of the entire human genome. It began in 1984 and published the first draft of the human genome in 2001, finding that the number of human genes is significantly fewer than previous estimates. The project has advanced clinical genetics, population screening, personalized medicine, and functional genomics. It revealed the landscape of the human genome and potential for comparing it to other species to identify functionally important DNA sections.
The Human Genome Project was a 15-year scientific effort that mapped the entire human genome. It was primarily funded by governments in the US, UK, Japan, and other countries and cost $3 billion total. The project successfully identified the locations of all genes within human DNA and provided insights that enable genetically modifying crops, locating cancer cells, and diagnosing genetic diseases prenatally. Key techniques included genetic mapping to locate gene pairs on chromosomes and linkage analysis to determine the distance between disease-causing genes. The project's outcomes include further enabling gene therapy and precisely locating genes responsible for diseases.
The document summarizes the Human Genome Project. The project had goals of identifying all 30,000+ genes in the human DNA sequence and determining the order of the 3 billion chemical base pairs. Samples from diverse donors were collected and sequenced using both hierarchical shotgun and whole genome shotgun methods. Sequence data was stored in databases like GeneBank and made accessible through genome browsers. The project also addressed ethical, legal and social issues and has applications in medicine, forensics and ancestry research.
The document summarizes the Human Genome Project which aimed to sequence and map the entire human genome. The project was launched in 1990 and completed in 2003. Its goals were to identify all human genes, determine the sequences of DNA base pairs, make the data widely available, and address ethical issues. The sequencing process involved isolating DNA, cloning fragments, and using shotgun sequencing. The project has applications in medicine like diagnosing diseases, pharmacology, and gene therapy. It also has applications in agriculture, forensics, evolution studies, and more. Both pros and cons are discussed. Ethical, legal and social issues around areas like privacy, discrimination, and commercialization were also important considerations of the project.
The human genome project vlad mike mike leo duffguest73a974
The Human Genome Project was a 13-year international scientific research project that aimed to determine the sequence of chemical base pairs that make up DNA and identify and map all the genes in the human genome. It was coordinated by the U.S. Department of Energy and National Institutes of Health, starting in 1990 and completing in 2003. The project mapped all the approximately 20,000-25,000 genes in human DNA, with the information being made publicly available.
This document provides information about genetics and genomics. It defines genetics as the study of genes, heredity, and trait inheritance. It then summarizes the history of genetics discoveries from Mendel's work in 1866 to cloning of Dolly the sheep in 1996. The document outlines different areas of genetics research including classical, molecular, behavioral, clinical, and population genetics as well as genomics. It compares genetics and genomics, describing genomics as the study of entire genomes and gene interactions. Several major genomics projects and their goals are summarized such as the Human Genome Project, Cancer Genome Atlas, HapMap, and UK10K.
The Human Genome Project began in 1990 with the goal of mapping all the genes in human DNA to better understand human health and disease. Over 13 years and $3 billion, an international team sequenced the entire human genome, identifying all 3 billion DNA base pairs and approximately 30,000 genes located on human chromosomes. The project was completed in 2003 and its results are stored in public databases, allowing scientists to better diagnose, treat and prevent genetic disorders.
The sequencing of the complete human genome has led to three key outcomes:
1) It has allowed for improved forensics like identifying suspects through DNA evidence and exonerating those wrongly convicted.
2) It has enabled advances in molecular medicine such as improving gene therapy and developing earlier detection methods for genetic diseases.
3) It has facilitated better risk assessment including evaluating health risks from radiation exposure and carcinogens.
The Human Genome Project was an international effort to determine the DNA sequence of the entire human genome. It began in 1984 and published the first draft of the human genome in 2001, finding that the number of human genes is significantly fewer than previous estimates. The project has advanced clinical genetics, population screening, personalized medicine, and functional genomics. It revealed the landscape of the human genome and potential for comparing it to other species to identify functionally important DNA sections.
The Human Genome Project was a 15-year scientific effort that mapped the entire human genome. It was primarily funded by governments in the US, UK, Japan, and other countries and cost $3 billion total. The project successfully identified the locations of all genes within human DNA and provided insights that enable genetically modifying crops, locating cancer cells, and diagnosing genetic diseases prenatally. Key techniques included genetic mapping to locate gene pairs on chromosomes and linkage analysis to determine the distance between disease-causing genes. The project's outcomes include further enabling gene therapy and precisely locating genes responsible for diseases.
The document summarizes the Human Genome Project. The project had goals of identifying all 30,000+ genes in the human DNA sequence and determining the order of the 3 billion chemical base pairs. Samples from diverse donors were collected and sequenced using both hierarchical shotgun and whole genome shotgun methods. Sequence data was stored in databases like GeneBank and made accessible through genome browsers. The project also addressed ethical, legal and social issues and has applications in medicine, forensics and ancestry research.
The document summarizes the key aspects of the Human Genome Project. It began in 1990 as a collaborative effort to sequence the entire human genome. Major milestones included a working draft in 2000 covering over 90% of the genome, and completion in 2003, two years ahead of schedule. The goals were to identify all human genes, develop genetic maps, and make the data publicly available. It helped locate genes associated with diseases and traits but also raised ethical issues around privacy and use of genetic information.
The Human Genome Project mapped our entire genome in 2003, identifying 30,000-35,000 genes in our body. This allows scientists to identify traits and predict disorders, such as predicting disorders in babies before birth through gene mapping. Gene therapy uses vectors to carry normal genes into human cells to correct disorders by producing the correct protein and trait, with the hope that this continues to find cures for new diseases and viruses.
The document discusses the principal aims and applications of the Human Genome Project. The three main aims are to improve human genetics research infrastructure, establish DNA sequence as the interface between human and model organism biology, and improve DNA analytical biochemistry. Key applications discussed are molecular medicine like disease diagnosis, and using microbial genomes to research waste control and environmental cleanup. It provides examples of how genome sequencing is advancing fields like medicine, biotechnology, and environmental applications.
The document provides an overview of the Human Genome Project (HGP). It describes the HGP's goal of mapping and sequencing the entire human genome. The HGP was an international research effort that worked alongside a private company, Celera Genomics, to complete a rough draft of the human genome by 2000. The completion of the HGP marked a major scientific achievement and has transformed fields like medicine, biotechnology, and genetics by providing a comprehensive map of the human genetic code.
