Sequence Homology M M Dalkilic Ph D Monday

  • Slides: 16
Download presentation
Sequence Homology M. M. Dalkilic, Ph. D Monday, September 08, 2008 Class II Indiana

Sequence Homology M. M. Dalkilic, Ph. D Monday, September 08, 2008 Class II Indiana University, Bloomington, IN 1 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Outline �Sword of Damocles Lab I ? Skeptica Due l �New Reading Posted on

Outline �Sword of Damocles Lab I ? Skeptica Due l �New Reading Posted on Website �New Lab II / Homework Posted on Website �Readings [Mount] Chap 3, [R] Chaps 3 -4 �Most Important Aspect of Bioinformatics— homology search through sequence similarity 2 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Outline (cont’d) �Sequence Similarity o Most common Bioinformatics tool in use o One of

Outline (cont’d) �Sequence Similarity o Most common Bioinformatics tool in use o One of the most misunderstood tools in use o Requires a great deal of background in ancillary disciplines —especially computation 3 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Outline (cont’d) �Computational Elements of Sequence Similarity o Algorithms o Complexity o Recursion &

Outline (cont’d) �Computational Elements of Sequence Similarity o Algorithms o Complexity o Recursion & recurrence relations o Program strategies to reduce complexity of algorithms • Divide and Conquer • Dynamic Programming Sequence Similiarty (Computation) M. M. 4 Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Biochemcal Example How do we compare two “things” “representation of sequence of molecules” 5

Biochemcal Example How do we compare two “things” “representation of sequence of molecules” 5 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 © Glutumate Neg. charged R-group Aspartate Neg. Charged R-group

Computation Algorithm “process or rules for (esp. machine) calculations. The execution of an algorithm

Computation Algorithm “process or rules for (esp. machine) calculations. The execution of an algorithm must not include any subjective decisions, nor must it require the use of intuition or creativity” [Brassard & Bratley] 6 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation Algorithm When we set out to solve a problem, it is important to

Computation Algorithm When we set out to solve a problem, it is important to decide…on (1) size of the instances (2) representation (3) time/memory considerations 7 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation Algorithm (1) Size of the instances (2) Representation (3) Time/Memory considerations 8 Sequence

Computation Algorithm (1) Size of the instances (2) Representation (3) Time/Memory considerations 8 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation constant Upper bound starts Upper bound 9 Sequence Similiarty (Computation) M. M. Dalkilic,

Computation constant Upper bound starts Upper bound 9 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation 10 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University,

Computation 10 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation Recurrence relations—relations defined by (1) initial point (2) recursive (self-depreciation) 11 Sequence Similiarty

Computation Recurrence relations—relations defined by (1) initial point (2) recursive (self-depreciation) 11 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation 12 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University,

Computation 12 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation Though every recursive program can be written as as a while 13 Sequence

Computation Though every recursive program can be written as as a while 13 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation 14 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University,

Computation 14 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation 15 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University,

Computation 15 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Computation (Next Lecture) Divide and Conquer gives rise to Dynamic Programming—the approach used in

Computation (Next Lecture) Divide and Conquer gives rise to Dynamic Programming—the approach used in sequence comparison 16 Sequence Similiarty (Computation) M. M. Dalkilic, Ph. D So. I Indiana University, Bloomington, IN 2008 ©

Homology and Cladistics Homology Homology a shared traitHomology and Cladistics Homology Homology a shared trait
Homology versus Analogy Evolutionary Homology Serial Homology CriteriaHomology versus Analogy Evolutionary Homology Serial Homology Criteria
Homology and sequence alignment 1 Homology Similarity betweenHomology and sequence alignment 1 Homology Similarity between
Homology and Homologs Homology just means sequence similarityHomology and Homologs Homology just means sequence similarity
n Sequence homology similarity and comparison Homology isn Sequence homology similarity and comparison Homology is
Bioinformatics 4 Sequence Analysis Sequence Similarity and HomologyBioinformatics 4 Sequence Analysis Sequence Similarity and Homology
Homology Serial Homology Analogy 2 individuals structures haveHomology Serial Homology Analogy 2 individuals structures have
Homology modelling NMR Xray Homology Modelling Helices areHomology modelling NMR Xray Homology Modelling Helices are
Pertemuan 5 Sequence Diagram Sequence Diagram Sequence diagramPertemuan 5 Sequence Diagram Sequence Diagram Sequence diagram
Sequence organisation in conversation Sequence expansion Sequence expansionSequence organisation in conversation Sequence expansion Sequence expansion
Haitham Elmarakeby Sequence to Sequence Learning Sequence toHaitham Elmarakeby Sequence to Sequence Learning Sequence to
Sequence Diagrams CSIS 3600 Sequence Diagrams A sequenceSequence Diagrams CSIS 3600 Sequence Diagrams A sequence
Pairwise sequence Alignment Sequence Alignment Sequence analysis isPairwise sequence Alignment Sequence Alignment Sequence analysis is
Materi 2 Sequence Flowchart Sequence Sequence adalah uruturutanMateri 2 Sequence Flowchart Sequence Sequence adalah uruturutan
Sequence of Events Sequence of Events The sequenceSequence of Events Sequence of Events The sequence