> MIT 10.555 : bioinformatics
methods | principles | applications
> spring 2003
Welcome to 10.555! Syllabus and Problem Set 1 have been posted.
Enrollment confirmation was sent to email@example.com. If you did not receive it, please notify Faisal (firstname.lastname@example.org).
slides from the 02.04.2003 lecture have been posted in the "course notes" section! Please peruse the 02.11.2003 set of course notes for the next lecture as well.
due to the Monday schedule of classes next Tuesday 02.18.2003, problem set 1 will be due the following Tuesday 02.25.2003.
slides from the 02.25.2003 lecture have been posted! problem set 2 was sent to email@example.com.
today's lecture has been rescheduled to monday 03.10.2003 2pm-5pm, room 56-154. please submit problem set 2 by this time.
slides from the 03.10.2003 and 03.11.2003 lectures have been posted! problem set 3 was sent to firstname.lastname@example.org.
since enrollment has reached steady state and email addresses have been confirmed, further announcements will be sent to email@example.com.
> lecturersGregory Stephanopoulos
> teaching assistantFaisal Reza
>the courseThis course provides an introduction to Bioinformatics. We define this field as the principles and computational methods aiming at the upgrade of the information content of the large volume of biological data generated by genome sequencing, as well as cell-wide measurements of gene expression (DNA microarrays), protein profiles (proteomics), metabolites and metabolic fluxes. Additionally, bioinformatics is concerned with whole organism data, especially human physiological variable measurements including organ function assessments, hormone levels, blood flow, neuronal activity etc., that characterize normal and pathophysiology. The overall goal of this data upgrade process is to elucidate cell function and physiology from a comprehensive set of measurements as opposed to using single markers of cellular function. Fundamentals from systems theory will be presented to define modeling philosophies and simulation methodologies for the integration of genomic and physiological data in the analysis of complex biological processes, e.g. genetic regulatory networks and metabolic pathways. Various computational methods will address a broad spectrum of problems in functional genomics and cell physiology, including; analysis of sequences, (alignment, homology discovery, gene annotation), gene clustering, pattern recognition/discovery in large-scale expression data, elucidation of genetic regulatory circuits, analysis of metabolic networks and signal transduction pathways. Applications of bioinformatics to metabolic engineering, drug design, and biotechnology will be also discussed.
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