The document summarizes several genome and brain mapping projects that followed the completion of the Human Genome Project in 2003. It describes the objectives and outcomes of the HapMap Project, ENCODE Project, Human Proteome Project, European Commission's Human Brain Project, and U.S. Brain Mapping Project. All of these projects aimed to further understand the human genome and proteome, characterize gene functions, and map the structure and diseases of the human brain. The research generated vast amounts of freely available data and furthered knowledge in human biology, disease research, and brain-inspired technologies.
The document summarizes the human genome project. It discusses that the goal of the project was to map all the genes in the human DNA and determine the sequence of the 3 billion nucleotide base pairs. It was a large international project started in 1990 involving many universities. Some key milestones were determining the genes and their sequences, improving data analysis tools, and addressing ethical issues. The project provided benefits like understanding disease and developing personalized medicine. However, it also raised social issues regarding privacy of genetic data and potential discrimination. The sequencing revealed there are around 30,000 genes but many functions are still unknown. Future challenges include determining non-coding DNA and gene functions.
The Human Genome Project was a large, international collaborative project launched in 1990 with the main goal of determining the complete DNA sequence of human genes. It involved research groups from six countries and sought to map all human genes to further the study of genetic diseases. By 2003, the project had completed mapping over 99% of the human genome, finding that while genomes are over 99.9% identical, small differences of 0.1% can impact traits and disease susceptibility. The project provided tremendous medical implications, including enabling identification of disease genes and advancing fields like gene therapy and pharmacogenomics.
Genomics is the study of an organism's entire genome, including all of its genes and their interrelationships. It involves sequencing and analyzing genomes to understand how genes are expressed and work together. The term was coined in 1986. Some key goals of genomics are to sequence entire genomes, understand gene expression, and determine how the genome directs growth and development. Sequencing genomes provides insights into finding genes and understanding how they function together. The Human Genome Project, completed in 2003, mapped the entire human genome sequence. Genomics has applications in medicine, agriculture, evolution studies, and forensics.
The human genome project began in 1990 as a large-scale global effort to map the entire human genome. It was completed in 2003, two years ahead of schedule, at a cost of over $3 billion in public funding. The project raised important ethical issues regarding topics like biosafety, animal rights, biotechnology, genetic screening, and discrimination. While genetic screening allows for early detection of diseases and more informed medical decisions, it also risks stigmatization and potential misuse of genetic data by insurance companies.
Comparative genomics involves comparing genomes to discover similarities and differences. It can provide insights into evolutionary relationships, help predict gene function, and aid in drug discovery. The first step is often aligning genome sequences using tools like BLAST or MUMmer. Genomes can then be compared at various levels, such as overall nucleotide statistics, genome structure, and coding/non-coding regions. Comparing gene and protein content across genomes helps predict functions. Conserved genomic features across species also aid prediction. Insights into genome evolution come from studying molecular events like inversions and duplications. Comparative genomics has impacted phylogenetics and drug target identification.
Genomics is a discipline in genetics that applies recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble and analyze the function and structure of genomes
The document provides an overview of the Human Genome Project (HGP). The HGP was an international scientific research project that aimed to determine the sequence of nucleotide base pairs that make up human DNA and identify and map all human genes. The project began in 1990 and was completed in 2003, two years ahead of schedule. Key outcomes included identifying over 1800 disease genes, developing over 1000 genetic tests, and determining that the human genetic origin is from Africa. The project helped lay the groundwork for advances in personalized medicine.
The document discusses human genes and bioinformatics. It defines bioinformatics as the field that merges biology, computer science, and information technology to understand and organize molecular data on a large scale. It provides information on the human genome, including that it contains around 35,000-50,000 genes and has been sequenced. Genome projects have provided data that can be used in medicine, pharmacogenomics, and other areas to gain biological insights.
Genomics, mutation breeding and society - IAEA Coffee & Banana meeting - Schw...Pat (JS) Heslop-Harrison
i) The document discusses applying genomics tools and techniques like sequencing, mutation breeding, and tissue culture to assess genetic diversity in Ensete, conserve the Ensete gene pool, and support breeding. It aims to identify pathogens and soil biota, compare the Ensete genome to other species, and document and make information accessible.
ii) Genomics is revolutionizing the study of taxonomy, phylogeny, and diversity in crops. It enables exploiting biodiversity for breeding through tools like markers, mutation induction, and tissue culture.
iii) The research has impacts outside academia through legislation, breeding more sustainable varieties, sequencing whole genomes, risk assessment, and advising on biotechnology and food safety.
The document describes the process of creating transgenic mice through microinjection of fertilized mouse eggs with transgenes. The injected eggs are implanted into foster mothers and the offspring ("pups") are analyzed using PCR or Southern blotting to identify potential founders that have the transgene. Founders can then be further studied to analyze the effects of the transgene. Transgenic mice have aided research on diseases like Alzheimer's and cancer by acting as disease models and allowing specific proteins to be produced. While transgenic mice research is useful, there are also ethical concerns regarding animal treatment and environmental issues if genetically modified animals escape.
Bioinformatics is an interdisciplinary field that uses computational tools and techniques to analyze and interpret biological data. It plays a key role in areas like agriculture and healthcare. Some major areas of bioinformatics research include gene finding, protein structure prediction, and drug design. All organisms possess genetic material DNA that controls cell functioning and is the basis for inheritance. Understanding genomes, genes, and how genetic information is expressed presents many challenges. Comparative genomics through genome projects of different organisms can provide insights into evolution and aid in drug development.
A transgenic animal is one that has had part of another species' genome transferred into its own through genetic engineering techniques. One common transgenic animal is mice. To create a transgenic mouse, scientists typically microinject a transgene into fertilized mouse eggs which are then implanted into a foster mother mouse. The offspring are tested for the presence of the transgene. Transgenic mice are useful for studying diseases and testing toxicants. While they aid research, some have ethical concerns about transgenic animal welfare and environmental impacts if genetically modified animals escape.
Transgenic animals are produced by artificially introducing genetic material from another species into the animal's genome. There are several methods used to create transgenic animals, including DNA microinjection, retrovirus-mediated gene transfer, and embryonic stem cell transfer. Examples of transgenic animals include mice, cows, pigs, monkeys, rabbits, and fish. Transgenic animals have applications in medicine, agriculture, and industry, such as producing human proteins for pharmaceuticals, creating disease models, and improving crop yields. However, there are also disadvantages like unintended effects on the animal's genes and low survival rates.
