Applications Using standard Bioinformatics applications.
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Transcript of Applications Using standard Bioinformatics applications.
Applications
Using standard Bioinformatics applications
Introduction
The overall plan for the regeneration of high quality annotation information as
contained in the EMBL disk-file ISTN501
figWHAT.eps
Scientific Background ToMer Operon
● Function
● Genetic Structure and Regulation
● Mobility Of The Mer Operon
The principal proteins and their functions
figPRINCIPLE.eps
Downloading The Raw DNA Sequence
Initial BLAST Sequence Similarity Search
Maxim 18.1
With BLAST scores, up is down and lower is better
http://opal.biology.gatech.edu/GeneMark/
GeneMark
The web-based interface to GeneMark as running at EBI
figEBIGENEBANK.eps
Using BLAST to identify specific sequences
Dealing with false negatives and missing proteins
Over predicted genes and false positives
http://www.expasy.org/swissmod/
Structural Prediction With SWISS-MODEL
Maxim 18.2
The major limitation of ``homology modelling'' is that homology to a known structure is needed
Alternatives to homology modelling
Modelling with SWISS-MODEL
The SWISS-MODEL predicted structure of ORF2/MerP
figORF2MERP.eps
The SWISS-MODEL predicted structure of ORF2/MerP, second version
figORF2MERP2.eps
The SWISS-MODEL predicted structure of ORF3/MerA (A)
figORF3MERAA.eps
The SWISS-MODEL predicted structure of ORF3/MerAB
figORF3MERAB.eps
The SWISS-MODEL predicted structure of ORF6/TNR5
figORF6TNR5.eps
DeepView as a Structural Alignment Tool
The ORF2 and ORF3_A structures loaded into DeepView prior to structural
alignment
figDEEPVIEW.eps
DeepView's Iterative Magic Fit dialogue box
figDEEPVIEWDIALOG.eps
Structural Alignment created using the DeepView's Iterative Magic Fit facility
figDEEPVIEWEXAMPLE.eps
Selecting the current ``layer'' in DeepView
figDEEPLAYER.eps
Possible Explanation Behind MerA/HMA Duplication Event
figPOSSIBLE.eps
The structural alignment of ORF3_B and the ``official'' Mercury Reductase X-ray
structure
figCYSTEINES.eps
Maxim 18.3
Homology modelling can only model protein sequences similar to those which are already
known
PROSITE and Sequence Motifs
Maxim 18.4
Searching large datasets with non-specific, short sequence fragments results in many false
positives
http://www.expasy.org/prosite/
http://www.ebi.ac.uk/interpro/
http://www.geneontology.org
● http://www.kegg.org
Using PROSITE patterns and matrices
Phylogenetics
A look at the HMA domain of MerA and MerP
------------------------------- -------------------------------SWISS-PROT IDs of MerP Proteins SWISS-PROT IDs of MerA Proteins------------------------------- -------------------------------MERP_ACICA MERA_ACICAMERP_ALCSP MERA_ALCSPMERP_PSEAE MERA_BACSRMERP_PSEFL MERA_ENTAGMERP_SALTI MERA_PSEAEMERP_SERMA MERA_PSEFLMERP_SHEPU MERA_SERMAMERP_SHIFL MERA_SHEPUMERA_SHIFLMERA_STAEPMERA_STRLIMERA_THIFE------------------------------- -------------------------------
The multiple sequence alignment of the example proteins
figLISTMERAMERP.eps
The EBI's tree graphical display
figTREE.eps
Maxim 18.5
Whenever you make a statement, call for more research (money)!
Maxim 18.6
Database annotation is hard to do well, so be prepared to update it on a regular basis
Maxim 18.7
Automation can be very helpful when creating annotation, but to achieve the highest quality,
humans are needed to make some value judgments
Maxim 18.8
Conclusions are based on the available data which, in this case, is the database annotation
(which may or may not be current)
Where To From Here?