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6.895 Computational Biology: Genomes, Networks, Evolution (MIT) 6.895 Computational Biology: Genomes, Networks, Evolution (MIT)

Description

This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include:Genomes: Biological Sequence Analysis, Hidden Markov Models, Gene Finding, RNA Folding, Sequence Alignment, Genome Assembly.Networks: Gene Expression Analysis, Regulatory Motifs, Graph Algorithms, Scale-free Networks, Network Motifs, Network Evolution.Evolution: Comparative Genomics, Phylogenetics, Genome Duplication, Genome Rearrangements, Evolutionary Theory, Rapid Evolution. This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include:Genomes: Biological Sequence Analysis, Hidden Markov Models, Gene Finding, RNA Folding, Sequence Alignment, Genome Assembly.Networks: Gene Expression Analysis, Regulatory Motifs, Graph Algorithms, Scale-free Networks, Network Motifs, Network Evolution.Evolution: Comparative Genomics, Phylogenetics, Genome Duplication, Genome Rearrangements, Evolutionary Theory, Rapid Evolution.

Subjects

Genomes: Biological sequence analysis | Genomes: Biological sequence analysis | hidden Markov models | hidden Markov models | gene finding | gene finding | RNA folding | RNA folding | sequence alignment | sequence alignment | genome assembly | genome assembly | Networks: Gene expression analysis | Networks: Gene expression analysis | regulatory motifs | regulatory motifs | graph algorithms | graph algorithms | scale-free networks | scale-free networks | network motifs | network motifs | network evolution | network evolution | Evolution: Comparative genomics | Evolution: Comparative genomics | phylogenetics | phylogenetics | genome duplication | genome duplication | genome rearrangements | genome rearrangements | evolutionary theory | evolutionary theory | rapid evolution | rapid evolution

License

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6.096 Algorithms for Computational Biology (MIT) 6.096 Algorithms for Computational Biology (MIT)

Description

This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks. This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks.

Subjects

biological sequence analysis | biological sequence analysis | gene finding | gene finding | motif discovery | motif discovery | RNA folding | RNA folding | global and local sequence alignment | global and local sequence alignment | genome assembly | genome assembly | comparative genomics | comparative genomics | genome duplication | genome duplication | genome rearrangements | genome rearrangements | evolutionary theory | evolutionary theory | gene expression | gene expression | clustering algorithms | clustering algorithms | scale-free networks | scale-free networks | machine learning applications | machine learning applications

License

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7.28 Molecular Biology (MIT) 7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized. This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.

Subjects

molecular biology | molecular biology | biochemical mechanisms | biochemical mechanisms | gene expression | gene expression | evolution | evolution | prokaryotic genome | prokaryotic genome | eukaryotic genomes | eukaryotic genomes | gene regulation | gene regulation | DNA replication | DNA replication | genetic recombination | genetic recombination | RNA processing | RNA processing | translation | translation | genome | genome

License

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7.342 Personal Genomics and Medicine: What's in Your Genome? (MIT) 7.342 Personal Genomics and Medicine: What's in Your Genome? (MIT)

Description

Human genome sequencing has revolutionized our understanding of disease susceptibility, drug metabolism and human ancestry. This course will explore how these advances have been made possible by revolutionary new sequencing methodologies that have decreased costs and increased throughput of genome analysis, making it possible to examine genetic correlates for a variety of biological processes and disorders. The course will combine discussions of primary scientific research papers with hands-on data analysis and small group presentations. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a Human genome sequencing has revolutionized our understanding of disease susceptibility, drug metabolism and human ancestry. This course will explore how these advances have been made possible by revolutionary new sequencing methodologies that have decreased costs and increased throughput of genome analysis, making it possible to examine genetic correlates for a variety of biological processes and disorders. The course will combine discussions of primary scientific research papers with hands-on data analysis and small group presentations. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a

