* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Gene Expression
Genomic imprinting wikipedia , lookup
Protein moonlighting wikipedia , lookup
Gene expression wikipedia , lookup
Gene desert wikipedia , lookup
Gene expression profiling wikipedia , lookup
Point mutation wikipedia , lookup
List of types of proteins wikipedia , lookup
Non-coding DNA wikipedia , lookup
Promoter (genetics) wikipedia , lookup
Transcriptional regulation wikipedia , lookup
Molecular evolution wikipedia , lookup
Silencer (genetics) wikipedia , lookup
Gene regulatory network wikipedia , lookup
Gene Expression The problem: Biomedical Engineering is inherently “reverse engineering” requiring analysisfirst and synthesis second. (A good system has already been built.) Analysis at cell level has been reversed: Traditional: symptom to function to metabolite, to protein (often enzyme) to gene. Now: Gene (genomics) to protein (proteomics), to metabolite, to function. The interplay between the genome and the cell. The regulatory problem – extragenomic and gene-driven responses. Development via differentiation. The unidirectional hypothesis Signal transduction The Need for Quantification Massive amounts of qualitative information Genome (human – 3 109 nucleotides; ~40,000 genes): Introns and Exons Individual genes: promoters, operators, transcribed regions. Transcription Translation Protein processing Gene Networks Transcription factors Inducers, represssors, attenuators, anti-attenuators. The need for quantification. • • • • • A large signaling network Characterize “devices” Identify “connections” Little spatial segregation Physical systems use channels to direct signals; media are common to many channels • Biological systems use highly differentiated chemical complementation. The need for quantification. Complex objective functions Technical approaches • Scale I: Bioinformatics – Searching the genomic database – The ultimate goal is to link all sequences to their functions. – Interspecies: • look for highly conserved regions to infer basic behavior. • Use functionally identified sequences in one species to infer function in other species. • SNP’s • Polymorphic mutations • Multiple gene diseases Bioinformatics … • Intraspecies: • Difference between consensus genome and individual genomes. • Purpose (disease?) – driven investigation of differences among individuals. • Need for clinical database and familial symptomatic and genomic data. Bioinformatics … • Pattern-recognition techniques – Alon’s “motifs” Technical Approaches • Scale III: ‘Reverse’ physiology – Disease-related studies – Mechanisms (e.g. chemotaxis, apoptosis,specific differentiation steps) Technical Approaches • Scale II: Specifics in Search of Generalizations / Generalizations in Search of Specifics – Paradigm systems – Synthetic systems The Overall Goal • Guidance of research. – The ‘control’ hypothesis – Mechanistic design of experiments • Codification of biological knowledge – Quantification, numerical databases – Standard mechanisms (computational modules) • Synthesis.