Preliminary explanations.
Formal stage start. Problem definition.
ILP: first constraints and properties.
Review of the ILP formulation: corrections, objective function (min MDSs quantity), functions definitions (equivalence, inverse, MIC/MAC substring notation). LP solver: GUROBI.
Preprocessing phase (properties directly verifiable on the instance):
- Generate all possibile MDSs annotations
- Compute values of some variables
- Python or Ruby
- Constraints description or brief explanation;
- Group similar constraints;
- Correct every non-compliant constraint (e.g.
if
cannot be used, if not in the preprocessing phase); - Correct
Cov_{MIC}(i,j)
; - Remove useless and redunant constraints;
- Necessary variable and constraints: proof of correctness;
- Missing constraints (e.g. MDS_End > MDS_Start);
- Preprocessing: use
find
or Python'sre.search
on every MIC's substring to find if they exist in the MAC (Consider length > 3 as minimum for IESs and MDSs); - Thesis: should be understandable to CS undergraduates. 35-40 pages. Main elements:
- Introduction
- Prerequisites
- What I've learnt during the stage experience
- What I've done during the stage
Proof of correctness:
Being I an instance of the problem, P the correspondent ILP formulation, A any solution of P:
- Show how to use a solution of P (computed by Gurobi) to build a solution of the starting problem;
- Show that (1) is always possible.
- Produce a basic (solvable) version of the problem
-
DNA recombination through assembly graphs - Angela Angeleska, Nataša Jonoska, Masahico Saito
-
mds ies db
: a database of ciliate genome rearrangements - Jonathan Burns, Denys Kukushkin, Kelsi Lindblad, Xiao Chen, Natasa Jonoska and Laura F. Landweber -
MDS and IES annotation algorithm (Python) used in
mds ies db
- BLAST - Basic Local Alignment Search Tool
-
Programmed genome rearrangements in the ciliate Oxytricha - V. Talya Yerlici, Laura F. Landweber
-
RNA-guided DNA assembly - Angela Angeleska, Natasa Jonoska