Programs - Course Description

NEW COURSE

SPRING 2007

Chem/Bioinformatics

84.567 Section 201

Introduction to Computer Simulations of Biomolecules

Spring 2007

Instructor: Dr. Valeri Barsegov

Chem/Bioinformatics 84.567 will provide an introductory survey of the basis of theory/simulations of biomolecules. It is accessible to anyone who has completed two semesters of undergraduate chemistry. Topics/examples will be borrowed from modern biological chemistry and biophysics of single biomolecules. The course will be useful for senior undergraduates and beginning graduate students. Chem/Bioinformatics 84.567 will attempt to cultivate computational skills, which one needs to tackle current scientific problems of biology and biophysics. Students will learn to

• select appropriate computational methods for a particular problem
• model DNA, RNA and proteins using a computer
• calculate molecular characteristics accessible in current experiments
• perform statistical data analysis of experimental/simulation data

Lectures: 2:00pm - 3:15pm, Tuesday and Thursday

Instructor: Dr. Valeri Barsegov
Office: Room 402A, Olney Hall
Email: Valeri_Barsegov@uml.edu

Course Outline:

Part 1: Introduction to Biomolecules (10 lectures)

Part 2: Computer Simulations of Biomolecules (18 lectures)

Undergraduate  Courses

Biological Sciences  (visit the Registrar's website for information on schedule)

81.111.202 Principles of Biology I
Designed for students intending to pursue careers in the biological sciences, biotechnology or bioinformatics related areas. This is course introduces such topics as the chemical and physical basis of life, its evolution, diversity and distribution, as well as the interrelationships between life forms. The central theme of gene replication, translation, expression and selection will be emphasized as a unifying principle which determines and integrates structure and function at the cell, individual, population and community levels of organization.

81.112 Principles of Biology II
A continuation of the 81.111 in which students are introduced to such topics as molecular energy exchange in organisms (photosynthesis and respiratory metabolism). The common functional needs of support, locomotion, nutrition, internal communication and the maintenance of homeostasis are considered. Control and regulation of organisms at levels beyond the individual are considered through discussions of population and community ecology.

81.113 Principles of Biology I Laboratory
A series of field trips and laboratory exercises designed to introduce the student to concepts of the distribution and maintenance of life. Specific consideration is given to the diversity and organization of local ecosystems; the continuation of life is considered through exercises covering mitosis, meiosis, genetics and evolutionary biology. A weekly one-hour pre-laboratory recitation is an integral component of the course.

81.114 Principles of Biology II Laboratory
A series of laboratory experiments, analyses and exercises designed to introduce students to biological techniques and processes at the subcellular, cellular and organ systems levels. A weekly one-hour prelaboratory recitation is an integral component of the course.

81.335 Principles of Genetics
Prerequisites: 81.111, 81.112, and 84.222. Corequisite: 81.337. The theories of both classical and molecular genetics are explored with emphasis on the experimental evidence which has laid the foundation for contemporary understanding of genetics. Included is the nature of the genetic material, gene action, genetic recombination, gene regulation, gene interaction, the production and inheritance of genetic phenotypes, chromosomal mechanics, and the behavior of genes in populations.

81.337 Experimental Genetics
Corequisite: 81.335. Techniques of genetic analysis using molecular, prokaryotic and eukaryotic systems. There is an emphasis on problem solving and statistical methods.

81.419/519 Principles of Biochemistry I
Prerequisite: Organic Chemistry (Physical Chemistry is recommended). Primarily for M.S. students in Biological Sciences. Lectures and text assignments on the subjects of protein, carbohydrate, lipid, enzyme and membrane biochemistry will be supplemented with research journal readings.

81.420/520 Principles of Biochemistry II
Prerequisite: 81-519 or equivalent. This course is a continuation of 81-519 and will include discussions on all aspects of amino acid and nucleic acid metabolism and protein biosynthesis.

Chemistry (visit the Registrar's website for information on schedule)

84.121 Chemistry I
Corequisite: 84.123. Introduction to basic concepts of chemistry. Topics include chemical calculations, atomic structures, the periodic table, basic bonding theory, solutions, liquids, and gases.

