How can we apply genetic algorithms to the field of bioinformatics? What kind of problems can genetic algorithms attempt to solve?
If this is the title of your new book, I am looking forward to read it ;-P
I think it's more likely that it's an essay question for University.
This is way too vague of a question. Perhaps this should be more of a discussion forum post. I'll change it to a forum post. I've also edited the question to be a bit more specific.
can you be more specific about the question Or,
this is the answer
the use of genetic algorithms in bioinformatics
The lab I spent most of my undergrad years in does work with GAs:
It's more the other way around, applying bioinformatics algorithms to genetic problems, e.g. phasing or assembly.
Given our use of heuristics and optimal solutions, I'd say the principal statement also holds true - we do use GAs.
I assume you are looking for examples of application:
An adaptive genetic algorithm for selection of blood-based biomarkers for prediction of Alzheimer's disease progression
Genetic algorithms applied to multi-class prediction for the analysis of gene expression data
GenClust: A genetic algorithm for clustering gene expression data
And to satisfy the character "R" in your tags:
GALGO: an R package for multivariate variable selection using genetic algorithms.
An additional example for analyzing cancer sequencing data is: SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing
Thank you for your guidance, I learned a lot。
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