Bioinformatics (general definition):    Area between Computer Sciences (Informatics) and Biology (genomics)     (or application of the tools of informatics to biology) Bioinformatics took off only with the availability of large amounts of genome information, thus a more narrow delineation might be:        Area between Informatics and Genomics Related areas: Computational biology, Cybernetics  Typically bioinformatics is considered to include: management of biological databanks, access to biological data, and extracting useful information from biological data. For more detailed discussion see Mark Gerstein's introduction slides 53ff

Discuss Gersteins's slides on "Is it bioinformatics or not".
Else:

• Developing new technologies for massively parallel sequencing, aka next generation sequencing techniques, usually are not part of bioinformatiics; however, it is very helpful to know about these techniques. Links that provide additional information are:
  
• Pac Bio sequencer (video),
  Oxford Nanopore,
  454 sequencing (diagram here),
  Ion torrent,
  Illumina/Solexa )
  paired end sequencing (figure from a nature article)

• Read through the slides on homology and on protein structure
• Would in your opinion maintaining a database on beetles that contains data on where was the beetle collected, its morphology, and where is it stored in the collection fall under bioinformatics?
• Would in your opinion determining the 3D structure of a protein using X-ray crystallography fall under bioinformatics?
• How many different proteins with length of 100 aa are theoretically possible?
• At most how many aa substitutions does one need to turn one of these sequence into an another one?
• Formulate a question that you could ask on Wednesday (things you didn't understand, anything you want to hear more details about).

• Read through the slides on protein structure or listen to the ">movie
• Read following entries in Wikipedia:
  • http://en.wikipedia.org/wiki/Protein_folding
  • http://en.wikipedia.org/wiki/Ramachandran_plot
• Fold an origami crane, write your name on the wings. We will use it as a flag in the class on Friday.
• If you want to keep personal copies of the things you do during the computer exercises, bring a laptop or memory stick to class on Friday.

What does Bioinformatics have to do with Molecular Evolution?  Problem: Application of first principles does not work (yet):  The following chain processes are (believed to be) mainly determined by the DNA sequence (plus other components of the cell which in turn are encoded by other parts of the genome). But at present it can at present not be simulated in a computer.   DNA sequence -> transcription -> translation -> protein folding -> protein function (catalytic and other properties) -> properties of the organism(s) -> properties of the population and community ecology (taking also the non biological environment into account) -> ... .   Most scientists believe that the principle of reductionism (plus new laws and relations emerging on each level) is true for this chain; however, this is clearly "in principle" only. Biology relies on this sequence to work more or less unambiguously (prions), but: At several steps along the way from DNA to function our understanding of the chemical and physical processes involved is so incomplete that prediction of protein function based on only a single DNA sequence is at present impossible (at least for a protein of reasonable size). Solution: Use evolutionary context: "Nothing in biology makes sense except in the light of evolution" Theodosius Dobzhansky Present day proteins evolved through substitution and selection from ancestral proteins. Related proteins have similar sequence AND similar structure AND similar function. In the above mantra "similar function" can refer to: identical function, similar function, e.g.: identical reactions catalyzed in different organisms; or same catalytic mechanism but different substrate (malic and lactic acid dehydrogenases); similar subunits and domains that are brought together through a (hypothetical) process called domain shuffling, e.g. nucleotide binding domains in hexokinase, myosin, HSP70, and ATPsynthases. The Size of Protein Sequence Space (back of the envelope calculation): Consider a protein of 600 amino acids. Assume that for every position there could be any of the twenty possible amino acid. Then the total number of possibilities is 20 choices for the first position times 20 for the second position times 20 to the third .... = 20 to the 600 = 4*10^780 different proteins possible with lengths of 600 amino acids. For comparison the universe contains only about 10^89 protons and has an age of about 5*10^17 seconds or 5*10^29 picoseconds. If every proton in the universe were a computer that explored one possible protein sequence per picosecond, we only would have explored 5*10^118 sequences, i.e. a negligible fraction of the possible sequences with length 600 (one in about 10^662). The following is based on observation and not on an a priori truth: If two proteins (not necessarily true for nucleotide sequences) show significant similarity in their primary sequence, they have shared ancestry, and probably similar function. (although some proteins acquired radically new functional assignments, lysozyme -> lense crystalline).  To date there is no example known where convergent evolution has let to significant similarity of the primary sequence (although here are examples where similar selection pressures have resulted in similar convergent substitutions in homologous proteins). THE REVERSE IS NOT TRUE: PROTEINS WITH THE SAME OR SIMILAR FUNCTION DO NOT ALWAYS SHOW SIGNIFICANT SEQUENCE SIMILARITY for one of two reasons: a)  they evolved independently (e.g. different types of nucleotide binding sites); or b)   they underwent so many substitution events that there is no readily detectable similarity remaining. In particular, PROTEINS WITH SHARED ANCESTRY DO NOT ALWAYS SHOW SIGNIFICANT SIMILARITY (reason: see B above); many recent advances concern the improved detection of similarity.