84.122 Chemistry II
Prerequisite: 84.121 Corequisite: 84.124.  A continuation of 84.121. Topics include thermodynamics, kinetics, acids and bases, introduction to organic chemistry, chemical equilibrium, precipitation reactions, and electrochemistry.

84.123 Chemistry I Lab
Corequisite: 84.121. Experimental study of chemical principles and chemical transformation coordinated with topics considered in 84.121. Examines some of the more important reactions of elements, oxides, acids, bases, and salts. Other topics include chemical separation, purification, preparation of inorganic salts, quantitative determinations dealing with the formula of a compound, gas laws, and colligative properties. Stresses careful techniques and precise measurements. 

84.124 Chemistry II Lab
Corequisite: 84.122 A continuation of the laboratory study begun in 84.123 that is coordinated with topics of 84.122. Topics include: thermochemistry, kinetics, spectroscopy, titration, pH, equilibrium reaction and constants. Some aqueous solution reactions and organic reactions are examined. Accurate measurements and precise instrumental and apparatus operation are expected.

84.467/567 BioCheminformatics
The purpose of this course is to describe the structure and energetics of large biological molecules, how this data is obtained experimentally via instrumental approaches, modeled computationally, understood and potentially exploited.  Permission of Instructor is required.

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84.468    Computational Chemistry 
Prerequisite: Permission of instructor. This course will provide an overview of the use of computational approaches to describing the structure, energetics and physical properties of small molecules and large biologically important molecules such as nucleic acids and proteins.  General approaches to computational molecular modeling of proteins, nucleic acids and how they interact with small ligand molecules will be discussed.

Computer Science (visit the Registrar's website  for information on schedule)

91.309 Database I
This course surveys topics in database management systems. Topics include access methods, data models (network, hierarchical, relational, semantic and object oriented), query languages, database design, query optimization, concurrency control, recovery, security, integrity, client-server architecture and distributed database systems.  A database application project will be assigned.

91.510 Computational Methods in Molecular Biology
This is an advanced course in computer science, focusing on current problems in genomics. The emphasis is on identifying the appropriate combinatorial algorithmic solutions to specific biological problems. Primary topics will include DNA sequence assembly, DNA/protein sequence comparison, phylogenetic trees, RNA and protein folding, and microarray analysis. Prerequisites are knowledge of biology and algorithms. Undergraduates may take this course provided they satisfy the prerequisites. For more information feel free to contact Dr. Grinstein.

91.420/91.543 Artificial Intelligence
Prerequisites: 91.301 and 91.304 or consent of instructor
Do you ever wonder how to write a “smarter” program that could figure out for itself what to do given knowledge about cause and effect, that could learn from its experiences, or that could understand or write language people use, not artificial programming languages? If so, then artificial intelligence may be for you! In particular, in this course we will study:  what differentiates artificial intelligence programs, the history of  artificial intelligence, heuristic search techniques, predicate and  first-order logic representation and reasoning, planning, probabilistic  reasoning, natural language (i.e., English) understanding and generation,  agents and multi-agent programs, artificial vision, and more. Student  reviews from last year’s class were fantastic, and with last year’s class to  build on, this year’s class will be better.

Philosophy (visit the Registrar's website  for information on schedule)

45.401/501 Bioethics and Genetic Research
This course explains the rapidly advancing frontiers of biomedical and genetics research where science, ethics and public policy intersect.  Through readings, case studies, video clips, and class discussions students will analyze the ethical and public policy challenges arising from both the achievements of biomedical science and the changes within science itself.  They will also examine the practice and context of scientific research today and its relationship to the public and government agencies.

Graduate Courses

Biological Sciences

81.501,502 Selected Topics in Biology
Current topics in various fields of biology presented in lecture, seminar or discussion  groups. Subject matter may vary depending on interests of instructor and needs of students. May be repeated for credit when course content differs.

81.505 Bioinformatics
Prerequisites: 81.335 and 91.201 or permission of instructor. Corequisite: 81.507. Lectures cover the biological and computational basis of approaches to sequence alignment, gene detection, protein structure prediction, phylogenetic inference, analysis of microarray gene expression data, gene mapping, comparative genomics, genome evolution and genome maps. A term paper, seminar or poster presentation may be required. 