It describes a modern day methodology that is frequently used to produce novel products and improve the quality of products effectively. This PPT includes only a few of the methods that have been discovered. Kindly inform if any corrections or inclusions are needed. And yes, suggestions are always heartily welcome.
ubio is starting a series of biology tutorials aimed at introducing biology, biotechnology and bioinformatics to computer engineers. The first part of the presentation is essentially a biochemistry tutorial that introduces molecular biochemistry.
The document discusses the internal components of a computer. It begins by explaining that the processor is the "heart" of the computer as it processes all data-related tasks. It then describes different types of memory including RAM, ROM, flash memory, and hard drives. Additional components covered include network cards, expansion cards, input/output devices, and connection interfaces.
The document summarizes the key aspects of the Human Genome Project. It began in 1990 as a collaborative effort to sequence the entire human genome. Major milestones included a working draft in 2000 covering over 90% of the genome, and completion in 2003, two years ahead of schedule. The goals were to identify all human genes, develop genetic maps, and make the data publicly available. It helped locate genes associated with diseases and traits but also raised ethical issues around privacy and use of genetic information.
The Human Genome Project mapped our entire genome in 2003, identifying 30,000-35,000 genes in our body. This allows scientists to identify traits and predict disorders, such as predicting disorders in babies before birth through gene mapping. Gene therapy uses vectors to carry normal genes into human cells to correct disorders by producing the correct protein and trait, with the hope that this continues to find cures for new diseases and viruses.
The document discusses the principal aims and applications of the Human Genome Project. The three main aims are to improve human genetics research infrastructure, establish DNA sequence as the interface between human and model organism biology, and improve DNA analytical biochemistry. Key applications discussed are molecular medicine like disease diagnosis, and using microbial genomes to research waste control and environmental cleanup. It provides examples of how genome sequencing is advancing fields like medicine, biotechnology, and environmental applications.
The document provides an overview of the Human Genome Project (HGP). It describes the HGP's goal of mapping and sequencing the entire human genome. The HGP was an international research effort that worked alongside a private company, Celera Genomics, to complete a rough draft of the human genome by 2000. The completion of the HGP marked a major scientific achievement and has transformed fields like medicine, biotechnology, and genetics by providing a comprehensive map of the human genetic code.
The document summarizes several genome and brain mapping projects that followed the completion of the Human Genome Project in 2003. It describes the objectives and outcomes of the HapMap Project, ENCODE Project, Human Proteome Project, European Commission's Human Brain Project, and U.S. Brain Mapping Project. All of these projects aimed to further understand the human genome and proteome, characterize gene functions, and map the structure and diseases of the human brain. The research generated vast amounts of freely available data and furthered knowledge in human biology, disease research, and brain-inspired technologies.
The document summarizes the human genome project. It discusses that the goal of the project was to map all the genes in the human DNA and determine the sequence of the 3 billion nucleotide base pairs. It was a large international project started in 1990 involving many universities. Some key milestones were determining the genes and their sequences, improving data analysis tools, and addressing ethical issues. The project provided benefits like understanding disease and developing personalized medicine. However, it also raised social issues regarding privacy of genetic data and potential discrimination. The sequencing revealed there are around 30,000 genes but many functions are still unknown. Future challenges include determining non-coding DNA and gene functions.
The Human Genome Project was a large, international collaborative project launched in 1990 with the main goal of determining the complete DNA sequence of human genes. It involved research groups from six countries and sought to map all human genes to further the study of genetic diseases. By 2003, the project had completed mapping over 99% of the human genome, finding that while genomes are over 99.9% identical, small differences of 0.1% can impact traits and disease susceptibility. The project provided tremendous medical implications, including enabling identification of disease genes and advancing fields like gene therapy and pharmacogenomics.
Genomics is the study of an organism's entire genome, including all of its genes and their interrelationships. It involves sequencing and analyzing genomes to understand how genes are expressed and work together. The term was coined in 1986. Some key goals of genomics are to sequence entire genomes, understand gene expression, and determine how the genome directs growth and development. Sequencing genomes provides insights into finding genes and understanding how they function together. The Human Genome Project, completed in 2003, mapped the entire human genome sequence. Genomics has applications in medicine, agriculture, evolution studies, and forensics.
The human genome project began in 1990 as a large-scale global effort to map the entire human genome. It was completed in 2003, two years ahead of schedule, at a cost of over $3 billion in public funding. The project raised important ethical issues regarding topics like biosafety, animal rights, biotechnology, genetic screening, and discrimination. While genetic screening allows for early detection of diseases and more informed medical decisions, it also risks stigmatization and potential misuse of genetic data by insurance companies.
Comparative genomics involves comparing genomes to discover similarities and differences. It can provide insights into evolutionary relationships, help predict gene function, and aid in drug discovery. The first step is often aligning genome sequences using tools like BLAST or MUMmer. Genomes can then be compared at various levels, such as overall nucleotide statistics, genome structure, and coding/non-coding regions. Comparing gene and protein content across genomes helps predict functions. Conserved genomic features across species also aid prediction. Insights into genome evolution come from studying molecular events like inversions and duplications. Comparative genomics has impacted phylogenetics and drug target identification.
Genomics is a discipline in genetics that applies recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble and analyze the function and structure of genomes
The document provides an overview of the Human Genome Project (HGP). The HGP was an international scientific research project that aimed to determine the sequence of nucleotide base pairs that make up human DNA and identify and map all human genes. The project began in 1990 and was completed in 2003, two years ahead of schedule. Key outcomes included identifying over 1800 disease genes, developing over 1000 genetic tests, and determining that the human genetic origin is from Africa. The project helped lay the groundwork for advances in personalized medicine.
The document discusses human genes and bioinformatics. It defines bioinformatics as the field that merges biology, computer science, and information technology to understand and organize molecular data on a large scale. It provides information on the human genome, including that it contains around 35,000-50,000 genes and has been sequenced. Genome projects have provided data that can be used in medicine, pharmacogenomics, and other areas to gain biological insights.
Genomics, mutation breeding and society - IAEA Coffee & Banana meeting - Schw...Pat (JS) Heslop-Harrison
i) The document discusses applying genomics tools and techniques like sequencing, mutation breeding, and tissue culture to assess genetic diversity in Ensete, conserve the Ensete gene pool, and support breeding. It aims to identify pathogens and soil biota, compare the Ensete genome to other species, and document and make information accessible.
ii) Genomics is revolutionizing the study of taxonomy, phylogeny, and diversity in crops. It enables exploiting biodiversity for breeding through tools like markers, mutation induction, and tissue culture.
iii) The research has impacts outside academia through legislation, breeding more sustainable varieties, sequencing whole genomes, risk assessment, and advising on biotechnology and food safety.
