A finding maximal clique algorithm for predicting loop of protein structure

In this paper we equate the problem of predicting the loop 3D structure in the comparative modeling to a problem of finding the maximal clique with the best weight. Each possible conformation of a residue in a loop sequence is represented as a node in a graph. Edges are then drawn between pairs of nodes that are consistent with each other. Edge and nodes are weighted according to some fixed criteria. Once the entire graph is constructed, all the maximal sets of cliques are found using an algorithm of artificial neural network models. The cliques with the best weights represent the optimal conformation of the region of loop sequence.     

Solving the Maximum Clique Problem with Symmetric Rank-One Non-negative Matrix Approximation

Finding complete subgraphs in a graph, that is, cliques, is a key problem and has many real-world applications, e.g., finding communities in social networks, clustering gene expression data, modeling ecological niches in food webs, and describing chemicals in a substance. The problem of finding the largest clique in a graph is a well-known difficult combinatorial optimization problem and is called the maximum clique problem. In this paper, we formulate a very convenient continuous characterization of the maximum clique problem based on the symmetric rank-one non-negative approximation of a given matrix and build a one-to-one correspondence between stationary points of our formulation and cliques of a given graph. In particular, we show that the local (resp. global) minima of the continuous problem corresponds to the maximal (resp. maximum) cliques of the given graph. We also propose a new and efficient clique finding algorithm based on our continuous formulation and test it on the DIMACS data sets to show that the new algorithm outperforms other existing algorithms based on the Motzkin–Straus formulation and can compete with a sophisticated combinatorial heuristic.     

Evolution towards the Maximum Clique

As is well known, the problem of finding a maximum clique in a graph isNP-hard. Nevertheless, NP-hard problems may have easy instances. This paperproposes a new, global optimization algorithm which tries to exploit favourabledata constellations, focussing on the continuous problem formulation: maximizea quadratic form over the standard simplex. Some general connections of thelatter problem with dynamic principles of evolutionary game theory areestablished. As an immediate consequence, one obtains a procedure whichconsists (a) of an iterative part similar to interior-path methods based on theso-called replicator dynamics; and (b) a routine to escape from inefficient,locally optimal solutions. For the special case of finding a maximum clique ina graph where the quadratic form arises from a regularization of the adjacencematrix, part (b), i.e. escaping from maximal cliques not of maximal size, isaccomplished with block pivoting methods based on (large) independent sets,i.e. cliques of the complementary graph. A simulation study is included whichindicates that the resulting procedure indeed has some merits.     

Algorithmic aspects of clique-transversal and clique-independent sets

A minimum clique-transversal set MCT(G) of a graph G=(V,E) is a set SV of minimum cardinality that meets all maximal cliques in G. A maximum clique-independent set MCI(G) of G is a set of maximum number of pairwise vertex-disjoint maximal cliques. We prove that the problem of finding an MCT(G) and an MCI(G) is NP-hard for cocomparability, planar, line and total graphs. As an interesting corollary we obtain that the problem of finding a minimum number of elements of a poset to meet all maximal antichains of the poset remains NP-hard even if the poset has height two, thereby generalizing a result of Duffas et al. (J. Combin. Theory Ser. A 58 (1991) 158–164). We present a polynomial algorithm for the above problems on Helly circular-arc graphs which is the first such algorithm for a class of graphs that is not clique-perfect. We also present polynomial algorithms for the weighted version of the clique-transversal problem on strongly chordal graphs, chordal graphs of bounded clique size, and cographs. The algorithms presented run in linear time for strongly chordal graphs and cographs. These mark the first attempts at the weighted version of the problem.     

