We propose a method for visualizing a set of related metabolic pathways using 2 2 D graph drawing. Interdependent, two-dimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant di#erences among the pathways. Layouts are determined by a global layout of the union of all pathway-representing graphs using a variant of the proven Sugiyama approach for layered graph drawing that allows edges to cross if they appear in di#erent graphs.

The reconstruction of ancestral genome architectures and gene orders from homologies between extant species is a longstanding problem, considered by both cytogeneticists and bioinformaticians. A comparison of the two approaches was recently investigated and discussed in a series of papers, sometimes with diverging points of view regarding the performance of these two approaches. We describe a general methodological framework for reconstructing ancestral genome segments from conserved syntenies in extant genomes. We show that this problem, from a computational point of view, is naturally related to physical mapping of chromosomes and benefits from using combinatorial tools developed in this scope. We develop this framework into a new reconstruction method considering conserved gene clusters with similar gene content, mimicking principles used in most cytogenetic studies, although on a different kind of data. We implement and apply it to datasets of mammalian genomes. We perform intensive theoretical and experimental comparisons with other bioinformatics methods for ancestral genome segments reconstruction. We show that the method that we propose is stable and reliable: it gives convergent results using several kinds of data at different levels of resolution, and all predicted ancestral regions are well supported. The results come eventually very close to cytogenetics studies. It suggests that the comparison of methods for ancestral genome reconstruction should include the algorithmic aspects of the methods as well

) S. Muthukrishnan Laxmi Parida y Abstract We initiate the complexity study of physical mapping with the emerging technology of Optical Mapping (OM) pioneered by the team lead by David Schwartz at the W. M. Keck Laboratory for Biomolecular Imaging, Dept of Chemistry, NYU. In currently popular electrophoretic approaches, information about the relative ordering of the fragments comprising the DNA molecule is lost, thus leading to difficult computational problems of composing the fragments in to a physical map depicting their relative order. In contrast, the relative ordering of the pieces is readily obtained in OM. However, OM faces serious technological challenges as it has low resolution and is faultprone. We take a combinatorial approach to the problem of constructing physical maps from the erroneous data generated by OM. We identify two abstract problems in this context, namely, the Exclusive Binary Flip-Cut and Exclusive Weighted Flip-Cut problems. For both, we present polynom...

A fundamental problem in computational biology is the construction of physical maps of chromosomes from hybridization experiments between unique probes and clones of chromosome fragments in the presence of error. Alizadeh, Karp, Weisser and Zweig (Algorithmica 13:1/2, 52--76, 1995) first considered a maximum-likelihood model of the problem that is equivalent to finding an ordering of the probes that minimizes a weighted sum of errors, and developed several effective heuristics. We show that by exploiting information about the end-probes of clones, this model can be formulated as a weighted Betweenness Problem. This affords the significant advantage of allowing the well-developed tools of integer linear-programming and branch-and-cut algorithms to be brought to bear on physical mapping, enabling us for the first time to solve small mapping instances to optimality even in the presence of high error. We also show that by combining the optimal solution of many small overlapping Betweenness...

Tettelin et. al. proposed a new method for closing the gaps in whole genome shotgun sequencing projects. The method uses a multiplex PCR strategy in order to minimize the time and eort required to sequence the DNA in the missing gaps. This procedure has been used in a number of microbial sequencing projects including Streptococcus pneumoniae and other bacteria. In this paper we describe a theoretical framework for this problem and propose an improved method that guarantees Address: Dept. of Computer and Information Sciences, Wachman Hall Rm 304 (038-24), Temple University, 1805 N Broad St, Philadelphia PA 19122-6094, USA. Research performed in part at DIMACS. Email: beigel@joda.cis.temple.edu. Supported in part by the National Science Foundation under grants CCR-9996021, and CCR-0049019. y Address: Dept. of Mathematics, Tel Aviv University, 69978 Tel Aviv, ISRAEL. Email: noga@math.tau.ac.il. z Email: apaydin@cs.stanford.edu. x Address: 4 Independence Way, Pri...