The document describes the process of creating transgenic mice through microinjection of fertilized mouse eggs with transgenes. The injected eggs are implanted into foster mothers and the offspring ("pups") are analyzed using PCR or Southern blotting to identify potential founders that have the transgene. Founders can then be further studied to analyze the effects of the transgene. Transgenic mice have aided research on diseases like Alzheimer's and cancer by acting as disease models and allowing specific proteins to be produced. While transgenic mice research is useful, there are also ethical concerns regarding animal treatment and environmental issues if genetically modified animals escape.
Bioinformatics is an interdisciplinary field that uses computational tools and techniques to analyze and interpret biological data. It plays a key role in areas like agriculture and healthcare. Some major areas of bioinformatics research include gene finding, protein structure prediction, and drug design. All organisms possess genetic material DNA that controls cell functioning and is the basis for inheritance. Understanding genomes, genes, and how genetic information is expressed presents many challenges. Comparative genomics through genome projects of different organisms can provide insights into evolution and aid in drug development.
A transgenic animal is one that has had part of another species' genome transferred into its own through genetic engineering techniques. One common transgenic animal is mice. To create a transgenic mouse, scientists typically microinject a transgene into fertilized mouse eggs which are then implanted into a foster mother mouse. The offspring are tested for the presence of the transgene. Transgenic mice are useful for studying diseases and testing toxicants. While they aid research, some have ethical concerns about transgenic animal welfare and environmental impacts if genetically modified animals escape.
Transgenic animals are produced by artificially introducing genetic material from another species into the animal's genome. There are several methods used to create transgenic animals, including DNA microinjection, retrovirus-mediated gene transfer, and embryonic stem cell transfer. Examples of transgenic animals include mice, cows, pigs, monkeys, rabbits, and fish. Transgenic animals have applications in medicine, agriculture, and industry, such as producing human proteins for pharmaceuticals, creating disease models, and improving crop yields. However, there are also disadvantages like unintended effects on the animal's genes and low survival rates.
It describes a modern day methodology that is frequently used to produce novel products and improve the quality of products effectively. This PPT includes only a few of the methods that have been discovered. Kindly inform if any corrections or inclusions are needed. And yes, suggestions are always heartily welcome.
ubio is starting a series of biology tutorials aimed at introducing biology, biotechnology and bioinformatics to computer engineers. The first part of the presentation is essentially a biochemistry tutorial that introduces molecular biochemistry.
The document discusses the internal components of a computer. It begins by explaining that the processor is the "heart" of the computer as it processes all data-related tasks. It then describes different types of memory including RAM, ROM, flash memory, and hard drives. Additional components covered include network cards, expansion cards, input/output devices, and connection interfaces.
This document discusses the importance of computational tools for biological research. It provides an overview of how computer applications are used in areas like the Human Genome Project, transcriptomics, proteomics, and systems biology. The document also notes challenges for biological research in Thailand, including a lack of background knowledge in computer science and limited access to free and easy-to-use computational tools, especially in the Thai language. It argues that biology students in Thailand should be taught bioinformatics and computational biology skills to better facilitate biological research.
Bioinformatics is an interdisciplinary field that combines computer science, statistics, mathematics and engineering to study and process biological data, such as DNA sequences, in order to better understand biology. It involves developing methods and software tools to analyze large amounts of biological data, including sequencing genomes to understand what makes different organisms function. As data sets have grown enormously in size, bioinformatics relies on high-performance computing to make sense of it all and gain insights into normal cellular processes and how they are altered in disease states.
Building Executable Biology Models for Synthetic BiologyNatalio Krasnogor
The leveraging of today's unprecedented capability to manipulate biological systems by state-of-the-art computational, mathematical and engineering techniques , may profoundly affect the way we approach the solution to pressing grand challenges such as the development of sustainable green energy, next generation healthcare, etc. The conceptual cornerstone of Synthetic Biology a field very much on its infancy- is that methodologies commonly used to design and construct non-biological artefacts (e.g. computer programs, airplanes, bridges, etc) might also be mastered to create designer living entities. Computational methods for modeling in Synthetic Biology consist of a list of instructions detailing an algorithm that can be executed and whose computation resembles the behavior of the biological system under study. This computational approach to modelling biological systems has been termed executable biology. In this talk I will describe current approaches for the automated generation and testing of executable biology models for synthetic biology.
This was a colloquioum talk at the Computer Science Department, Ben-Gurion University of the Negev, Israel (30/June/2009)
This document discusses the parallels between computer science and synthetic biology from a perspective that "everything is software". It notes how early humans developed coding systems like mathematics to record and compute information. Over time, more advanced coding systems like writing systems and languages emerged, alongside machines that could process these codes. The document then discusses how computer science developed coding languages and machines that can recognize and execute these languages. It argues that synthetic biology may be viewed similarly, with DNA acting as a coding language that can be programmed like software. The document concludes by discussing how initiatives like iGEM are attempting to engineer genetic codes and grammars to build biological machines, bringing together concepts from computer science, engineering and synthetic biology.
This document discusses the use of computers in medicine and biology. In medicine, computers are used for X-rays and CT scans to produce images of internal structures, MRI to map internal structures without radiation, monitoring patient vital signs, and robotic surgery. Computers also store diagnostic information in databases and allow it to be instantly accessible worldwide. In biology, computers enable visual simulations and illustrations to help understand concepts, and are used for research through accessing online information and experimental simulations.
The document summarizes a bioinformatics summer camp, including:
1. The camp will cover basic molecular biology and bioinformatics topics like DNA, proteins, gene expression and the genetic code.
2. Students will work on computational analysis projects involving whole genome sequencing, gene expression profiling, and functional and comparative genomics.
3. The camp will teach techniques for analyzing protein structures and interactions, gene expression data, and identifying pockets on protein surfaces.
This document discusses bioinformatics and computational biology. It defines bioinformatics as conceptualizing biology in terms of molecules and applying informatics techniques like mathematics and computer science to understand and organize molecular information on a large scale. Computational biology refers to developing algorithms and statistical models to analyze biological data through computers. The document provides examples of areas studied in bioinformatics like sequence analysis, genome annotation, and regulation analysis. It also outlines some important applications of bioinformatics like gene therapy and personalized medicine.