Subjects

genome sequencing | genome sequencing | genome analysis | genome analysis | disease susceptibility | disease susceptibility | drug metabolism | drug metabolism | human ancestry | human ancestry | mitochondrial DNA | mitochondrial DNA | tyrosine kinase inhibitors | tyrosine kinase inhibitors | BCR-ABL gene fusion | BCR-ABL gene fusion | PCSK9 inhibitors | PCSK9 inhibitors | hypercholesterolemia | hypercholesterolemia | genetic testing | genetic testing | next generation sequencing | next generation sequencing | Single-nucleotide polymorphisms (SNPs) | Single-nucleotide polymorphisms (SNPs) | copy number variations (CNVs) | copy number variations (CNVs) | genome-wide association studies (GWAS) | genome-wide association studies (GWAS) | Chronic myelogenous leukemia (CML) | Chronic myelogenous leukemia (CML) | mosaics | mosaics | chimeras | chimeras | bioinformatics | bioinformatics

License

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6.047 Computational Biology: Genomes, Networks, Evolution (MIT) 6.047 Computational Biology: Genomes, Networks, Evolution (MIT)

Description

This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: biological sequence analysis, hidden Markov models, gene finding, RNA folding, sequence alignment, genome assembly Networks: gene expression analysis, regulatory motifs, graph algorithms, scale-free networks, network motifs, network evolution Evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory, rapid evolution This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: biological sequence analysis, hidden Markov models, gene finding, RNA folding, sequence alignment, genome assembly Networks: gene expression analysis, regulatory motifs, graph algorithms, scale-free networks, network motifs, network evolution Evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory, rapid evolution

Subjects

computational biology | computational biology | algorithms | algorithms | machine learning | machine learning | biology | biology | biological datasets | biological datasets | genomics | genomics | proteomics | proteomics | genomes | genomes | sequence analysis | sequence analysis | sequence alignment | sequence alignment | genome assembly | genome assembly | network motifs | network motifs | network evolution | network evolution | graph algorithms | graph algorithms | phylogenetics | phylogenetics | comparative genomics | comparative genomics | python | python | probability | probability | statistics | statistics | entropy | entropy | information | information

License

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7.344 The Fountain of Life: From Dolly to Customized Embryonic Stem Cells (MIT) 7.344 The Fountain of Life: From Dolly to Customized Embryonic Stem Cells (MIT)

Description

During development, the genetic content of each cell remains, with a few exceptions, identical to that of the zygote. Most differentiated cells therefore retain all of the genetic information necessary to generate an entire organism. It was through pioneering technology of somatic cell nuclear transfer (SCNT) that this concept was experimentally proven. Only 10 years ago the sheep Dolly was the first mammal to be cloned from an adult organism, demonstrating that the differentiated state of a mammalian cell can be fully reversible to a pluripotent embryonic state. A key conclusion from these experiments was that the difference between pluripotent cells such as embryonic stem (ES) cells and unipotent differentiated cells is solely a consequence of reversible changes. These changes, which hav During development, the genetic content of each cell remains, with a few exceptions, identical to that of the zygote. Most differentiated cells therefore retain all of the genetic information necessary to generate an entire organism. It was through pioneering technology of somatic cell nuclear transfer (SCNT) that this concept was experimentally proven. Only 10 years ago the sheep Dolly was the first mammal to be cloned from an adult organism, demonstrating that the differentiated state of a mammalian cell can be fully reversible to a pluripotent embryonic state. A key conclusion from these experiments was that the difference between pluripotent cells such as embryonic stem (ES) cells and unipotent differentiated cells is solely a consequence of reversible changes. These changes, which hav

Subjects

embryonic stem cells | embryonic stem cells | stem cells | stem cells | cells | cells | genetics | genetics | genome | genome | Dolly | Dolly | clone | clone | regenerative therapy | regenerative therapy | somatic | somatic | SCNT | SCNT | pluripotent | pluripotent | scientific literature | scientific literature | nuclear | nuclear | embryonic | embryonic | adult | adult | epigenetics | epigenetics | methylation | methylation | DNA | DNA | histone | histone | biomedical | biomedical | differentiation | differentiation | epigenome | epigenome | nuclear transfer | nuclear transfer | customized | customized | zygote | zygote | RNA | RNA | cancer | cancer | medicine | medicine

