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These pipelines are used to better understand the genetic basis of disease, unique adaptations, desirable properties (especially in agricultural species), or differences between populations. Bioinformatics also includes proteomics , which tries to understand the organizational principles within nucleic acid and protein sequences.
The concept of biological computation proposes that living organisms perform computations, and that as such, abstract ideas of information and computation may be key to understanding biology.
Hierarchical algorithms find successive clusters using previously established clusters, whereas partitional algorithms determine all clusters at once. Hierarchical algorithms can be agglomerative (bottom-up) or divisive (top-down). Agglomerative algorithms begin with each element as a separate cluster and merge them in successively larger clusters.
To implement the algorithm above, explicit formulas are required for the gradient of the function ((,),) where the function is (, ′) = | ′ |. The learning algorithm can be divided into two phases: propagation and weight update.
In biology supervised learning can be helpful when we have data that we know how to categorize and we would like to categorize more data into those categories. Diagram showing a simple random forest. A common supervised learning algorithm is the random forest, which uses numerous decision trees to train a model to classify a dataset. Forming ...
Different algorithms in evolutionary computation may use different data structures to store genetic information, and each genetic representation can be recombined with different crossover operators. Typical data structures that can be recombined with crossover are bit arrays , vectors of real numbers, or trees .
Mathematical and theoretical biology, or biomathematics, is a branch of biology which employs theoretical analysis, mathematical models and abstractions of living organisms to investigate the principles that govern the structure, development and behavior of the systems, as opposed to experimental biology which deals with the conduction of ...
Computational phylogenetics, phylogeny inference, or phylogenetic inference focuses on computational and optimization algorithms, heuristics, and approaches involved in phylogenetic analyses. The goal is to find a phylogenetic tree representing optimal evolutionary ancestry between a set of genes, species, or taxa.