1. The document discusses the cell cycle, mitosis, meiosis, and cell division. It describes how cell growth triggers cell division, with the cell membrane growing more slowly than the cytoplasm.
2. Mitosis is described as nuclear division that copies a cell's DNA so each daughter cell has identical DNA. The stages of mitosis are interphase, prophase, metaphase, anaphase, and telophase.
3. Meiosis produces gametes and involves two nuclear divisions. In meiosis I, homologous chromosomes separate. In meiosis II, sister chromatids separate, resulting in haploid gametes. Fertilization of an egg and sperm restores diploidy.
This document provides an overview of bioinformatics software. It discusses how bioinformatics is an interdisciplinary field that develops methods and tools for understanding biological data. The document outlines the history, goals, approaches, relation to other fields, and conclusion of bioinformatics. It was written by Umer Farooq for a class at the University of Education, Okara Campus in Pakistan.
Responsive web design (RWD) is an approach to web design aimed at crafting sites to provide an optimal viewing and interaction experience like easy reading and navigation with a minimum of resizing, panning, and scrolling across a wide range of devices (from desktop computer monitors to mobile phones).
Responsive web design is becoming more important as the amount of mobile traffic now accounts for more than half of total internet traffic. This trend is so prevalent that Google has begun to boost the ratings of sites that are mobile friendly if the search was made from a mobile device. This has the net effect of penalizing sites that are not mobile friendly.
The responsive web design responds to the needs of the users and the devices they’re using. The layout changes based on the size and capabilities of the device and provides the enhanced user-experience by re-structuring the contents as per the end-user devices. With plethora devices releasing every day, this has gained significance in the web designing and along with it came the testing challenges. In this workshop, we are going to discuss the challenges in testing RWD websites and how to overcome those by using the tools available online.
Why Galen?
Galen is an open source framework built for responsive websites. It provides the feasibility to test the various pages on screen sizes and browsers. The test and spec files can be written in plain English which makes it easier for the business people to understand and contribute.
Bioinformatics plays a key role in drug discovery by enabling researchers to efficiently analyze large amounts of biological data and computationally simulate drug-target interactions. Some important applications of bioinformatics in drug discovery include virtual high-throughput screening of compound libraries against protein targets to identify potential drug leads, analyzing genetic and protein sequences to infer evolutionary relationships and identify drug targets, and using homology modeling to predict the 3D structures of targets to aid in drug design when experimental structures are unknown.
CADD is a mixture of bioinformatics and computer science where the information from bioinformatics is combined into a software which makes it easier to process.
Bioinformatics analyzes massive amounts of biological data like DNA sequences to uncover hidden biological information. It has many applications like molecular medicine, drug development, and microbial genome analysis. Common bioinformatics tools like BLAST are used to compare query sequences against databases to find similar sequences. BLAST works through a heuristic algorithm that finds short matches between sequences to locate potential homologs in an efficient manner. Other algorithms like Smith-Waterman and FASTA also perform sequence alignment but with different tradeoffs in accuracy and speed.
Uses of Artificial Intelligence in BioinformaticsPragya Pai
This presentation is about the usage of Artificial Intelligence in Bioinformatics. These slides give the basic knowledge about usage of Artificial Intelligence in Bioinformatics.
1. Bioinformatics uses computer science and information technology to analyze biological data and assist with drug discovery. It helps identify drug targets and design drug candidates.
2. The drug design process involves identifying a disease target, studying compounds of interest, detecting molecular disease bases, rational drug design, refinement, and testing. Bioinformatics tools assist with each step.
3. CADD uses computational methods to simulate drug-receptor interactions and is heavily dependent on bioinformatics tools and databases. It supports techniques like virtual screening, sequence analysis, homology modeling, and physicochemical modeling to aid drug development.
The different use and negative effects of computers in education.
P.S. Guys kindly click like if the article is helpful and IF you're going to download the slides/presentation.Thank you.
Bioinformatics combines computer science, statistics, mathematics, and biology to study and process biological data on a large scale. The document discusses several applications of bioinformatics including information search and retrieval, sequence comparison for genetics, phylogenetic analysis, genome annotation, proteomics, pharmacogenomics, and drug discovery. Tools are provided for various applications such as linkage analysis, phylogenetic analysis, genome annotation, and protein identification.
Recently, it was reported that the forkhead box O (FoxO) transcription factor promotes human cytomegalovirus (HCMV)
replication via direct binding to the promoters of the major immediate-early (MIE) genes, but how the FoxO factor impacts HCMV
replication remains unknown. In this report, we found that human cytomegalovirus (HCMV), a beta herpesvirus member, could
dramatically induce the expression of FOXOs in the infected human fibroblasts. The induced FOXOs were recruited into the viral
replication compartments (vRC) in the nucleus, especially at the late stage of infection. Suppression of FOXO expression by RNA
interference significantly inhibited HCMV replication, and the production of progeny virus was reduced remarkably.
Mechanistically, FOXO knockdown intensively crippled viral late gene expression at the transcriptional level, while it only
marginally affected viral DNA synthesis. This study highlights how FoxO enhances HCMV gene transcription and viral replication
to promote productive infection
This document provides an introduction to the field of bioinformatics. It discusses how bioinformatics applies computing techniques to analyze large amounts of biological data from fields like molecular biology, medicine, and biotechnology. The document outlines the course contents, which will cover topics like biological databases, gene and protein analysis, phylogenetic analysis, and gene prediction. It provides background on related fields like computational biology, medical informatics, and proteomics. The history of bioinformatics is also summarized, from early genetics and discovery of DNA to advances in computing that enabled large-scale analysis of biological data.
The document provides an introduction to the field of bioinformatics. It discusses how bioinformatics applies computer science to analyze large amounts of biological data from fields like molecular biology, medicine, and biotechnology. It also outlines some of the main topics that will be covered in the course, including biological databases, gene and protein analysis, phylogenetic analysis, and gene prediction.
Genome projects
Definition of genome, history of genome projects, whole genome sequencing, Maxam Gilbert sequencing, sanger sequencing, explanation on the first sequenced organisms (Bacteriophage, bacteria, archaeon, virus, bakers yeast, nematode.
Model organism-Arabidopsis thaliana, Mus musculus, Oryza sativa, Pan troglodyte etc.
Human genome project, milestones and significance.
