Abstract Knowledge of kin relationships between members of wild animal populations has
broad application in ecology and evolution research by allowing the investigation of …

The origin and fate of new mutations within species is the fundamental process underlying
evolution. However, while much attention has been focused on characterizing the presence …

Understanding and correctly utilizing relatedness among samples is essential for genetic
analysis; however, managing sample records and pedigrees can often be error prone and …

We consider the problem of learning Bayesian networks (BNs) from complete discrete data.
This problem of discrete optimisation is formulated as an integer program (IP). We describe …

Background Genealogical research and ancestry testing are popular recreational activities
but little is known about the impact of the use of these services on clients' biological and …

Kinship testing based on genetic markers, as forensic short tandem repeats (STRs) and
single nucleotide polymorphisms (SNPs), has valuable practical applications. Paternity and …

The challenging task of learning structures of probabilistic graphical models is an important
problem within modern AI research. Recent years have witnessed several major algorithmic …

Bayesian network structure learning is the well-known computationally hard problem of
finding a directed acyclic graph structure that optimally describes given data. A learned …

Directed acyclic graphs are widely used to describe directional pairwise relations. Such
relations are estimated by reconstructing a directed acyclic graph's structure, which is …

Integer linear programming (ILP) is a versatile modeling and optimization technique that is
increasingly used in non-traditional ways in biology, with the potential to transform biological …