On a Space-Optimal Distributed Traversal Algorithm

2001 ◽  
pp. 216-228
Author(s):  
Sébastien Tixeuil
Keyword(s):  
Traversal Algorithm

scholarly journals On the complexity of haplotyping a microbial community

2020 ◽  
Author(s):  
Samuel M Nicholls ◽  
Wayne Aubrey ◽  
Kurt De Grave ◽  
Leander Schietgat ◽  
Christopher J Creevey ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Community Sample ◽  
Population Level ◽  
Single Individual ◽  
Metagenomic Sample ◽  
Potential Benefits ◽  
Software Implementations ◽  
Occurrence Matrix ◽  
Number Of Individuals ◽  
Traversal Algorithm

Abstract Motivation Population-level genetic variation enables competitiveness and niche specialization in microbial communities. Despite the difficulty in culturing many microbes from an environment, we can still study these communities by isolating and sequencing DNA directly from an environment (metagenomics). Recovering the genomic sequences of all isoforms of a given gene across all organisms in a metagenomic sample would aid evolutionary and ecological insights into microbial ecosystems with potential benefits for medicine and biotechnology. A significant obstacle to this goal arises from the lack of a computationally tractable solution that can recover these sequences from sequenced read fragments. This poses a problem analogous to reconstructing the two sequences that make up the genome of a diploid organism (i.e. haplotypes), but for an unknown number of individuals and haplotypes. Results The problem of single individual haplotyping (SIH) was first formalised by Lancia et al. in 2001. Now, nearly two decades later, we discuss the complexity of “haplotyping” metagenomic samples, with a new formalisation of Lancia et al’s data structure that allows us to effectively extend the single individual haplotype problem to microbial communities. This work describes and formalizes the problem of recovering genes (and other genomic subsequences) from all individuals within a complex community sample, which we term the metagenomic individual haplotyping (MIH) problem. We also provide software implementations for a pairwise single nucleotide variant (SNV) co-occurrence matrix and greedy graph traversal algorithm. Availability and implementation Our reference implementation of the described pairwise SNV matrix (Hansel) and greedy haplotype path traversal algorithm (Gretel) are open source, MIT licensed and freely available online at github.com/samstudio8/hansel and github.com/samstudio8/gretel, respectively.

scholarly journals Relatedness and TBox-Driven Rule Learning in Large Knowledge Bases

2020 ◽  
Vol 34 (03) ◽  
pp. 2975-2982
Author(s):  
Giuseppe Pirrò
Keyword(s):  
Quality Assessment ◽  
Rule Learning ◽  
Semantic Relatedness ◽  
Knowledge Bases ◽  
The Body ◽  
Traversal Algorithm

We present RARL, an approach to discover rules of the form body ⇒ head in large knowledge bases (KBs) that typically include a set of terminological facts (TBox) and a set of TBox-compliant assertional facts (ABox). RARL's main intuition is to learn rules by leveraging TBox-information and the semantic relatedness between the predicate(s) in the atoms of the body and the predicate in the head. RARL uses an efficient relatedness-driven TBox traversal algorithm, which given an input rule head, generates the set of most semantically related candidate rule bodies. Then, rule confidence is computed in the ABox based on a set of positive and negative examples. Decoupling candidate generation and rule quality assessment offers greater flexibility than previous work.

A state traversal algorithm using a state covariance matrix

1993 ◽  
Author(s):  
Akira Motohara ◽  
Toshinori Hosokawa ◽  
Michiaki Muraoka ◽  
Hidetsugu Maekawa ◽  
Kazuhiro Kayashima ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
Traversal Algorithm

An Efficient Traversal Algorithm for Large Hypergraphs and its Applications for Graph Analysis

2017 ◽  
Vol 23 (8) ◽  
pp. 492-497
Author(s):  
Chungmo Ryu ◽  
Junghyuk Seo ◽  
Myoung Ho Kim
Keyword(s):  
Graph Analysis ◽  
Traversal Algorithm

scholarly journals Test Case Generation for UML Behavioral Diagram by Traversal Algorithm