81.507 Bioinformatics Laboratory
Prerequisites: 81.335 and 91.201 or permission of instructor. Corequisite: 81.505. Computer-based analysis exercises and independent projects designed to showcase the capabilities and limitations of available computational tools used in genome research. Results of comparisons and evaluation of available methods will be summarized in lab reports.

81.519 Principles of Biochemistry I
Prerequisite: Organic Chemistry (Physical Chemistry is recommended). Primarily for M.S. students in Biological Sciences. Lectures and text assignments on the subjects of protein, carbohydrate, lipid, enzyme and membrane biochemistry will be supplemented with research journal readings.

81.520 Principles of Biochemistry II
Prerequisite: 81-519 or equivalent. This course is a continuation of 81-519 and will include discussions on all aspects of amino acid and nucleic acid metabolism and protein biosynthesis.

81.567 Recombinant DNA Techniques
Prerequisite: Permission of instructor. A study of the principles by which recombinant DNA technology is used to engineer genetically modified organisms as sources of useful products and as vehicles for basic research.  The course will begin by discussing the techniques used in applying recombinant DNA in prokaryotic and eukaryotic cells.  Students will be instructed in both experimental and computational methods to identify and isolate genes, design and produce recombinant DNA molecules, and introduce recombinant molecules into prokaryotic and eukaryotic cells.  Specific applications of recombinant DNA technology will then be discussed and will include such topics as production of heterologous proteins, vaccines and other therapeutic agents.  The production of both transgenic animals and plants will be addressed, as well as the applications of recombinant DNA to the human genome.  Finally, the students will be introduced to the regulatory was well as ethical issues involving the use of recombinant DNA technology.

Chemistry

84.550 Biochemistry
Prerequisite: Permission of Instructor. An advanced study of the structure and properties of proteins, nucleic acids, carbohydrates and lipids, including kinetics and mechanisms of enzyme action, and detailed description of metabolic pathways of carbohydrates.

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84.551 Biochemistry II
Prerequisite: 84.550 or Permission of Instructor. A continuation of 84.550 with emphasis on metabolic pathways of lipids, amino acids and nucleic acid, biosynthesis of proteins and selected topics in molecular biology and specialty areas of biochemistry.

84.570 Advanced Protein Chemistry
Prerequisite: Permission of Instructor. This course will involve an in-depth evaluation of protein structure and function.  Topics covered will include chemical properties of polypeptides, biosynthesis and degradation of proteins, evolutionary and genetic origins of protein sequence, as well as physical interactions of proteins and conformational properties of globular and membrane proteins.  Where appropriate, protein database search programs will aid in evaluation of sequence alignment, construction of evolutionary trees and prediction and visualization of three-dimensional structure. 

84.567/467 BioCheminformatics
Prerequisite: Permission of Instructor. The purpose of this undergraduate course it to describe the structure and energetics of large biological molecules how this data is obtained experimentally via instrumental approaches, modeled computationally, understood and potentially exploited. 

84.580 Advanced Analytical Biochemistry
Prerequisite: 84.550 or permission of instructor. Analytical biochemistry involves the separation, detection, and analysis of biological molecules. This course addresses advanced theory and applications of contemporary biochemical techniques and instrumentation. Topics covered include chromatographic and electrophoretic separation techniques, detection of biomolecules by spectroscopy and radiochemical methods, biological preparations, and structural analysis of proteins, nucleic acids, polysaccharides and lipids.

Computer Science

91.502 Foundations of Computer Science
Prerequisites: 91.500 or 92.322, 91.404 or 91.583, and at least one computer programming course or significant programming experience. An advanced introduction to theoretical computer science. This course will cover the fundamentals of automata, formal languages, and computability theory.

91.503 Algorithms
Prerequisites: 91.500, and 91.404 or 91.583. Co-requisite: 91.502. Abstract types, lists, trees, graphs, sets; relevant algorithms and their worst and average case analyses; fast transforms; polynomial, integer, and matrix algorithms; NP-completeness.

91.504 Advanced Algorithms
Topics in computability, complexity, and analysis of algorithms.

91.505 Formal Languages and Automata
Prerequisites: 91.502 and 91.503. Languages, grammars, and recognizers; Chomsky hierarchy; finite state machines and regular languages; PDAs and context-free languages; context-sensitive languages and their recognition; Turing Machines; open and unsolvable problems.

