Under the Alfred P. Sloan Fellowship in Computational Biology, I have been afforded the opportunity to study phylogenetics--one of the most important and exciting disciplines in computational biology. A phylogeny depicts an evolutionary relationship among a set of organisms (or taxa). Typically, a phylogeny is represented by a binary tree, where modern organisms are placed at the leaves and ancestral organisms occupy internal nodes, with the edges of the tree denoting evolutionary relationships. The task of phylogenetics is to infer this tree from observations upon present-day organisms. Reconstructing phylogenies is a major component of modern research programs in many areas of biology and medicine, but it is enormously expensive. The most commonly used techniques attempt to solve NP-hard problems such as maximum likelihood and maximum parsimony, typically by bounded searches through an exponentially-sized tree-space. For example, there are over 13 billion possible trees for 13 organisms. Phylogenetic heuristics that quickly analyze large amounts of data accurately will revolutionize the biological field. This final report highlights my activities in phylogenetics during the two-year postdoctoral period at the University of New Mexico under Prof. Bernard Moret. Specifically, this report reports my scientific, community and professional activities as an Alfred P. Sloan Postdoctoral Fellow in Computational Biology.

Researchers interested in the history of the Indo-European family of languages have used a variety of methods to estimate the phylogeny of the family, and have obtained widely differing results. In this paper we explore the reconstructions of the Indo-European phylogeny obtained by using the major phylogeny estimation procedures on an existing database of 336 characters (including lexical, phonological, and morphological characters) for 24 Indo-European languages. Our study finds that the different methods agree in part, but that there are also several striking differences. We discuss the reasons for these differences, and make proposals with respect to phylogenetic reconstruction in historical linguistics.

The Research Network on "Interacting stochastic systems of high complexity" set up by the German Research Foundation aimed at exploring and developing connections between research in infinite-dimensional stochastic analysis, statistical physics, spatial population models from mathematical biology, complex models of financial markets or of stochastic models interacting with other sciences. This book presents a structured collection of papers on the core topics, written at the close of the 6-year programme by the research groups who took part in it. The structure chosen highlights the interweaving of certain themes and certain interconnections discovered through the joint work. This yields a reference work on results and methods that will be useful to all who work between applied probability and the physical, economic, and life sciences.

One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.

Phylogenetic reconstruction--the method by which biologists examine the relationship between living and extinct organisms in an effort to identify evolutionary pathways--has seen radical changes in the last ten years. But as rapid advances in mathematical, molecular, developmental, and cladistic techniques have greatly improved reconstruction efforts, they have also sparked controversy, especially with regard to the assumptions and data underlying the cladistic method. This book brings together contributions from a wide range of practitioners in order to find common ground. By examining numerous models from a variety of fields, the book serves as a guide to the latest methods of classification and phylogeny reconstruction and provides insights into the relative merits that each approach has to offer. In particular, developmental studies emerge as a significant factor in cladogram construction. Splendidly written and wide-ranging in scope, Models in Phylogeny Reconstruction will be welcomed by students and researchers in systematic and evolutionary biology.