2019 ◽  
Vol 8 (10) ◽  
pp. 3262-3266
Keyword(s):  
Accurate Result ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Sequence Diagrams ◽  
Research Focus ◽  
Activity Diagram ◽  
Path Coverage ◽  
The Comparative Study ◽  
Traversal Algorithm

Software testing play crucial role in the software development as it consumes lot of time and resources. However testing process needs to be more efficiently done because overall software quality relies upon good testing approach. The present research focus on generation of test cases from UML diagrams. The combination graph is made by using activity and sequence diagrams. These diagrams proves to be more efficient as activity diagram gives the dynamic behavior of the model and sequence diagram is used to understand detailed functionality of the system. In this paper, a combined approach using Breadth first and depth first search is proposed which will generate expected test cases. The comparative study is done for test case generation using BFS and DFS algorithm and the result proves that the DFS traversal algorithm provides more accurate result for path coverage.

scholarly journals Exploring graph traversal algorithms in graph-based molecular generation

2021 ◽  
Author(s):  
Rocío Mercado ◽  
Esben Bjerrum ◽  
Ola Engkvist
Keyword(s):  
Natural Products ◽  
Search Algorithm ◽  
Molecular Graph ◽  
Molecular Shape ◽  
Generative Models ◽  
Training Data ◽  
Depth First Search ◽  
Graph Traversal ◽  
The Impact ◽  
Traversal Algorithm

Here we explore the impact of different graph traversal algorithms on molecular graph generation. We do this by training a graph-based deep molecular generative model to build structures using a node order determined via either a breadth- or depth-first search algorithm. What we observe is that using a breadth-first traversal leads to better coverage of training data features compared to a depth-first traversal. We have quantified these differences using a variety of metrics on a dataset of natural products. These metrics include: percent validity, molecular coverage, and molecular shape. We also observe that using either a breadth- or depth-first traversal it is possible to over-train the generative models, at which point the results with the graph traversal algorithm are identical

scholarly journals Cayley and Tutte polytopes

2012 ◽  
Vol DMTCS Proceedings vol. AR,... (Proceedings) ◽  
Author(s):  
Matjaž Konvalinka ◽  
Igor Pak
Keyword(s):  
Complete Graph ◽  
Tutte Polynomial ◽  
Convex Hulls ◽  
Connected Graphs ◽  
Labeled Trees ◽  
Graph Traversal ◽  
International Audience ◽  
Search Graph ◽  
Traversal Algorithm

International audience Cayley polytopes were defined recently as convex hulls of Cayley compositions introduced by Cayley in 1857. In this paper we resolve Braun's conjecture, which expresses the volume of Cayley polytopes in terms of the number of connected graphs. We extend this result to a two-variable deformations, which we call Tutte polytopes. The volume of the latter is given via an evaluation of the Tutte polynomial of the complete graph. Our approach is based on an explicit triangulation of the Cayley and Tutte polytope. We prove that simplices in the triangulations correspond to labeled trees and forests. The heart of the proof is a direct bijection based on the neighbors-first search graph traversal algorithm. Les polytopes de Cayley ont été définis récemment comme des ensembles convexes de compositions de Cayley introduits par Cayley en 1857. Dans ce papier, nous résolvons la conjecture de Braun. Cette dernière exprime le volume du polytopes de Cayley en termes du nombre de graphes connexes. Nous étendons ce résultat à des déformations de polytopes de Cayley à deux variables, à savoir les polytopes de Tutte. Le volume de ces derniers est donnè par une évaluation du polynôme de Tutte du graphe complet. Notre approche est basée sur une triangulation explicite des polytopes de Cayley et Tutte. Nous démontrons que les simplexes de ces triangulations correspondent à des arbres marqués. La pierre angulaire de notre démonstration est une bijection directe basées sur l'algorithme de la recherche du premier voisin sur le graphe.

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