91.506 Theory of Computation
Prerequisites: 91.502 and 91.503. Examination of models of computation: Turing Machines, Markov algorithms, etc. Recursive function theory; selected topics.

91.507 Computational Algebra
Prerequisites: 91.502 and 91.503. Construction of software for algebraic problems: linear systems, eigenvalues; singular value decomposition; examination of currently available systems.

91.508 Parallel Algorithms
Prerequisites: 91.502 and 91.503. Topics in algorithm design and analysis; mapping and modeling; issues in complexity; lower bounds; models of parallel computation.

91.510 Computational Methods in Molecular Biology
This is an advanced course in computer science, focusing on current problems in genomics. The emphasis is on identifying the appropriate combinatorial algorithmic solutions to specific biological problems. Primary topics will include DNA sequence assembly, DNA/protein sequence comparison, phylogenetic trees, RNA and protein folding, and microarray analysis. Prerequisites are knowledge of biology and algorithms. Undergraduates may take this course provided they satisfy the prerequisites. For more information feel free to contact Dr. Grinstein.

91.521 A Discipline for Software Engineering
Prerequisites: Programming competence, preferably in C or C++; Recommended: knowledge of one spreadsheet and database system, and basic statistical methods. Practical experience with personal software process management methods, based on Humphrey's text of that name. Basic statistical methods, estimating and measurement techniques for program size, resource usage, schedules and errors.

91.522 Object-Oriented Analysis and Design
Prerequisites: 91.303 and 91.304 and significant C-language programming experience. Object-oriented techniques for analysis, specification, and design. Static information models and state-based dynamic behavior models applied to rapid prototyping projects that both use and implement object-oriented CASE tools. Syllabus for 91.522

91.523 Software Engineering I
Prerequisites: 91.522 and 91.502 and (301 or 531). Continuation of 91.522; a team-based project course that applies object-oriented methods to designing, implementing, and maintaining interactive and distributed software systems with emphasis on quality and reusability. (Undergraduates may substitute this course for 91.412.) Syllabus for 91.523

91.524 Software Engineering II: Validation and Verification
Prerequisites: 91.503 and 91.523 and familiarity with formal methods. Comparative analysis of program development support systems; specification and code generation techniques for testing and rapid prototyping of large software systems. Introduction to formal specifications and proof-of-correctness. Students will contribute to ongoing software tool development projects.

91.526 Project Management
Prerequisites: Undergraduate Computer Science background or CMS 63.408 or 63.490. Exposure to desktop microcomputers. Programming experience is helpful but not required. Integration of management and software-engineering concepts within a project management context; topics include general management techniques, models and metrics, case studies, and a significant class project.

91.527 Human-Computer Interaction
Prerequisites: Programming ability in C. An examination of the factors that contribute to well-engineered user interfaces for a wide variety of programs. Consideration of screen design, programming technique, and input devices. Review of human factors literature and development of skills for designing and evaluating user interfaces.

91.531 Programming Language Design
Prerequisites: 91.301 and 91.502. A one-semester course designed to provide students with hands-on understanding of the underlying concepts of programming languages, the principles of their design, and the fundamental methods for their implementation. An executable metalanguage such as Scheme or SML is used throughout the course, facilitating the design of high-level, concise interpreters that are easy to comprehend. The approach is analytical because the salient features of the imperative, functional, object-oriented, and logic programming paradigms are described in the executable metalanguage.

91.541 Scientific Visualization
Prerequisite: 91.546 or 91.427. Topics from the current literature. This course looks at classical and novel methodologies for the visualization of large amounts of data. Examples from the medical literature and from other areas of application will be studied in substantial detail.

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91.542 Vision and Imaging Systems
Prerequisite: 91.503. Fundamentals of vision. Mathematical techniques for signal processing; continuous and discrete images; binary images; segmentation; edges and edge finding; reflectance map; optical flow; photogrammetry; pattern classification; polyhedral objects; extended Gaussian images. A project will be required.