Subgraph extraction and metaheuristics for the maximum clique problem

The maximum clique problem involves finding the largest set of pairwise adjacent vertices in a graph. The problem is classic but still attracts much attention because of its hardness and its prominent applications. Our work is based on the existence of an order of all the vertices whereby those belonging to a maximum clique stay close enough to each other. Such an order can be identified via the extraction of a particular subgraph from the original graph. The problem can consequently be seen as a permutation problem that can be addressed efficiently by metaheuristics. We first design a memetic algorithm (MA) for this purpose. Computational experiments conducted on the DIMACS benchmark instances clearly show that our MA not only outperforms existing genetic approaches, but it also compares very well to state-of-the-art algorithms regarding the maximal clique size found after different runs. Furthermore, we show that a hybridization of MA with an iterated local search (ILS) improves the stability of the algorithm. This hybridization (MA-ILS) permits to find two distinct maximal cliques of size 79 and one of size 80 for the C2000.9 instance of the DIMACS benchmark.     

Pseudo-Hamiltonian-connected graphs

Given a graph G and a positive integer k, denote by G[k] the graph obtained from G by replacing each vertex of G with an independent set of size k. A graph G is called pseudo-k Hamiltonian-connected if G[k] is Hamiltonian-connected, i.e., every two distinct vertices of G[k] are connected by a Hamiltonian path. A graph G is called pseudo Hamiltonian-connected if it is pseudo-k Hamiltonian-connected for some positive integer k. This paper proves that a graph G is pseudo-Hamiltonian-connected if and only if for every non-empty proper subset X of V(G), |N(X)|>|X|. The proof of the characterization also provides a polynomial-time algorithm that decides whether or not a given graph is pseudo-Hamiltonian-connected. The characterization of pseudo-Hamiltonian-connected graphs also answers a question of Richard Nowakowski, which motivated this paper.     

Multicolor routing in the undirected hypercube

An undirected routing problem is a pair (G,R) where G is an undirected graph and R is an undirected multigraph such that V(G)=V(R). A solution to an undirected routing problem (G,R) is a collection P of undirected paths of G (possibly containing multiple occurrences of the same path) such that edges of R are in one-to-one correspondence with the paths of P, with the path corresponding to edge {u,v} connecting u and v. We say that a collection of paths P is k-colorable if each path of P can be colored by one of the k colors so that the paths of the same color are edge-disjoint (each edge of G appears at most once in the paths of each single color). In the circuit-switched routing context, and in optical network applications in particular, it is desirable to find a solution to a routing problem that is colorable with as few colors as possible. Let Q_n denote the n-dimensional hypercube, for arbitrary n1. We show that a routing problem (Q_n,R) always admits a 4d-colorable solution where d is the maximum vertex degree of R. This improves over the 16d/2-color result which is implicit in the previous work of Aumann and Rabani [SODA95, pp. 567–576]. Since, for any positive d, there is a multigraph R of degree d such that any solution to (Q_n,R) requires at least d colors, our result is tight up to a factor of four. In fact, when d=1, it is tight up to a factor of two, since there is a graph of degree one (the antipodal matching) that requires two colors.     

Intersection graphs of paths in a tree

The intersection graph for a family of sets is obtained by associating each set with a vertex of the graph and joining two vertices by an edge exactly when their corresponding sets have a nonempty intersection. Intersection graphs arise naturally in many contexts, such as scheduling conflicting events, and have been widely studied.We present a unified framework for studying several classes of intersection graphs arising from families of paths in a tree. Four distinct classes of graphs arise by considering paths to be the sets of vertices or the edges making up the path, and by allowing the underlying tree to be undirected or directed; in the latter case only directed paths are allowed. Two further classes are obtained by requiring the directed tree to be rooted. We introduce other classes of graphs as well. The rooted directed vertex path graphs have been studied by Gavril; the vertex path graphs have been studied by Gavril and Renz; the edge path graphs have been studied by Golumbic and Jamison, Lobb, Syslo, and Tarjan.The main results are a characterization of these graphs in terms of their “clique tree” representations and a unified recognition algorithm. The algorithm repeatedly separates an arbitrary graph by a (maximal) clique separator, checks the form of the resultant nondecomposable “atoms,” and finally checks that each separation step is valid. In all cases, the first two steps can be performed in polynomial time. In all but one case, the final step is based on a certain two-coloring condition and so can be done efficiently; in the other case the recognition problem can be shown to be NP-complete since a certain three-coloring condition is needed.The strength of this unified approach is that it clarifies and unifies virtually all of the important known results for these graphs and provides substantial new results as well. For example, the exact intersecting relationships among these graphs, and between these graphs and chordal and perfect graphs fall out easily as corollaries. A number of other results, such as bounds on the number of (maximal) cliques, related optimization problems on these graphs, etc., are presented along with open problems.     