License

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7.347 Epigenetic Regulation of Stem Cells (MIT) 7.347 Epigenetic Regulation of Stem Cells (MIT)

Description

During development a single totipotent cell gives rise to the vast array of cell types present in the adult human body, yet each cell has essentially the same DNA sequence. As cells differentiate, distinct sets of genes must be coordinately activated and repressed, ultimately leading to a cell-type specific pattern of gene expression and a particular cell fate. In eukaryotic organisms, DNA is packaged in a complex protein super structure known as chromatin. Modification and reorganization of chromatin play a critical role in coordinating the cell-type specific gene expression programs that are required as a cell transitions from a pluripotent stem cell to a fully differentiated cell type. Epigenetics refers to such heritable changes that occur in chromatin without altering the primary DNA During development a single totipotent cell gives rise to the vast array of cell types present in the adult human body, yet each cell has essentially the same DNA sequence. As cells differentiate, distinct sets of genes must be coordinately activated and repressed, ultimately leading to a cell-type specific pattern of gene expression and a particular cell fate. In eukaryotic organisms, DNA is packaged in a complex protein super structure known as chromatin. Modification and reorganization of chromatin play a critical role in coordinating the cell-type specific gene expression programs that are required as a cell transitions from a pluripotent stem cell to a fully differentiated cell type. Epigenetics refers to such heritable changes that occur in chromatin without altering the primary DNA

Subjects

Stem cells | Stem cells | induced pluripotency | induced pluripotency | Epigenetics | Epigenetics | chromatin | chromatin | histone | histone | epigenome | epigenome | genome-wide analyses | genome-wide analyses | high-throughput sequencing technologies | high-throughput sequencing technologies | Chromatin Immunoprecipitation sequencing | Chromatin Immunoprecipitation sequencing | ncRNAs | ncRNAs | epigenetic regulation | epigenetic regulation | DNA methylation | DNA methylation | post-translational modification of histones | post-translational modification of histones | roles of chromatin-assembly modifying complexes | roles of chromatin-assembly modifying complexes | non-coding RNAs | non-coding RNAs | nuclear organization | nuclear organization | developmental fate | developmental fate | stem cell therapy | stem cell therapy

License

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7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.

Subjects

molecular biology | biochemical mechanisms | gene expression | evolution | prokaryotic genome | eukaryotic genomes | gene regulation | DNA replication | genetic recombination | RNA processing | translation | genome

License

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7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.

Subjects

molecular biology | biochemical mechanisms | gene expression | evolution | prokaryotic genome | eukaryotic genomes | gene regulation | DNA replication | genetic recombination | RNA processing | translation | genome

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.

Subjects

molecular biology | biochemical mechanisms | gene expression | evolution | prokaryotic genome | eukaryotic genomes | gene regulation | DNA replication | genetic recombination | RNA processing | translation | genome

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.895 Computational Biology: Genomes, Networks, Evolution (MIT)

Description

This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include:Genomes: Biological Sequence Analysis, Hidden Markov Models, Gene Finding, RNA Folding, Sequence Alignment, Genome Assembly.Networks: Gene Expression Analysis, Regulatory Motifs, Graph Algorithms, Scale-free Networks, Network Motifs, Network Evolution.Evolution: Comparative Genomics, Phylogenetics, Genome Duplication, Genome Rearrangements, Evolutionary Theory, Rapid Evolution.