91.543/420 Artificial Intelligence
Graduate prerequisite: 91.502 or consent of instructor. Do you ever wonder how to write a “smarter” program that could figure out for itself what to do given knowledge about cause and effect, that could learn from its experiences, or that could understand or write language people use, not artificial programming languages? If so, then artificial intelligence may be for you! In particular, in this course we will study:  what differentiates artificial intelligence programs, the history of  artificial intelligence, heuristic search techniques, predicate and  first-order logic representation and reasoning, planning, probabilistic  reasoning, natural language (i.e., English) understanding and generation,  agents and multi-agent programs, artificial vision, and more. Student  reviews from last year’s class were fantastic, and with last year’s class to  build on, this year’s class will be better.

91.545 Knowledge Based Systems
Prerequisite: 91.543. Topics covered: heuristic searching techniques, languages for symbolic computing (LISP and Prolog), rule-based programming (forward and backward chaining, conflict resolution), production systems (CLIPS and OPS5), frames (hierarchies, attributes, rule integration), blackboard systems, uncertainty (Bayesian updating, Dempster-Shafer theory, and Fuzzy sets and Fuzzy logic), explanation facilities, practical techniques for expert systems development (design and implementation), maintenance of rule-based systems, knowledge based systems in real-time applications and validation, verification, testing, and reliability of expert systems.

91.546 Computer Graphics I
Prerequisites: 91.401 and permission of instructor. Introduction to the hardware, software and mathematics of 2- and 3-dimensional interactive computer graphics systems, including standards, modeling, transformations, hidden-surface removal, shading, and realism.

91.547 Computer Graphics II
Prerequisite: 91.546. Lighting models, photorealism, animation, constructive solid geometry, and distributed graphics.

91.548 Robotics I
Prerequisite: 91.503 and 91.515. Theory of robotics control, manipulation, and vision; current industrial techniques and applications; vision and sensors; factory of the future, and productivity.

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91.549 Robotics II
Prerequisite: 91.548. Intelligent manufacturing, expert systems for CAD/CAM, autonomous robots, computer integrated manufacturing, robotic planning, and topics in advanced sensors.
 

91.550 Topics in Data Mining
Prerequisite: Graduate or advanced undergraduate student in good standing. This course will cover current research topics in machine learning and artificial intelligence. Primarily, we will study: 1) increasing the autonomy of machine learning and artificial intelligence programs, 2) modeling systems and processes, 3) reasoning with these models and using them in machine learning and artificial intelligence programs, and 4) applying these programs to scientific databases. Coursework will involve reading and discussing papers, a semester project, and smaller projects involving modeling scientific domains and processes as well as the application of machine learning and artificial intelligence programs to scientific data sets. Projects will be done by groups of 2 or 3 students. Domain experts will be recruited to evaluate findings made by the groups, and some projects may result in findings of scientific interest. Prerequisites: graduate or advanced undergraduate student in good standing.

91.551 Computer Architecture
Prerequisites: 91.305 or 585 and 91.503. An advanced study of computer system organization. Topics include data-path design, control, ALU's, memory organization, distributed processing, theories of parallel computing, advanced architectures, computer communication.

91.553 Parallel Processing
Prerequisites: 91.305 and 91.308. A survey of parallel computer architectures, parallel programming languages, and parallel algorithms, with emphasis on solving practical problems with parallel computers. A final project, typically a substantial parallel program, is required. Usually offered during the Spring semester.

91.573 Database I
Prerequisites: 91.503 and 91.515. Study of various database models including hierarchical, network, relational, entity-relationship, and object-oriented models. This course also covers data design, integrity, security, concurrency, recovery, query processing, and distribution.

91.574 Database II
Prerequisite: 91.573. Continuation of Data Base I. Various issues in the implementation of database systems will be covered.

Mathematics

92.593 Experimental Design
Use of designed experiments to gain information faster and more efficiently than using trial and error, while controlling extraneous factors.  Factorial and fractional factorial design with each factor at two levels (the heart of modern off-line quality control).  Classical analysis of variance models including factorial, blocked and hierarchical (nested) designs.  Introduction to interlaboratory testing and response surface methodology.  Designing, carrying out, analyzing and reporting results of real experiments.

Philosophy

45.501/401 Bioethics and Genetic Research
This course explains the rapidly advancing frontiers of biomedical and genetics research where science, ethics and public policy intersect.  Through readings, case studies, video clips, and class discussions students will analyze the ethical and public policy challenges arising from both the achievements of biomedical science and the changes within science itself.  They will also examine the practice and context of scientific research today and its relationship to the public and government agencies.

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