On a conjecture of Meyniel

A graph G is said to be very strongly perfect if for each induced subgraph H of G, each vertex of H belongs to a stable set that meets all maximal cliques of H. Meyniel proved that a graph is perfect if each of its odd cycles with at least five vertices contains at least two chords. Nowadays, such a graph is called a Meyniel graph. We prove that, as conjectured by Meyniel, a graph is very strongly perfect if and only if it is a Meyniel graph. We also design a polynomial-time algorithm which, given a Meyniel graph G and a vertex x of G, finds a stable set that contains x and meets all maximal cliques of G. We shall convert this algorithm into another polynomial-time algorithm which, given a Meyniel graph G, finds an optimal coloring of G, and a largest clique of G. Finally, we shall establish another property, related to perfection, of Meyniel graphs.     

路的字典积的邻和可区别边染色

图G的正常[k]-边染色σ是指颜色集合为[k]={1,2,…,k}的G的一个正常边染色.用w_σ（x）表示顶点x关联边的颜色之和,即w_σ（x）=∑_e∋x σ（e）,并称w_σ（x）关于σ的权.图G的k-邻和可区别边染色是指相邻顶点具有不同权的正常[k]-边染色,最小的k值称为G的邻和可区别边色数,记为χ'_∑（G）.现得到了路P_n与简单连通图H的字典积P_n[H]的邻和可区别边色数的精确值,其中H分别为正则第一类图、路、完全图的补图.     

Greedy maximum-clique decompositions

A greedy clique decomposition of a graph is obtained by removing maximal cliques from a graph one by one until the graph is empty. We have recently shown that any greedy clique decomposition of a graph of ordern has at mostn ²/4 cliques. A greedy max-clique decomposition is a particular kind cf greedy clique decomposition where maximum cliques are removed, instead of just maximal ones. In this paper, we show that any greedy max-clique decompositionC of a graph of ordern has, wheren(C) is the number of vertices inC.     

The completely positive and doubly nonnegative completion problems

We prove the following. Let G be an undirected graph. Every partially specified symmetric matrix, the graph of whose specified entries is G and each of whose fully specified submatrices is completely positive (equal to BB^T for some entrywise nonnegative matrix B), may be completed to a completely positive matrix if and only if G is a block-clique graph (a chordal graph in which distinct maximal cliques overlap in at most one vertex). The same result holds for matrices that are doubly nonnegative (entrywise nonnegative and positive semidefinite).     

A study of ACO capabilities for solving the maximum clique problem

This paper investigates the capabilities of the Ant Colony Optimization (ACO) meta-heuristic for solving the maximum clique problem, the goal of which is to find a largest set of pairwise adjacent vertices in a graph. We propose and compare two different instantiations of a generic ACO algorithm for this problem. Basically, the generic ACO algorithm successively generates maximal cliques through the repeated addition of vertices into partial cliques, and uses “pheromone trails” as a greedy heuristic to choose, at each step, the next vertex to enter the clique. The two instantiations differ in the way pheromone trails are laid and exploited, i.e., on edges or on vertices of the graph. We illustrate the behavior of the two ACO instantiations on a representative benchmark instance and we study the impact of pheromone on the solution process. We consider two measures—the re-sampling and the dispersion ratio—for providing an insight into the performance at run time. We also study the benefit of integrating a local search procedure within the proposed ACO algorithm, and we show that this improves the solution process. Finally, we compare ACO performance with that of three other representative heuristic approaches, showing that the former obtains competitive results.     