Subjects

Genomes: Biological sequence analysis | hidden Markov models | gene finding | RNA folding | sequence alignment | genome assembly | Networks: Gene expression analysis | regulatory motifs | graph algorithms | scale-free networks | network motifs | network evolution | Evolution: Comparative genomics | phylogenetics | genome duplication | genome rearrangements | evolutionary theory | rapid evolution

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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7.342 Personal Genomics and Medicine: What's in Your Genome? (MIT)

Description

Human genome sequencing has revolutionized our understanding of disease susceptibility, drug metabolism and human ancestry. This course will explore how these advances have been made possible by revolutionary new sequencing methodologies that have decreased costs and increased throughput of genome analysis, making it possible to examine genetic correlates for a variety of biological processes and disorders. The course will combine discussions of primary scientific research papers with hands-on data analysis and small group presentations. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a

Subjects

genome sequencing | genome analysis | disease susceptibility | drug metabolism | human ancestry | mitochondrial DNA | tyrosine kinase inhibitors | BCR-ABL gene fusion | PCSK9 inhibitors | hypercholesterolemia | genetic testing | next generation sequencing | Single-nucleotide polymorphisms (SNPs) | copy number variations (CNVs) | genome-wide association studies (GWAS) | Chronic myelogenous leukemia (CML) | mosaics | chimeras | bioinformatics

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.

Subjects

molecular biology | biochemical mechanisms | gene expression | evolution | prokaryotic genome | eukaryotic genomes | gene regulation | DNA replication | genetic recombination | RNA processing | translation | genome

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.096 Algorithms for Computational Biology (MIT)

Description

This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks.

Subjects

biological sequence analysis | gene finding | motif discovery | RNA folding | global and local sequence alignment | genome assembly | comparative genomics | genome duplication | genome rearrangements | evolutionary theory | gene expression | clustering algorithms | scale-free networks | machine learning applications

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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Oxford at Said: A human genome in minutes and what it will mean to you

Description

Oxford Nanopore is a British company, spun out of the University of Oxford in 2005 and founded on the science of Prof Hagan Bayley. It is developing new technology that has the potential to improve greatly the speed and cost of DNA sequencing. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

Subjects

genome | genomics | hagan bailey | DNA sequencing | Oxford Nanopore | genome | genomics | hagan bailey | DNA sequencing | Oxford Nanopore

License

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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7.60 Cell Biology: Structure and Functions of the Nucleus (MIT) 7.60 Cell Biology: Structure and Functions of the Nucleus (MIT)

Description

This course covers the fundamentals of nuclear cell biology as well as the methodological and experimental approaches upon which they are based. Topics include Eukaryotic genome structure, function, and expression, processing of RNA, and regulation of the cell cycle. The techniques and logic used to address important problems in nuclear cell biology is emphasized. Lectures cover broad topic areas in nuclear cell biology and class discussions focus on representative papers recently published in the field. This course covers the fundamentals of nuclear cell biology as well as the methodological and experimental approaches upon which they are based. Topics include Eukaryotic genome structure, function, and expression, processing of RNA, and regulation of the cell cycle. The techniques and logic used to address important problems in nuclear cell biology is emphasized. Lectures cover broad topic areas in nuclear cell biology and class discussions focus on representative papers recently published in the field.

Subjects

cell biology | cell biology | nucleus | nucleus | biology | biology | nuclear cell biology | nuclear cell biology | DNA replication | DNA replication | DNA repair | DNA repair | DNA | DNA | genome | genome | cell cycle control | cell cycle control | chromatin | chromatin | gene expression | gene expression | replication | replication | transcription | transcription | RNA | RNA | RNA interference | RNA interference | mRNA | mRNA | microRNA | microRNA | RNAi | RNAi

License

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STS.330 History and Anthropology of Medicine and Biology (MIT) STS.330 History and Anthropology of Medicine and Biology (MIT)

Description

This course explores recent historical and anthropological approaches to the study of medicine and biology. Topics include histories of bodies and embodiment in medicine; institutional and social genealogies and futures for genes and genomes; the role of science and medicine in racial formation; epidemics and emergent diseases; new reproductive technologies and socialities; the laboratory and field lives of animals, plants, microbes, molecules, and environments. This course explores recent historical and anthropological approaches to the study of medicine and biology. Topics include histories of bodies and embodiment in medicine; institutional and social genealogies and futures for genes and genomes; the role of science and medicine in racial formation; epidemics and emergent diseases; new reproductive technologies and socialities; the laboratory and field lives of animals, plants, microbes, molecules, and environments.

