Learn about the common algorithms used in bioinformatics and how they can analyze biological data, such as DNA, ... Maximum Parsimony, Maximum Likelihood, and Bayesian Inference. Add your perspective.

This maximum likelihood approach was first proposed in the scAge method, which was developed to estimate the age of a samples from single cell methylation data. In contrast to scAge, our method is ...

Exascale Maximum Likelihood (ExaML) code for phylogenetic inference using MPI. This code implements the popular RAxML search algorithm for maximum likelihood based inference of phylogenetic trees. It ...

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem ...

Software accompaniment to. If you use the STELLS2 to run on larger data in a publication, please cite the following reference: Jingwen Pei and Yufeng Wu, STELLS2: Fast and Accurate Coalescent-based ...

The use of maximum likelihood estimation has become extremely popular in a vast number of fields. Statistical methods are paramount for analysing biological data and maximum likelihood estimation ...

This paper present the application of Maximum Likelihood Estimation (ML) algorithm for the cluster head selection with an unequal clustering protocol. In wireless sensor network it is generally found ...