The document discusses the hierarchy of knowledge in biochemistry, molecular biology, and biotechnology. It begins by explaining how biochemistry initially focused on proteins and enzymes, while molecular biology focused on nucleic acids and the structure and function of genes. Biotechnology emerged due to advances in molecular biology and recombinant DNA techniques. The key areas of each discipline are defined, including how molecular biology studies how organisms are made from simple molecules at the cellular level.
This document provides a history of genetics, describing major events from ancient times through the 20th century. It outlines old ideas that had to be overcome, like spontaneous generation and inheritance of acquired traits. Key discoveries include Mendel's work in 1866, rediscovery in 1900, Morgan's work linking genes to chromosomes in 1910, and Watson and Crick's DNA structure determination in 1953. The current understanding is that DNA sequences encode instructions to build organisms, with genes expressing as RNA and protein. Mutations occur randomly and natural selection favors those that increase fitness.
This document provides a history of biotechnology from its origins thousands of years ago to modern applications. It discusses:
- Key events and discoveries from 6000 BC to the present, including the structure of DNA being discovered in 1953 and the first recombinant DNA molecule being created in 1972.
- The major periods of biotechnology history: pre-1800, 1800-1900, 1900-1953, 1953-1976, 1977-present.
- Applications of biotechnology in medicine (red), agriculture/food (green), industrial processes (white), and environment (blue).
- Modern products like insulin, monoclonal antibodies, genetically engineered crops, and the use of microbes, plants, and animals to produce therapeutic proteins.
1. Genetics has a long history dating back to early animal and plant domestication where selective breeding was used to develop desirable traits.
2. Modern genetics was established in the mid-19th century through Mendel's work on inheritance in pea plants. Major advances in the 20th century included discovering that genes are located on chromosomes and determining the DNA structure.
3. Recent milestones include cloning DNA molecules and sequencing entire genomes, advancing basic research and medical applications. New techniques also raise ethical issues requiring consideration.
This document provides a history of genetics, describing major events from ancient times through the 20th century. It notes that early civilizations practiced selective breeding of animals and plants. In the mid-1800s, Darwin published On the Origin of Species introducing the theory of evolution, while Mendel's work on inheritance in plants was published but largely ignored. In the early 1900s, Mendel's work was rediscovered and linked to chromosomes. Major advances included discovering DNA's role as the genetic material and determining its structure. The current understanding of genetics includes DNA containing genes that encode proteins, with mutations constantly occurring but most having no effect.
Mendel's work with pea plants in the mid-19th century laid the foundations of genetics by demonstrating that traits are passed from parents to offspring through discrete units of inheritance. During the early 20th century, scientists such as Morgan and Sutton connected Mendel's theories to chromosomes and the cellular basis of inheritance. The emergence of molecular genetics in the mid-20th century revealed that DNA carries the genetic information that is passed from cell to cell and between generations.
Comparative proteogenomics using mass spectrometry data from multiple genomes can address problems that a single genome approach cannot. It helps identify rare post-translational modifications, resolve "one-hit wonders" by looking for correlated peptides in orthologous proteins across species, and identify programmed frameshifts and sequencing errors. The approach is demonstrated through an analysis of mass spectrometry data from three Shewanella bacteria genomes, improving gene predictions and annotations compared to existing tools.
The document provides a history of genetics, beginning with early ideas about inheritance and selective breeding. Major milestones include Darwin's theory of evolution by natural selection in 1859, Mendel's laws of inheritance in 1866, and the discoveries that DNA is the genetic material and determines its 3D structure. In the 20th century, knowledge advanced with linkage of genes to chromosomes in 1910, discovery that mutations cause genetic change in 1926, and determining the DNA structure and genetic code in 1953 and 1966. Current understanding is that DNA sequences encode instructions to build organisms, with genes expressing via transcription and translation, and inheritance of alleles explaining variation.
Genomics is the study of whole genomes. In the 1980s, scientists determined sequences of important genes. In the 1990s, the genome of H. influenzae was fully sequenced. The Human Genome Project, begun in 1990, fully sequenced the human genome ahead of schedule in 2003. The human genome contains 3.2 billion DNA base pairs and 30,000-40,000 genes. While genomics provides medical benefits, it also raises safety, ethical, and privacy concerns that remain open questions.
This document provides an overview of DNA and genetics. It discusses how DNA was established as the genetic material through experiments in the 1900s and 1950s. It describes the structure of DNA as a double helix based on the work of Watson, Crick, Wilkins and Franklin. It also summarizes Mendel's laws of inheritance and how chromosomes package and transmit genetic information from one generation to the next. The document traces the history of genetics from early Greek philosophers through modern discoveries that have revolutionized our understanding of heredity and molecular biology.
This document provides a history of biotechnology from 500 BC to the present. It describes early uses of microorganisms in China and Greece. Major developments include the invention of the microscope in the 16th century, the discovery of cells and bacteria in the 17th century, and the first vaccine in the late 18th century. The 20th century saw discoveries of DNA, genes, and genetic engineering. Major milestones include cloning in the 1970s-80s, the Human Genome Project in the 1980s-90s, and the sequencing of the human genome in 2001. Biotechnology now involves cloning animals, developing new drugs and vaccines, and sequencing pathogen genomes.
Genomics is the study of genomes, including sequencing genomes and determining the complete set of proteins and genes in an organism. The first genomes sequenced included Haemophilus influenzae in 1995 and the human genome was completed in 2003, taking 13 years. Genomics provides information on genes, metabolic pathways, and the functioning of organisms through approaches like genome sequencing, structural genomics, functional genomics, comparative genomics, and proteomics.
Human Genome Project (HGP) was an international scientific research project with the goal of determining the base pairs that make up human DNA, and of identifying and mapping all of the genes of the human genome from both a physical and a functional
This document discusses automating responsive website testing. It begins by defining responsive web design as designing and developing websites to respond to the user's behavior and environment based on screen size, platform and orientation. It then discusses how responsive design is achieved through techniques like a flexible grid, relative sizing, media queries and flexible images. The document outlines things to consider when testing responsive websites like checking different resolutions, important content visibility and text formatting. It introduces tools that can be used for responsive testing like Galen Framework, which defines layouts across devices using a spec file and verifies the layout by resizing browsers.
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2. What Is Bioinformatics?
• Bioinformatics is the unified discipline formed
from the combination of biology, computer
science, and information technology.