Subjects

historical medicine | historical medicine | medieval dissection | medieval dissection | gender | gender | visible human project | visible human project | genealogies | genealogies | genome | genome | biological kinship | biological kinship | biology of race | biology of race | race and disease | race and disease | emerging diseases | emerging diseases | human relationship with animals | human relationship with animals | reproductive technologies | reproductive technologies | therapeutics | therapeutics | bioprospecting | bioprospecting | climate change | climate change | environmental technology | environmental technology

License

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7.88J Protein Folding Problem (MIT) 7.88J Protein Folding Problem (MIT)

Description

This course focuses on the mechanisms by which the amino acid sequence of polypeptide chains (proteins), determine their three-dimensional conformation. Topics in this course include sequence determinants of secondary structure, the folding of newly synthesized polypeptide chains within cells, folding intermediates aggregation and competing off-pathway reactions, and the unfolding and refolding of proteins in vitro. Additional topics covered are the role of helper proteins such as chaperonins and isomerases, protein recovery problems in the biotechnology industry, and diseases found associated with protein folding defects. This course focuses on the mechanisms by which the amino acid sequence of polypeptide chains (proteins), determine their three-dimensional conformation. Topics in this course include sequence determinants of secondary structure, the folding of newly synthesized polypeptide chains within cells, folding intermediates aggregation and competing off-pathway reactions, and the unfolding and refolding of proteins in vitro. Additional topics covered are the role of helper proteins such as chaperonins and isomerases, protein recovery problems in the biotechnology industry, and diseases found associated with protein folding defects.

Subjects

amino acid sequence | amino acid sequence | polypeptide chains | polypeptide chains | sequence determinants | sequence determinants | folding | folding | synthesized polypeptide chains within cells | synthesized polypeptide chains within cells | unfolding and refolding of proteins in vitro | unfolding and refolding of proteins in vitro | folding intermediates aggregation | folding intermediates aggregation | competing off-pathway reactions | competing off-pathway reactions | chaperonins | chaperonins | isomerases | isomerases | helper proteins | helper proteins | protein recovery problems | protein recovery problems | biotechnology industry | biotechnology industry | protein folding defects | protein folding defects | 3-D conformation | 3-D conformation | globular proteins | globular proteins | fibrous proteins | fibrous proteins | kinetics | kinetics | in vitro refolding | in vitro refolding | pathways | pathways | in vivo folding | in vivo folding | synthesized proteins | synthesized proteins | aggregation | aggregation | protein misfolding | protein misfolding | human disease | human disease | protein folding | protein folding | genome sequences | genome sequences | 7.88 | 7.88 | 5.48 | 5.48 | 7.24 | 7.24 | 10.543 | 10.543

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7.03 Genetics (MIT) 7.03 Genetics (MIT)

Description

The principles of genetics with application to the study of biological function at the level of molecules, cells, and multicellular organisms, including humans. Structure and function of genes, chromosomes and genomes. Biological variation resulting from recombination, mutation, and selection. Population genetics. Use of genetic methods to analyze protein function, gene regulation and inherited disease. The principles of genetics with application to the study of biological function at the level of molecules, cells, and multicellular organisms, including humans. Structure and function of genes, chromosomes and genomes. Biological variation resulting from recombination, mutation, and selection. Population genetics. Use of genetic methods to analyze protein function, gene regulation and inherited disease.

Subjects

Population genetics | Population genetics | selection | selection | mutation | mutation | recombination | recombination | genomes | genomes | chromosomes | chromosomes | genes | genes

License

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8.592 Statistical Physics in Biology (MIT) 8.592 Statistical Physics in Biology (MIT)

Description

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; Considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.Technical RequirementsAny number of biological sequence comparison software tools can be used to import the .fna files found on this course site. Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; Considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.Technical RequirementsAny number of biological sequence comparison software tools can be used to import the .fna files found on this course site.

