Metabolic Engineering Working Group: "Metabolic Engineering is a new approach to understanding and using metabolic processes. As the name implies, ME is the targeted and purposeful alteration of metabolic pathways found in an organism in order to better understand and use cellular pathways for chemical transformation, energy transduction, and supramolecular assembly. Knowledge acquired from this research will benefit society in a number of ways, including the ability to modify biological pathways to produce biological substitutes for less desirable chemical processes; allowing greater agricultural production, permitting more efficient and safer energy production, and; providing better understanding of the metabolic basis for some medical conditions that could assist in the development of new cures."
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MS in Bioinformatics and Computational Biology, USF - Start: "Master's of Science in Bioinformatics and Computational Biology
The Masters Program in 'Bioinformatics and Computational Biology' represents a multi-college partnership and a truly interdisciplinary collaboration. Participating departments include the Departments of Biochemistry & Molecular Biology in the College of Medicine, Mathematics in the College of Arts and Sciences, Computer Sciences and Engineering and the Division of Biomedical Engineering in the College of Engineering, Epidemiology & Biostatistics in the College of Public Health and Information Systems & Decision Sciences in the College of Business Administration.
The Masters Program in Bioinformatics and Computational Biology was initiated and will be administered by the Department of Biochemistry and Molecular Biology in the College of Medicine. The program development has been supported by a grant from the Alfred P. Sloan Foundation.
The goal of the Masters Program in Bioinformatics and Computational Biology is to provide students enrolled in the program with high quality training and education that will prepare them for careers in science, industry, health care and education. The curriculum has been designed accordingly and provides the theoretical background, the practical training and, with the internships, the 'real life' experience, which will equip students with the essential tools for a successful career in the field of Bioinformatics and Computational Biology."
BILD94 - Bioinformatics: "What is Bioinformatics?
Bioinformatics:
computerized annotation of genomic and biological information and data (databases)
transformation and manipulation of these data (software tools)
computational analysis of biological data
Overall Aim of Bioinformatics:
provide biologically important predictions from annotated data and transformation / manipulation of these data
Databases:
Primary and added-value databases
Sequence vs organismic databases
'Federated' databases: global computer networks ... WWW
Software tools access multiple databases, often at different sites
Software tools (computer programs):
Software tools: sequence analysis, database construction and management, evolutionary relations, structural analyses, pathways, microarray analysis, proteomic analysis
Software tools integrated into databases
Key words from some of the review articles listed at end:
Finding genes, locating coding regions, predicting function: automate
Function, Evolution, Sequence, Structure (FESS relationships)
Metabolic genotype, phenotype, redundancy
Genes to Pathways; Genes to biological knowledge
Assigning gene sets to different species: homologs vs paralogs
Finding conserved proteins common to all life
Expression profiles, relation to metabolic pathways / genetic networks
Gene synteny between species: gene adjacency in genomes
The Need for Bioinformatics:
Whole Genome Analyses and Sequences
Experimental Analyses involving Thousands of Genes simultaneously
DNA Chips and Array Analyses
Expression Arrays
Comparative Analyses between Species and Strains
Proteomics: 'Proteome' of an Organism ... 2D gels, Mass Spec
Medica"
Peppered moth - EvoWiki: "Starting in about 1850 entomologists began to notice a dark morph of this moth (termed carbonaria), and a range of intermediately shaded variants (termed insularia). Over the next 50 years, the dark variety gradually became the most prevalent in regions downwind from large industrial centers, where soot and other air pollutants from factories darkened the bark of trees and killed most lichens. The rapidity and striking nature of the change drew scientific attention; in 1896 Tutt proposed that carbonaria might be better camouflaged than typica on polluted surfaces, and that therefore natural selection, in the form of relatively higher bird predation on typica might account for the spread of carbonaria in polluted regions. In 1924 J.B.S. Haldane calculated that the selection coefficient required to produce such a change must have been ~0.3, a selection coefficient much higher than had been previously thought likely for natural evolution. [Q: too technical?] "
Selfish gene - EvoWiki: "selfish gene is a metaphor and hypothesis, initially proposed as a natural law, for a type of gene selection, coined by Richard Dawkins in his book of the same name. In this genes are are considered as operating with behavioural 'selfishness' (specifically not the same as conscious or psychological selfishness nor an evolutionary trait itself) and are the fundamental units of selection as well as of inheritance. All higher level functions of organisms, which Dawkins calls vehicles, are due to and for the benefit of selfish genes. Evolution is the consequence of a long fight between rival gene variants or alleles, the more selfish being the more successful by natural selection and so effecting adaptive changes in vehicles that are beneficial to the further transmission of those selfish genes but not necessarily the vehicles themselves.
The purpose of the selfish gene metaphor is to explain how biological altruism is possible without group selection, but is sometimes mistaken for genetic determinism or sociobiology.
Richard Dawkins, The Selfish Gene, Oxford University Press, 1976 (New ed. 1989). "
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