• "The mathematical, statistical and computing
methods that aim to solve biological problems
using DNA and amino acid sequences and
related information.“ –Frank Tekaia
3. A Molecular Alphabet
• Most large biological molecules are polymers,
ordered chains of simple molecules called
monomers
• All monomers belong to the same general class,
but there are several types with distinct and
well-defined characteristics
• Many monomers can be joined to form a single,
large macromolecule; the ordering of monomers
in the macromolecule encodes information, just
like the letters of an alphabet
4. Related Fields:
Computational Biology
• The study and application of computing methods
for classical biology
• Primarily concerned with evolutionary,
population and theoretical biology, rather than
the cellular or molecular level
5. Related Fields:
Medical Informatics
• The study and application of computing methods
to improve communication, understanding, and
management of medical data
• Generally concerned with how the data is
manipulated rather than the data itself
6. Related Fields:
Cheminformatics
• The study and application of computing
methods, along with chemical and biological
technology, for drug design and development
7. Related Fields:
Genomics
• Analysis and comparison of the entire genome of
a single species or of multiple species
• A genome is the set of all genes possessed by an
organism
• Genomics existed before any genomes were
completely sequenced, but in a very primitive
state
8. Related Fields:
Proteomics
• Study of how the genome is expressed in
proteins, and of how these proteins function and
interact
• Concerned with the actual states of specific cells,
rather than the potential states described by the
genome
9. Related Fields:
Pharmacogenomics
• The application of genomic methods to identify
drug targets
• For example, searching entire genomes for
potential drug receptors, or by studying gene
expression patterns in tumors
10. Related Fields:
Pharmacogenetics
• The use of genomic methods to determine what
causes variations in individual response to drug
treatments
• The goal is to identify drugs that may be only be
effective for subsets of patients, or to tailor drugs
for specific individuals or groups
13. Gregor Mendel (1822-1884)
• Credited with the theories of Heredity
• Developed his theories through the study of pea
pods.
• Studied them “for the fun of the thing”
14. Mendel’s Experiments
• Cross-bred two different types of pea seads
▫ Sperical
▫ Wrinkled
• After the 2nd generation of pea seeds were cross-
bred, Mendel noticed that, although all of the 2nd
generation seeds were spherical, about 1/4th of
the 3rd generation seeds were wrinkled.
15. Mendel’s Experiments (cont.)
• Through this, Mendel developed the concept of
“discrete units of inheritance,” and that each
individual pea plant had two versions, or alleles,
of a trait determining gene.
• This concept was later fully developed into the
concept of chromosomes
16. History of Chromosomes
• Walter Flemming
• August Weissman
• Theodor Boveri
• Walter S. Sutton
• Thomas Hunt Morgan
17. Walther Flemming (1843-1905)
• Studied the cells of salamanders and developing
improved fixing and staining methods
• Developed the concept of mitosis cell
reproduction (1882).
18. August Weismann (1834-1914)
• Studied plant and animal germ cells
• distinguished between body cells and germ cells
and proposed the theory of the continuity of
germ plasm from generation to generation
(1885)
• Developed the concept of meiosis
19. Theodor Boveri (1862-1915)
• Studied the eggs of exotic animals
• Used a light microscope to examine
chromosomes more closely
• Established individuality and continuity in
chromosomes
• Flemming, Boveri, and Weismann together are
given credit for the discovery of chromosomes
although they did not work together.
20. Walter S. Sutton (1877-1916)
• Also studied germ cells specifically those of the
Brachystola magna (grasshopper)
• Discovered that chromosomes carried the cell’s
unit’s of inheritance
21. Thomas Hunt Morgan (1866-1945)
• Born in Lexington, KY
• Studied the Drosophilae fruit fly to determine
whether heredity determined Darwinist
evolution
• Found that genes could be mapped in order
along the length of a chromosome
22. History of DNA
• Griffith
• Avery, MacLeod, and McCarty
• Hershey and Chase
• Watson and Crick
23. Frederick Griffith
• British microbiologist
• In 1928, Studied the effects of bacteria on mice
▫ Determined that some kind of “transforming
factor” existed in the heredity of cells
24. Oswald Theodore Avery (1877-1955)
Colin MacLeod
Maclyn McCarty
• 1944 - Through their work in bacteria, showed
that Deoxyribonucleic Acid (DNA) was the agent
responsible for transferring genetic information
▫ Previously thought to be a protein
25. Alfred Hershey (1908-1997)
Martha Chase (1930- )
• 1952 - Studied the bacteriophage T2 and its host
bacterium, Escherichia coli
• Found that DNA actually is the genetic material
that is transferred
26.
27. James Watson (1928-)
Francis Crick (1916-)
• 1951 – Collaborated to gather all available data
about DNA in order to determine its structure
• 1953 Developed
▫ The double helix model for DNA structure
▫ The AT-CG strands that the helix is consisted of
30. Computer Timeline
• ~1000BC The abacus
• 1621 The slide rule invented
• 1625 Wilhelm Schickard's mechanical calculator
• 1822 Charles Babbage's Difference Engine
• 1926 First patent for a semiconductor transistor
• 1937 Alan Turing invents the Turing Machine
• 1939 Atanasoff-Berry Computer created at Iowa State
▫ the world's first electronic digital computer
• 1939 to 1944 Howard Aiken's Harvard Mark I (the IBM ASCC)
• 1940 Konrad Zuse -Z2 uses telephone relays instead of mechanical logical
circuits
• 1943 Collossus - British vacuum tube computer
• 1944 Grace Hopper, Mark I Programmer (Harvard Mark I)
• 1945 First Computer "Bug", Vannevar Bush "As we may think"
31. Computer Timeline (cont.)
• 1948 to 1951 The first commercial computer – UNIVAC
• 1952 G.W.A. Dummer conceives integrated circuits
• 1954 FORTRAN language developed by John Backus (IBM)
• 1955 First disk storage (IBM)
• 1958 First integrated circuit
• 1963 Mouse invented by Douglas Englebart
• 1963 BASIC (standing for Beginner's All Purpose Symbolic Instruction Code) was written (invented) at
Dartmouth College, by mathematicians John George Kemeny and Tom Kurtzas as a teaching tool for
undergraduates
• 1969 UNIX OS developed by Kenneth Thompson
• 1970 First static and dynamic RAMs
• 1971 First microprocessor: the 4004
• 1972 C language created by Dennis Ritchie
• 1975 Microsoft founded by Bill Gates and Paul Allen
• 1976 Apple I and Apple II microcomputers released
• 1981 First IBM PC with DOS
• 1985 Microsoft Windows introduced
• 1985 C++ language introduced
• 1992 Pentium processor
• 1993 First PDA
• 1994 JAVA introduced by James Gosling
• 1994 Csharp language introduced
32. Putting it all Together
• Bioinformatics is basically where the findings in genetics
and the advancement in technology meet in that
computers can be helpful to the advancement of
genetics.
