Vineet Bafna

Genome Rearrangements and Sorting by Reversals

Sequence comparison in molecular biology is in the beginning of a major paradigm shift---a shift from gene comparison based on local mutations (i.e., insertions, deletions, and substitutions of nucleotides) to chromosome comparison based on global rearrangements (i.e., inversions and transpositions of fragments). The classical methods of sequence comparison do not work for global rearrangements, and little is known in computer science about the edit distance between sequences if global rearrangements are allowed. In the simplest form, the problem of gene rearrangements corresponds to sorting by reversals, i.e., sorting of an array using reversals of arbitrary fragments. Recently, Kececioglu and Sankoff gave the first approximation algorithm for sorting by reversals with guaranteed error bound 2 and identified open problems related to chromosome rearrangements. One of these problems is Gollans conjecture on the reversal diameter of the symmetric group. This paper proves the conjecture. Further, the problem of expected reversal distance between two random permutations is investigated. The reversal distance between two random permutations is shown to be very close to the reversal diameter, thereby indicating that reversal distance provides a good separation between related and nonrelated sequences in molecular evolution studies. The gene rearrangement problem forces us to consider reversals of signed permutations, as the genes in DNA could be positively or negatively oriented. An approximation algorithm for signed permutation is presented, which provides a performance guarantee of

Sorting by Transpositions

{3 over 2}

SNPs Problems, Complexity, and Algorithms

. Finally, using the signed permutations approach, an approximation algorithm for sorting by reversals is described which achieves a performance guarantee of

A polynomial time approximation scheme for minimum routing cost spanning trees

{7 over 4}

Haplotyping as perfect phylogeny: a direct approach.

.

On the Approximability of Numerical Taxonomy (Fitting Distances by Tree Metrics)

Sequence comparison in computational molecular biology is a powerful tool for deriving evolutionary and functional relationships between genes. However, classical alignment algorithms handle only local mutations (i.e., insertions, deletions, and substitutions of nucleotides) and ignore global rearrangements (i.e., inversions and transpositions of long fragments). As a result, the applications of sequence alignment to analyze highly rearranged genomes (i.e., herpes viruses or plant mitochondrial DNA) are rather limited. The paper addresses the problem of genome comparison versus classical gene comparison and presents algorithms to analyze rearrangements in genomes evolving by transpositions. In the simplest form the problem corresponds to sorting by transpositions, i.e., sorting of an array using transpositions of arbitrary fragments. We derive lower bounds on {em transposition distance} between permutations and present approximation algorithms for sorting by transpositions. The algorithms also imply a nontrivial upper bound on the transposition diameter of the symmetric group. Finally, we formulate two biological problems in genome rearrangements and describe the first {em algorithmic} steps toward their solution.

Comparative proteogenomics: Combining mass spectrometry and comparative genomics to analyze multiple genomes

Single nucleotide polymorphisms (SNPs) are the most frequent form of human genetic variation. They are of fundamental importance for a variety of applications including medical diagnostic and drug design. They also provide the highest-resolution genomic fingerprint for tracking disease genes. This paper is devoted to algorithmic problems related to computational SNPs validation based on genome assembly of diploid organisms. In diploid genomes, there are two copies of each chromosome. A description of the SNPs sequence information from one of the two chromosomes is called SNPs haplotype. The basic problem addressed here is the Haplotyping, i.e., given a set of SNPs prospects inferred from the assembly alignment of a genomic region of a chromosome, find the maximally consistent pair of SNPs haplotypes by removing data errors related to DNA sequencing errors, repeats, and paralogous recruitment. In this paper, we introduce several versions of the problem from a computational point of view. We show that the general SNPs Haplotyping Problem is NP-hard for mate-pairs assembly data, and design polynomial time algorithms for fragment assembly data.We give a network-flow based polynomial algorithm for the Minimum Fragment Removal Problem, and we show that the Minimum SNPs Removal problem amounts to finding the largest independent set in a weakly triangulated graph.

Deconvolution and Database Search of Complex Tandem Mass Spectra of Intact Proteins A COMBINATORIAL APPROACH

Given an undirected graph with nonnegative costs on the edges, the routing cost of any of its spanning trees is the sum over all pairs of vertices of the cost of the path between the pair in the tree. Finding a spanning tree of minimum routing cost is NP-hard, even when the costs obey the triangle inequality. We show that the general case is in fact reducible to the metric case and present a polynomial-time approximation scheme valid for both versions of the problem. In particular, we show how to build a spanning tree of an n-vertex weighted graph with routing cost at most

A Survey of Computational Methods for Determining Haplotypes

(1+epsilon)

Experimental selection of hypoxia-tolerant Drosophila melanogaster

of the minimum in time