Subjects

Bioinformatics | Bioinformatics | DNA | DNA | gene finding | gene finding | sequence comparison | sequence comparison | phylogenetic trees | phylogenetic trees | biopolymers | biopolymers | DNA double helix | DNA double helix | secondary structure of RNA | secondary structure of RNA | protein folding | protein folding | protein motors | membranes | protein motors | membranes | cellular networks | cellular networks | neural networks | neural networks | evolution | evolution | statistical physics | statistical physics | molecular biology | molecular biology | deoxyribonucleic acid | deoxyribonucleic acid | genes | genes | genetics | genetics | gene sequencing | gene sequencing | phylogenetics | phylogenetics | double helix | double helix | RNA | RNA | ribonucleic acid | ribonucleic acid | force | force | motion | motion | packaging | packaging | protein motors | protein motors | membranes | membranes | biochemistry | biochemistry | genome | genome | optimization | optimization | partitioning | partitioning | pattern recognition | pattern recognition | collective behavior | collective behavior

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7.01SC Fundamentals of Biology (MIT) 7.01SC Fundamentals of Biology (MIT)

Description

Fundamentals of Biology focuses on the basic principles of biochemistry, molecular biology, genetics, and recombinant DNA. These principles are necessary to understanding the basic mechanisms of life and anchor the biological knowledge that is required to understand many of the challenges in everyday life, from human health and disease to loss of biodiversity and environmental quality. Fundamentals of Biology focuses on the basic principles of biochemistry, molecular biology, genetics, and recombinant DNA. These principles are necessary to understanding the basic mechanisms of life and anchor the biological knowledge that is required to understand many of the challenges in everyday life, from human health and disease to loss of biodiversity and environmental quality.

Subjects

amino acids | amino acids | carboxyl group | carboxyl group | amino group | amino group | side chains | side chains | polar | polar | hydrophobic | hydrophobic | primary structure | primary structure | secondary structure | secondary structure | tertiary structure | tertiary structure | quaternary structure | quaternary structure | x-ray crystallography | x-ray crystallography | alpha helix | alpha helix | beta sheet | beta sheet | ionic bond | ionic bond | non-polar bond | non-polar bond | van der Waals interactions | van der Waals interactions | proton gradient | proton gradient | cyclic photophosphorylation | cyclic photophosphorylation | sunlight | sunlight | ATP | ATP | chlorophyll | chlorophyll | chlorophyll a | chlorophyll a | electrons | electrons | hydrogen sulfide | hydrogen sulfide | biosynthesis | biosynthesis | non-cyclic photophosphorylation | non-cyclic photophosphorylation | photosystem II | photosystem II | photosystem I | photosystem I | cyanobacteria | cyanobacteria | chloroplast | chloroplast | stroma | stroma | thylakoid membrane | thylakoid membrane | Genetics | Genetics | Mendel | Mendel | Mendel's Laws | Mendel's Laws | cloning | cloning | restriction enzymes | restriction enzymes | vector | vector | insert DNA | insert DNA | ligase | ligase | library | library | E.Coli | E.Coli | phosphatase | phosphatase | yeast | yeast | transformation | transformation | ARG1 gene | ARG1 gene | ARG1 mutant yeast | ARG1 mutant yeast | yeast wild-type | yeast wild-type | cloning by complementation | cloning by complementation | Human Beta Globin gene | Human Beta Globin gene | protein tetramer | protein tetramer | vectors | vectors | antibodies | antibodies | human promoter | human promoter | splicing | splicing | mRNA | mRNA | cDNA | cDNA | reverse transcriptase | reverse transcriptase | plasmid | plasmid | electrophoresis | electrophoresis | DNA sequencing | DNA sequencing | primer | primer | template | template | capillary tube | capillary tube | laser detector | laser detector | human genome project | human genome project | recombinant DNA | recombinant DNA | clone | clone | primer walking | primer walking | subcloning | subcloning | computer assembly | computer assembly | shotgun sequencing | shotgun sequencing | open reading frame | open reading frame | databases | databases | polymerase chain reaction (PCR) | polymerase chain reaction (PCR) | polymerase | polymerase | nucleotides | nucleotides | Thermus aquaticus | Thermus aquaticus | Taq polymerase | Taq polymerase | thermocycler | thermocycler | resequencing | resequencing | in vitro fertilization | in vitro fertilization | pre-implantation diagnostics | pre-implantation diagnostics | forensics | forensics | genetic engineering | genetic engineering | DNA sequences | DNA sequences | therapeutic proteins | therapeutic proteins | E. coli | E. coli | disease-causing mutations | disease-causing mutations | cleavage of DNA | cleavage of DNA | bacterial transformation | bacterial transformation | recombinant DNA revolution | recombinant DNA revolution | biotechnology industry | biotechnology industry | Robert Swanson | Robert Swanson | toxin gene | toxin gene | pathogenic bacterium | pathogenic bacterium | biomedical research | biomedical research | S. Pyogenes | S. Pyogenes | origin of replication | origin of replication

