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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

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 http://ocw.mit.edu/terms/index.htm

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20.020 Introduction to Biological Engineering Design (MIT) 20.020 Introduction to Biological Engineering Design (MIT)

Description

Includes audio/video content: AV special element video. This class is a project-based introduction to the engineering of synthetic biological systems. Throughout the term, students develop projects that are responsive to real-world problems of their choosing, and whose solutions depend on biological technologies. Lectures, discussions, and studio exercises will introduce (1) components and control of prokaryotic and eukaryotic behavior, (2) DNA synthesis, standards, and abstraction in biological engineering, and (3) issues of human practice, including biological safety; security; ownership, sharing, and innovation; and ethics. Enrollment preference is given to freshmen. This subject was originally developed and first taught in Spring 2008 by Drew Endy and Natalie Kuldell. Many of Drew's Includes audio/video content: AV special element video. This class is a project-based introduction to the engineering of synthetic biological systems. Throughout the term, students develop projects that are responsive to real-world problems of their choosing, and whose solutions depend on biological technologies. Lectures, discussions, and studio exercises will introduce (1) components and control of prokaryotic and eukaryotic behavior, (2) DNA synthesis, standards, and abstraction in biological engineering, and (3) issues of human practice, including biological safety; security; ownership, sharing, and innovation; and ethics. Enrollment preference is given to freshmen. This subject was originally developed and first taught in Spring 2008 by Drew Endy and Natalie Kuldell. Many of Drew's

Subjects

biology | biology | chemistry | chemistry | synthetic biology | synthetic biology | project | project | biotech | biotech | genetic engineering | genetic engineering | GMO | GMO | ethics | ethics | biomedical ethics | biomedical ethics | genetics | genetics | recombinant DNA | recombinant DNA | DNA | DNA | gene sequencing | gene sequencing | gene synthesis | gene synthesis | biohacking | biohacking | computational biology | computational biology | iGEM | iGEM | BioBrick | BioBrick | systems biology | systems biology

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 http://ocw.mit.edu/terms/index.htm

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2.72 Elements of Mechanical Design (MIT) 2.72 Elements of Mechanical Design (MIT)

Description

This is an advanced course on modeling, design, integration and best practices for use of machine elements such as bearings, springs, gears, cams and mechanisms. Modeling and analysis of these elements is based upon extensive application of physics, mathematics and core mechanical engineering principles (solid mechanics, fluid mechanics, manufacturing, estimation, computer simulation, etc.). These principles are reinforced via (1) hands-on laboratory experiences wherein students conduct experiments and disassemble machines and (2) a substantial design project wherein students model, design, fabricate and characterize a mechanical system that is relevant to a real world application. Students master the materials via problems sets that are directly related to, and coordinated with, the deliv This is an advanced course on modeling, design, integration and best practices for use of machine elements such as bearings, springs, gears, cams and mechanisms. Modeling and analysis of these elements is based upon extensive application of physics, mathematics and core mechanical engineering principles (solid mechanics, fluid mechanics, manufacturing, estimation, computer simulation, etc.). These principles are reinforced via (1) hands-on laboratory experiences wherein students conduct experiments and disassemble machines and (2) a substantial design project wherein students model, design, fabricate and characterize a mechanical system that is relevant to a real world application. Students master the materials via problems sets that are directly related to, and coordinated with, the deliv

Subjects

biology | biology | chemistry | chemistry | synthetic biology | synthetic biology | project | project | biotech | biotech | genetic engineering | genetic engineering | GMO | GMO | ethics | ethics | biomedical ethics | biomedical ethics | genetics | genetics | recombinant DNA | recombinant DNA | DNA | DNA | gene sequencing | gene sequencing | gene synthesis | gene synthesis | biohacking | biohacking | computational biology | computational biology | iGEM | iGEM | BioBrick | BioBrick | systems biology | systems biology | machine design | machine design | hardware | hardware | machine element | machine element | design process | design process | design layout | design layout | prototype | prototype | mechanism | mechanism | engineering | engineering | fabrication | fabrication | lathe | lathe | precision engineering | precision engineering | group project | group project | project management | project management | CAD | CAD | fatigue | fatigue | Gantt chart | Gantt chart

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 http://ocw.mit.edu/terms/index.htm

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20.453J Biomedical Information Technology (MIT) 20.453J Biomedical Information Technology (MIT)

Description

This course teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system desig This course teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system desig

Subjects

20.453 | 20.453 | 2.771 | 2.771 | HST.958 | HST.958 | imaging | imaging | medical imaging | medical imaging | metadata | metadata | molecular biology | molecular biology | medical records | medical records | DICOM | DICOM | RDF | RDF | OWL | OWL | SPARQL | SPARQL | SBML | SBML | CellML | CellML | semantic web | semantic web | BioHaystack | BioHaystack | database | database | schema | schema | ExperiBase | ExperiBase | genomics | genomics | proteomics | proteomics | bioinformatics | bioinformatics | computational biology | computational biology | clinical decision support | clinical decision support | clinical trial | clinical trial | microarray | microarray | gel electrophoresis | gel electrophoresis | diagnosis | diagnosis | pathway modeling | pathway modeling | XML | XML | SQL | SQL | relational database | relational database | biological data | biological data | ontologies | ontologies | drug development | drug development | drug discovery | drug discovery | drug target | drug target | pharmaceutical | pharmaceutical | gene sequencing | gene sequencing