A fundamental problem in computational biology is the construction of physical maps of chromosomes from hybridization experiments between unique probes and clones of chromosome fragments in the presence of error. Alizadeh, Karp, Weisser and Zweig [AKWZ94] first considered a maximumlikelihood model of the problem that is equivalent to finding an ordering of the probes that minimizes a weighted sum of errors, and developed several effective heuristics. We show that by exploiting information about the endprobes of clones, this model can be formulated as a weighted Betweenness Problem. This affords the significant advantage of allowing the well-developed tools of integer linearprogramming and branch-and-cut algorithms to be brought to bear on physical mapping, enabling us for the first time to solve small mapping instances to optimality even in the presence of high error. We also show that by combining the optimal solution of many small overlapping Betweenness Problems, one can effectively...

A 0-1 matrix has the Consecutive Ones Property (C1P) if there is a permutation of its columns that leaves the 1’s consecutive in each row. The Consecutive Ones Submatrix (C1S) problem is, given a 0-1 matrix A, to find the largest number of columns of A that form a submatrix with the C1P property. Such a problem finds application in physical mapping with hybridization data in genome sequencing. Let (a, b)-matrices be the 0-1 matrices in which there are at most a 1’s in each column and at most b 1’s in each row. This paper proves that the C1S problem remains NP-hard for i) (2, 3)-matrices and ii) (3, 2)-matrices. This solves an open problem posed in a recent paper of Hajiaghayi and Ganjali [1]. We further prove that the C1S problem is polynomial-time 0.8-approximatable for (2, 3)-matrices in which no two columns are identical and 0.5-approximatable for (2, ∞)-matrices in general. we also show that the C1S problem is polynomial-time 0.5-approximatable for (3, 2)-matrices. However, there exists an ɛ> 0 such that approximating the C1S problem for (∞, 2)-matrices within a factor of n ɛ (where n is the number of columns of the input matrix) is NP-hard. Keywords: NP-hardness, approximation algorithm, consecutive ones property, consecutive ones submatrix, caterpillar spanning tree 1

We propose a method for visualizing a set of related metabolic pathways across organisms using 2 1/2 dimensional graph visualization. Interdependent, twodimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant differences among the pathways. The (dis)similarities between pathways are expressed by the Hamming distances of the underlying graphs which are used to compute a stacking order for the pathways. Layouts are determined by a global layout of the union of all pathway graphs using a variant of the proven Sugiyama approach for layered graph drawing. Our variant layout approach allows edges to cross if they appear in different graphs.

We introduce a new combinatorial formulation of chromosome physical-mapping by the sampling-without-replacement protocol. In this protocol, which is simple, inexpensive, and has been used to successfully map several organisms, equal-length clones are hybridized against a subset of the clones called probes, which are designed to form a maximal nonoverlapping clone-subset. The output of the protocol is the clone-probe hybridization matrix H. The problem of finding a maximum-likelihood reconstruction of the order of the probes along the chromosome in the presence of false positive and negative hybridization error is equivalent to finding the minimum number of entries of H to change to zeros so that the resulting matrix has at most 2 ones per row, and the consecutive-ones property across rows. This combinatorial problem, which we call 2-Consecutive-Ones Mapping, has a concise integer linear-programming formulation, to which we apply techniques from polyhedral combinatorics. The formulatio...

We present a new method for reconstructing the distances between probes in physical maps of chromosomes constructed by hybridizing pairs of clones under the so-called sampling-without-replacement protocol. In this protocol, which is simple, inexpensive, and has been used to successfully map several organisms, equal-length clones are hybridized against a clone-subset called the probes. The probes are chosen by a sequential process that is designed to generate a pairwise-nonoverlapping subset of the clones. We derive a likelihood function on probe spacings and orders for this protocol under a natural model of hybridization error, and describe how to reconstruct the most likely spacing for a given order under this objective using continuous optimization. The approach is tested on simulated data and real data from chromosome VI of Aspergillus nidulans. On simulated data we recover the true order and close to the true spacing; on the real data, for which the true order and spacing is unknow...