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HST.512 Genomic Medicine (MIT) HST.512 Genomic Medicine (MIT)

Description

Includes audio/video content: AV lectures. This course reviews the key genomic technologies and computational approaches that are driving advances in prognostics, diagnostics, and treatment. Throughout the semester, emphasis will return to issues surrounding the context of genomics in medicine including: what does a physician need to know? what sorts of questions will s/he likely encounter from patients? how should s/he respond? Lecturers will guide the student through real world patient-doctor interactions. Outcome considerations and socioeconomic implications of personalized medicine are also discussed. The first part of the course introduces key basic concepts of molecular biology, computational biology, and genomics. Continuing in the informatics applications portion of the course, lec Includes audio/video content: AV lectures. This course reviews the key genomic technologies and computational approaches that are driving advances in prognostics, diagnostics, and treatment. Throughout the semester, emphasis will return to issues surrounding the context of genomics in medicine including: what does a physician need to know? what sorts of questions will s/he likely encounter from patients? how should s/he respond? Lecturers will guide the student through real world patient-doctor interactions. Outcome considerations and socioeconomic implications of personalized medicine are also discussed. The first part of the course introduces key basic concepts of molecular biology, computational biology, and genomics. Continuing in the informatics applications portion of the course, lec

Subjects

genomics | genomics | genomic medicine | genomic medicine | genetics | genetics | genomic measurement | genomic measurement | microarray | microarray | informatics | informatics | bioinformatics | bioinformatics | computational biology | computational biology | machine learning | machine learning | pharmacogenomics | pharmacogenomics | complex traits | complex traits | individual pharmacology | individual pharmacology | cancer diagnostics | cancer diagnostics | genetic disease | genetic disease | biomedical | biomedical | genomes | genomes | bioethics | bioethics | integrative genomics | integrative genomics | genomic technologies | genomic technologies

License

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6.877J Computational Evolutionary Biology (MIT) 6.877J Computational Evolutionary Biology (MIT)

Description

Why has it been easier to develop a vaccine to eliminate polio than to control influenza or AIDS? Has there been natural selection for a 'language gene'? Why are there no animals with wheels? When does 'maximizing fitness' lead to evolutionary extinction? How are sex and parasites related? Why don't snakes eat grass? Why don't we have eyes in the back of our heads? How does modern genomics illustrate and challenge the field? This course analyzes evolution from a computational, modeling, and engineering perspective. The course has extensive hands-on laboratory exercises in model-building and analyzing evolutionary data. Why has it been easier to develop a vaccine to eliminate polio than to control influenza or AIDS? Has there been natural selection for a 'language gene'? Why are there no animals with wheels? When does 'maximizing fitness' lead to evolutionary extinction? How are sex and parasites related? Why don't snakes eat grass? Why don't we have eyes in the back of our heads? How does modern genomics illustrate and challenge the field? This course analyzes evolution from a computational, modeling, and engineering perspective. The course has extensive hands-on laboratory exercises in model-building and analyzing evolutionary data.