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 http://ocw.mit.edu/terms/index.htm

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20.181 Computation for Biological Engineers (MIT) 20.181 Computation for Biological Engineers (MIT)

Description

This course covers the analytical, graphical, and numerical methods supporting the analysis and design of integrated biological systems. Topics include modularity and abstraction in biological systems, mathematical encoding of detailed physical problems, numerical methods for solving the dynamics of continuous and discrete chemical systems, statistics and probability in dynamic systems, applied local and global optimization, simple feedback and control analysis, statistics and probability in pattern recognition. An official course Web site and Wiki is maintained on OpenWetWare: 20.181 Computation for Biological Engineers. This course covers the analytical, graphical, and numerical methods supporting the analysis and design of integrated biological systems. Topics include modularity and abstraction in biological systems, mathematical encoding of detailed physical problems, numerical methods for solving the dynamics of continuous and discrete chemical systems, statistics and probability in dynamic systems, applied local and global optimization, simple feedback and control analysis, statistics and probability in pattern recognition. An official course Web site and Wiki is maintained on OpenWetWare: 20.181 Computation for Biological Engineers.

Subjects

Phylogenetic Inference | Phylogenetic Inference | Molecular Modeling | Molecular Modeling | Protein Design | Protein Design | Discrete Reaction Event Network Modeling | Discrete Reaction Event Network Modeling | Python | Python | genetics | genetics | DNA sequence | DNA sequence | genomics | genomics | gene sequencing | gene sequencing | UPGMA | UPGMA | Newick notation | Newick notation | parsimony | parsimony | downpass | downpass | uppass | uppass | jukes-cantor | jukes-cantor | invertase | invertase | genetic memory | genetic memory

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 http://ocw.mit.edu/terms/index.htm

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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.

Subjects

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

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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Attribution

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2.72 Elements of Mechanical Design (MIT)

Description

This is an advanced course on modeling, design, integration and best practices for use of machine elements such as bearings, springs, gears, cams and mechanisms. Modeling and analysis of these elements is based upon extensive application of physics, mathematics and core mechanical engineering principles (solid mechanics, fluid mechanics, manufacturing, estimation, computer simulation, etc.). These principles are reinforced via (1) hands-on laboratory experiences wherein students conduct experiments and disassemble machines and (2) a substantial design project wherein students model, design, fabricate and characterize a mechanical system that is relevant to a real world application. Students master the materials via problems sets that are directly related to, and coordinated with, the deliv

Subjects

biology | chemistry | synthetic biology | project | biotech | genetic engineering | GMO | ethics | biomedical ethics | genetics | recombinant DNA | DNA | gene sequencing | gene synthesis | biohacking | computational biology | iGEM | BioBrick | systems biology | machine design | hardware | machine element | design process | design layout | prototype | mechanism | engineering | fabrication | lathe | precision engineering | group project | project management | CAD | fatigue | Gantt chart

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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20.020 Introduction to Biological Engineering Design (MIT)

Description

This class is a project-based introduction to the engineering of synthetic biological systems. Throughout the term, students develop projects that are responsive to real-world problems of their choosing, and whose solutions depend on biological technologies. Lectures, discussions, and studio exercises will introduce (1) components and control of prokaryotic and eukaryotic behavior, (2) DNA synthesis, standards, and abstraction in biological engineering, and (3) issues of human practice, including biological safety; security; ownership, sharing, and innovation; and ethics. Enrollment preference is given to freshmen. This subject was originally developed and first taught in Spring 2008 by Drew Endy and Natalie Kuldell. Many of Drew's materials are used in this Spring 2009 version, and are i

Subjects

biology | chemistry | synthetic biology | project | biotech | genetic engineering | GMO | ethics | biomedical ethics | genetics | recombinant DNA | DNA | gene sequencing | gene synthesis | biohacking | computational biology | iGEM | BioBrick | systems biology

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

Site sourced from

https://ocw.mit.edu/rss/all/mit-alllifesciencescourses.xml

Attribution

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20.453J Biomedical Information Technology (MIT)

Description

This course teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system desig

Subjects

20.453 | 2.771 | HST.958 | imaging | medical imaging | metadata | molecular biology | medical records | DICOM | RDF | OWL | SPARQL | SBML | CellML | semantic web | BioHaystack | database | schema | ExperiBase | genomics | proteomics | bioinformatics | computational biology | clinical decision support | clinical trial | microarray | gel electrophoresis | diagnosis | pathway modeling | XML | SQL | relational database | biological data | ontologies | drug development | drug discovery | drug target | pharmaceutical | gene sequencing

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

Site sourced from

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20.181 Computation for Biological Engineers (MIT)

Description

This course covers the analytical, graphical, and numerical methods supporting the analysis and design of integrated biological systems. Topics include modularity and abstraction in biological systems, mathematical encoding of detailed physical problems, numerical methods for solving the dynamics of continuous and discrete chemical systems, statistics and probability in dynamic systems, applied local and global optimization, simple feedback and control analysis, statistics and probability in pattern recognition. An official course Web site and Wiki is maintained on OpenWetWare: 20.181 Computation for Biological Engineers.

Subjects

Phylogenetic Inference | Molecular Modeling | Protein Design | Discrete Reaction Event Network Modeling | Python | genetics | DNA sequence | genomics | gene sequencing | UPGMA | Newick notation | parsimony | downpass | uppass | jukes-cantor | invertase | genetic memory

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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