Abstract

In this paper we analyze the topological properties of airport network of India (ANI) using graph theoretic approach. We show that such an analysis can be useful not only in planning the infrastructure and growth of the air-traffic connectivity, but also in managing the flow of transportation during emergencies such as accidental failure of the airport, close down of the airport due to unexpected climate changes, terrorist attacks, etc. Knowledge of the connectivity pattern and load on various routes can also help in making judicious decisions for reduction of flights to contain the spread of the infectious disease.

Abstract

The recent large scale advances in science and technology has resulted in accumulation of large amount of biological pathways data. Any metabolic pathway contains large number of enzymes, metabolites and reactions. To make sense of diverse data available on a system, one needs to correlate and analyze them as a whole. Motivated by the potential benefits of graph theory and its application in biological data, we discuss the automated reconstruction and analysis of metabolite network of Arabidopsis thaliana using concepts of graph theory. A.thaliana metabolite network was reconstructed and analysis of the global properties of its metabolite-centric graph shows that the network is small-world and scale-free in nature. The investigation of nodes with high centrality values like high degree and high betweeness in this network help in identifying important metabolites, reactions, etc. Newman’s modularity-based approach has been used in the analysis of the metabolite network of A. thaliana to identify pathway clusters, isolated pathways, and orphan metabolites or products. Our analysis on network representations helps in understanding the relationship between the metabolites, enzymes and reactions of metabolic pathways in A. thaliana.

Abstract

Graph comparisons, quantitative characterizations, computation of topological indices, clustering and partitioning are some of the major computations of graph that have yielded valuable results in various disciplines. Motivated by the potential benefits of graph theory application on biological data, we discuss the reconstruction and analysis of enzyme centric network of Arabidopsis thaliana using graph theory concepts. We had earlier constructed the metabolite network of Arabidopsis thaliana and witnessed the scale free and small world nature of the network. Compared to metabolites, the enzymes are more conserved in and across many pathways. So the aim of constructing the enzyme centric network is to see if the network follows similar network properties of the metabolite network and to look for additional details that a metabolite network cannot reveal. The enzyme flat file from KEGG FTP is used as the data set for the reconstruction of the enzyme centric network. We examined the network to find the relationship between topological connections among enzymes and their functions during evolution. The enzyme sequences of high degree and high betweenness enzymes belonged to ancient fold class and ancestry value showing evidence that they evolved very slowly.

Abstract

IGIPT is a web-based integrated platform for the identification of genomic islands (GIs). It incorporates thirteen parametric measures based on anomalous nucleotide composition on a single platform, thus improving the predictive power of a horizontally acquired region, since it is known that no single measure can absolutely predict a horizontally transferred region. The tool filters putative GIs based on standard deviation from genomic average and also provide raw output in MS excel format for further analysis. To facilitate the identification of various structural features, viz., tRNA integration sites, repeats, etc. in the vicinity of GIs, the tool provides option to extract the predicted regions and its flanking regions.

Abstract

Pattern discovery is at the heart of bioinformatics, and algorithms from computer science have been widely used for identifying biological patterns. The assumption behind pattern discovery approaches is that a pattern that occurs often enough in biological sequences/structures or is conserved across organisms is expected to play a role in defining the respective sequence’s or structure’s functional behavior and/or evolutionary relationships. The pattern recognition problem addressed here is at the genomic level and involves identifying horizontally transferred regions, called genomic islands. A horizontally transferred event is defined as the movement of genetic material between phylogenetically unrelated organisms by mechanisms other than parent to progeny inheritance. Increasing evidence suggests the importance of horizontal transfer events in the evolution of bacteria, influencing traits such as antibiotic resistance, symbiosis and fitness, virulence, and adaptation in general. In the genomic era, with the availability of large number of bacterial genomes, the identification of genomic islands also form the first step in the annotation of the newly sequenced genomes and in identifying the differences between virulent and non-virulent strains of a species. Considerable effort is being made in their identification and analysis and in this chapter a brief summary of various approaches used in the identification and validation of horizontally acquired regions is discussed.