Subjects

6.877 | 6.877 | HST.949 | HST.949 | computational approaches | computational approaches | evolutionary biology | evolutionary biology | evolutionary theory and inferential logic of evolution by natural selection | evolutionary theory and inferential logic of evolution by natural selection | computational and algorithmic implications and requirements of evolutionary models | computational and algorithmic implications and requirements of evolutionary models | whole-genome species comparison | whole-genome species comparison | phylogenetic tree construction | phylogenetic tree construction | molecular evolution | molecular evolution | homology and development | homology and development | optimization and evolvability | optimization and evolvability | heritability | heritability | disease evolution | disease evolution | detecting selection in human populations | and evolution of language | detecting selection in human populations | and evolution of language | extensive laboratory exercises in model-building and analyzing evolutionary data | extensive laboratory exercises in model-building and analyzing evolutionary data

License

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7.349 Stem Cells: A Cure or Disease? (MIT) 7.349 Stem Cells: A Cure or Disease? (MIT)

Description

Have you ever considered going to a pharmacy to order some new cardiomyocytes (heart muscle cells) for your ailing heart? It might sound crazy, but recent developments in stem cell science have made this concept not so futuristic. In this course, we will explore the underlying biology behind the idea of using stem cells to treat disease, specifically analyzing the mechanisms that enable a single genome to encode multiple cell states ranging from neurons to fibroblasts to T cells. Overall, we hope to provide a comprehensive overview of this exciting new field of research and its clinical relevance. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literat Have you ever considered going to a pharmacy to order some new cardiomyocytes (heart muscle cells) for your ailing heart? It might sound crazy, but recent developments in stem cell science have made this concept not so futuristic. In this course, we will explore the underlying biology behind the idea of using stem cells to treat disease, specifically analyzing the mechanisms that enable a single genome to encode multiple cell states ranging from neurons to fibroblasts to T cells. Overall, we hope to provide a comprehensive overview of this exciting new field of research and its clinical relevance. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literat

Subjects

stem cells | stem cells | stem cell therapy | stem cell therapy | cellular reprogramming | cellular reprogramming | transdifferentiation | transdifferentiation | pluripotency | pluripotency | epigenetics | epigenetics | genome-wide sequencing | genome-wide sequencing | transcription-mediated reprogramming | transcription-mediated reprogramming | embryonic stem cell technology | embryonic stem cell technology | transcription factors | transcription factors | chromatin structure | chromatin structure | H3K4me3 | H3K4me3 | H3K27me3 | H3K27me3 | histone deacetylase 1 | histone deacetylase 1 | RNAi screens | RNAi screens | Oct4 | Oct4 | cloning | cloning | Dolly | Dolly | in vitro differentiation | in vitro differentiation | regenerative medicine | regenerative medicine

License

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7.89J Topics in Computational and Systems Biology (MIT) 7.89J Topics in Computational and Systems Biology (MIT)

Description

This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments. The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB Ph.D. program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology. This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments. The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB Ph.D. program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology.

Subjects

Computational Biology | Computational Biology | Systems Biology | Systems Biology | Genomics | Genomics | Protein Function | Protein Function | Nucleic Acid Binding Factors | Nucleic Acid Binding Factors | microarray analysis | microarray analysis | genome-wide mapping | genome-wide mapping | gene expression | gene expression | evolutionary dynamics | evolutionary dynamics | sequencing | sequencing | translation | translation | network motifs | network motifs | pathway modeling | pathway modeling | synthetic biology | synthetic biology | metagenomics | metagenomics | signal transduction | signal transduction

License

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