• Depending on the definition of Bioinformatics used, or
the source , it can be anywhere between 13 to 40 years
old
▫ Bioinformatics like studies were being performed in
the ’60s long before it was given a name
Sometimes called “molecular evolution”
▫ The term Bioinformatics was first published in 1991
34. What is Genomics?
• Genome
▫ complete set of genetic instructions for making an
organism
• Genomics
▫ any attempt to analyze or compare the entire
genetic complement of a species
▫ Early genomics was mostly recording genome
sequences
35. History of Genomics
• 1980
▫ First complete genome sequence for an organism is published
FX174 - 5,386 base pairs coding nine proteins.
~5Kb
• 1995
▫ Haemophilus influenzea genome sequenced (flu bacteria, 1.8 Mb)
• 1996
▫ Saccharomyces cerevisiae (baker's yeast, 12.1 Mb)
• 1997
▫ E. coli (4.7 Mbp)
• 2000
▫ Pseudomonas aeruginosa (6.3 Mbp)
▫ A. thaliana genome (100 Mb)
▫ D. melanogaster genome (180Mb)
36. 2001 The Big One
• The Human Genome sequence is published
▫ 3 Gb
▫ And the peasants rejoice!
37. What next?
• Post Genomic era
▫ Comparative Genomics
▫ Functional Genomics
▫ Structural Genomics
38. Comparative Genomics
• the management and analysis of the millions of
data points that result from Genomics
▫ Sorting out the mess
39. Functional Genomics
• Other, more direct, large-scale ways of
identifying gene functions and associations
▫ (for example yeast two-hybrid methods
40. Structural Genomics
• emphasizes high-throughput, whole-genome
analysis.
▫ outlines the current state
▫ future plans of structural genomics efforts around
the world and describes the possible benefits of
this research
42. What Is Proteomics?
• Proteomics is the study of the proteome—the
“PROTEin complement of the genOME”
• More specifically, "the qualitative and
quantitative comparison of proteomes under
different conditions to further unravel biological
processes"
43. What Makes Proteomics Important?
• A cell’s DNA—its genome—describes a blueprint
for the cell’s potential, all the possible forms that
it could conceivably take. It does not describe the
cell’s actual, current form, in the same way that
the source code of a computer program does not
tell us what input a particular user is currently
giving his copy of that program.
44. What Makes Proteomics Important?
• All cells in an organism contain the same DNA.
• This DNA encodes every possible cell type in
that organism—muscle, bone, nerve, skin, etc.
• If we want to know about the type and state of a
particular cell, the DNA does not help us, in the
same way that knowing what language a
computer program was written in tells us
nothing about what the program does.
45. What Makes Proteomics Important?
• There are more than 160,000 genes in each cell,
only a handful of which actually determine that
cell’s structure.
• Many of the interesting things about a given
cell’s current state can be deduced from the type
and structure of the proteins it expresses.
• Changes in, for example, tissue types, carbon
sources, temperature, and stage in life of the cell
can be observed in its proteins.
46. Proteomics In Disease Treatment
• Nearly all major diseases—more than 98% of all
hospital admissions—are caused by an particular
pattern in a group of genes.
• Isolating this group by comparing the hundreds
of thousands of genes in each of many genomes
would be very impractical.
• Looking at the proteomes of the cells associated
with the disease is much more efficient.
47. Proteomics In Disease Treatment
• Many human diseases are caused by a normal
protein being modified improperly. This also can
only be detected in the proteome, not the
genome.
• The targets of almost all medical drugs are
proteins. By identifying these proteins,
proteomics aids the progress of
pharmacogenetics.
48. Examples
• What do these have in common?
▫ Alzheimer's disease
▫ Cystic fibrosis
▫ Mad Cow disease
▫ An inherited form of emphysema
▫ Even many cancers
50. What is it?
• Fundamental components
▫ Proteins
• Ribosome's string together long linear chains of
amino acids.
▫ Called Proteins
▫ Loop about each other in a variety of ways
Known as folding
Determines whether or not the protein functions
51.
52.
53. Dangers
• Folding determines function
• Of the many ways of folding one means correct
functionality
▫ Misfolded proteins can mean the protein will have
a lack of functionality
Even worse can be damaging or dangerous to other
proteins
Too much of a misfolded protein can be worse then
too little of a normal folded one
Can poison the cells around it
54. History
• Linus Pauling – half a century ago
▫ Discovered
A-helix
B-sheets
These are found in almost every protein
• Christian Anfinsen – early 1960’s
▫ Discovered
Proteins tie themselves
If separated fold back into their own proper form
No folder or shaper needed
55. Expansion to Anfinsen
• Sometime the protein will fold into the WRONG
shape
• Chaperones
▫ Proteins who’s job is to keep their target proteins
from getting off the right folding path
▫ These two key elements help us understand keys
to protein folding diseases
56. What is Protein Folding
• Primary Structure
▫ 3-D conformation of a protein depends only on its
linear amino acid sequence
▫ In theory can be computed explicitly with only this
information
▫ One of the driving forces that is thought to cause
protein folding is called the hydrophobic effect
57. Hydrophobic effect
• Certain side chains do not like to be exposed to
water
▫ Tend to be found at the core of most proteins
▫ Minimize surface area in contact with water
63. Hydrogen Bonds
• In both secondary structures
▫ Alpha-helix
▫ Beta-Sheets
• Responsible for stabilization
• Greatly effect the final fold of the protein
64. Fold Calculation
• Of all the possible ways the protein could fold,
which one is
▫ Most stable structure
▫ Lowest energy
• Calculation of protein energy is only
approximate
▫ Thus compounding the complexity of such a
calculation
▫ Requiring enormous computational power
65. Why Fold Proteins
• Many genetic diseases are caused by
dysfunctional proteins
▫ By learning the structures we can learn the
functions of each protein
▫ Build better cures
▫ Understand mutation
▫ Assign structures functions to every protein
Thus understand the human genome
Decode the Human DNA