Abstract

We study the problem of secure message transmission (SMT) in asynchronous directed graphs, where an unbounded Byzantine adversary can corrupt some subset of nodes specified via an adversary structure. We focus on the particular variant (0, δ)-SMT, where the message remains perfectly private, but there is a small chance that the receiver R may not obtain it. This variant can be of two kinds: Monte Carlo - where R may output an incorrect message with small probability; and Las Vegas - where R never outputs an incorrect message. For a Monte Carlo (0, δ)-SMT protocol to exist in an asynchronous directed graph, we show that the minimum connectivity required in the network does not decrease even when privacy of the message being transmitted is not required. In the case of Las Vegas (0, δ)-SMT, we show that the minimum connectivity required matches exactly with the minimum connectivity requirements of the zero-error variant of SMT – (0, 0)-SMT. For a network that meets the minimum connectivity requirements, we provide a protocol efficient in the size of the graph and the adversary structure. We also provide a protocol efficient in the size of the graph for an important family of graphs, when the adversary structure is threshold.

Abstract

In this paper, we give approximate algorithms for privacy preserving distance based outlier detection for both horizontal and vertical distributions, which scale well to large datasets of high dimensionality in comparison with the existing techniques. In order to achieve efficient private algorithms, we introduce an approximate outlier detection scheme for the centralized setting which is based on the idea of Locality Sensitive Hashing. We also give theoretical and empirical bounds on the level of approximation of the proposed algorithms.

Abstract

We consider AESOP Task as Topic based evaluation of information content. Means at first stage, we identify the topics covered in given model/reference summary and calculate their importance. At the next stage, we calculate the information coverage in test/machine generated summary, wrt every identified topic. We use the local importance of words in calculation of importance of topics. From experiments it is clear that use of different methods for identification of topics and calculation of information coverage in test documents wrt every identified topic, have different effect on the result. It is important to note that our devised system do not require any linguistic support or learning or training in entire execution of the system.

Abstract

In this paper, we give an approximate algorithm for distance based outlier detection using Locality Sensitive Hashing (LSH) technique. We propose an algorithm for the centralized case wherein the entire dataset is locally available for processing. However, in case of very large datasets collected from various input sources, often the data is distributed across the network. Accordingly, we show that our algorithm can be effectively extended to a constant round protocol with low communication costs, in a distributed setting with horizontal partitioning.

Abstract

Three decades ago, Pease et al. introduced the problem of Byzantine Agreement [PSL 80] where nodes need to maintain a consistent view of the world in spite of the challenge posed by Byzantine faults. Subsequently, it is well known that Byzantine agreement over a completely connected synchronous network of n nodes tolerating up to t faults is (efficiently) possible if and only if t < n/3. Pease et al. further empowered the nodes with the ability to authenticate themselves and their messages and proved that agreement in this new model (popularly known as authenticated Byzantine agreement (ABA)) is possible if and only if t < n. (which is a huge improvement over the bound of t < n/3 in the absence of authentication for the same functionality). To understand the utility, potential and limitations of using authentication in distributed protocols for agreement, Gupta et al. [GGBS10] studied ABA in new light. They generalize the existing models and thus, attempt to give a unified theory of agreements over the authenticated and non-authenticated domains. In this paper we extend their results to synchronous (undirected) networks and give a complete characterization of agreement protocols. As a corollary, we show that agreement can be strictly easier than all-pair point-to-point communication. It is well known that in a synchronous network over n nodes of which up to any t are corrupted by a Byzantine adversary, BA is possible only if all pair point-to-point reliable communication is possible [Dol82, DDWY93]. Thus, a folklore in the area is that maintaining global consistency (agreement) is at least as hard as the problem of all pair point-to-point communication. Equivalently, it is widely believed that protocols for BA over incomplete networks exist only if it is possible to simulate an overlay-ed complete network. Surprisingly, we show that the folklore is not always true. Thus, it seems that agreement protocols may be more fundamental to distributed computing than reliable communication.