The complexity of irredundant sets parameterized by size

An irredundant set of vertices V′V in a graph G=(V,E) has the property that for every vertex uV′, N[V′−{u}] is a proper subset of N[V′]. We investigate the parameterized complexity of determining whether a graph has an irredundant set of size k, where k is the parameter. The interest of this problem is that while most “k-element vertex set” problems are NP-complete, several are known to be fixed-parameter tractable, and others are hard for various levels of the parameterized complexity hierarchy. Complexity classification of vertex set problems in this framework has proved to be both more interesting and more difficult. We prove that the k-element irredundant set problem is complete for W[1], and thus has the same parameterized complexity as the problem of determining whether a graph has a k-clique. We also show that the “parametric dual” problem of determining whether a graph has an irredundant set of size n−k is fixed-parameter tractable.     

Minimum rank of outerplanar graphs

The problem of finding the minimum rank over all symmetric matrices corresponding to a given graph has grown in interest recently. It is well known that the minimum rank of any graph is bounded above by the clique cover number, the minimum number of cliques needed to cover all edges of the graph. We generalize the idea of the clique cover number by defining the rank sum of a cover to be the sum of the minimum ranks of the graphs in the cover. Using this idea we obtain a combinatorial solution to the minimum rank problem for an outerplanar graph. As a consequence the minimum rank of an outerplanar graph is field independent and all outerplanar graphs have a universally optimal matrix. We also consider implications of the main result to the inverse inertia problem.     

Coloring the edges of a directed graph

Finding large cliques in a graph is an important problem in applied discrete mathematics. In directed graph a possible corresponding problem is finding large transitive subtournaments. It is well-known that coloring the graph speeds up the clique search in the undirected case. In this paper we propose coloring schemes to speed up the tournament search in the directed case. We prove two complexity results about the proposed colorings. A consequence of these results is that in practical computations we have to be content with approximate greedy coloring algorithms.     

Acyclic coloring of graphs without bichromatic long path

Let G be a graph of maximum degree Δ. A proper vertex coloring of G is acyclic if there is no bichromatic cycle. It was proved by Alon et al. [Acyclic coloring of graphs. Random Structures Algorithms, 1991, 2(3): 277−288] that G admits an acyclic coloring with O(Δ^4/3) colors and a proper coloring with O(Δ^{(k−1)/(k−2)}) colors such that no path with k vertices is bichromatic for a fixed integer k≥5. In this paper, we combine above two colorings and show that if k≥5 and G does not contain cycles of length 4, then G admits an acyclic coloring with O(Δ^{(k−1)/(k−2)}) colors such that no path with k vertices is bichromatic.     

Cohen–Macaulay monomial ideals of codimension 2

We give a structure theorem for Cohen–Macaulay monomial ideals of codimension 2, and describe all possible relation matrices of such ideals. In case that the ideal has a linear resolution, the relation matrices can be identified with the spanning trees of a connected chordal graph with the property that each distinct pair of maximal cliques of the graph has at most one vertex in common.     

Cycle contraction in oriented graphs

There exists an efficient algorithm for finding a branching of minimal weight among all branchings of maximal cardinality in an oriented graph. This algorithm is based on the cycle contraction technique and was developed by Tarjan. It is shown that this technique is applicable to a more general problem when the branching is subject to the additional condition that the set of vertices covered by this branching must be independent with respect to a given matroid.     

A reversal index for tournament matrices

Given a tournament matrix T, its reversal indexi_R(T), is the minimum k such that the reversal of the orientation of k arcs in the directed graph associated with T results in a reducible matrix. We give a formula for i_R(T) in terms of the score vector of T which generalizes a simple criterion for a tournament matrix to be irreducible. We show that i_R(T)≤[(n-1)/2] for any tournament matrix T of order n, with equality holding if and only if T is regular or almost regular, according as n is odd or even. We construct, for each k between 1 and [(n-1)/2], a tournament matrix of order n whose reversal index is k. Finally, we suggest a few problems.