Found 5553 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

**Graph** Based Machine Learning Interprets Diagnostic Isomer-Selective Ion-Molecule Reactions in Tandem Mass Spectrometry

Here, we introduce a first bootstrapped decision tree model trained on 36 known ion-molecule reactions with MOP using

**graph**-based connectivity of analyte’s functional groups as input. Expand abstract.Diagnostic ion-molecule reactions using tandem mass spectrometry can differentiate between isomeric compounds unlike a popular collision-activated dissociation methodology for the identification of previously unknown mixtures. Selected neutral reagents, such as 2-methoxypropene (MOP) are introduced into an ion trap mass spectrometer and react with protonated analytes to produce product ions diagnostic of the functional groups present in the analyte. However, the interpretation and understanding of specific reactions are challenging and time-consuming for chemical characterization. Here, we introduce a first bootstrapped decision tree model trained on 36 known ion-molecule reactions with MOP using

**graph**-based connectivity of analyte’s functional groups as input. A Cohen Kappa statistic of 0.72 was achieved, suggesting substantial inter-model reliability on limited training data. Prospective diagnostic product predictions were made and validated for 14 previously unpublished analytes . Chemical reactivity flowcharts were introduced to understand the decisions made by the machine learning method that will be useful for chemists.18289 days ago

5/10 relevant

chemRxiv

5/10 relevant

chemRxiv

Integrating Deep Neural Networks and Symbolic Inference for Organic Reactivity Prediction

Our approach outperforms previous

**graph**-based neural networks by predicting products with more than 90% accuracy, demonstrates intuitive chemical reasoning through a learned attention mechanism, and provides generalizability across various reaction types. Expand abstract.Accurate in silico models for the prediction of novel chemical reaction outcomes can be used to guide the rapid discovery of new reactivity and enable novel synthesis strategies for newly discovered lead compounds. Recent advances in machine learning, driven by deep learning models and data availability, have shown utility throughout synthetic organic chemistry as a data-driven method for reaction prediction. Here we present a machine-intelligence approach to predict the products of an organic reaction by integrating deep neural networks with a probabilistic and symbolic inference that flexibly enforces chemical constraints and accounts for prior chemical knowledge. We first train a

**graph**convolutional neural network to estimate the likelihood of changes in covalent bonds, hydrogen counts, and formal charges. These estimated likelihoods govern a probability distribution over potential products. Integer Linear Programming is then used to infer the most probable products from the probability distribution subject to heuristic rules such as the octet rule and chemical constraints that reflect a user's prior knowledge. Our approach outperforms previous**graph**-based neural networks by predicting products with more than 90% accuracy, demonstrates intuitive chemical reasoning through a learned attention mechanism, and provides generalizability across various reaction types. Furthermore, we demonstrate the potential for even higher model accuracy when complemented by expert chemists contributing to the system, boosting both machine and expert performance. The results show the advantages of empowering deep learning models with chemical intuition and knowledge to expedite the drug discovery process.18289 days ago

4/10 relevant

chemRxiv

4/10 relevant

chemRxiv

Policy Synthesis for Factored MDPs with **Graph** Temporal Logic
Specifications

The structure in the model and the specifications enable to develop a distributed algorithm that, given a factored Markov decision process and a

**graph**temporal logic formula, decomposes the synthesis problem into a set of smaller synthesis problems, one for each agent. Expand abstract. We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called

**graph**temporal logic specifications. The transition function and the spatial-temporal task of each agent depend on the agent itself and its neighboring agents. The structure in the model and the specifications enable to develop a distributed algorithm that, given a factored Markov decision process and a**graph**temporal logic formula, decomposes the synthesis problem into a set of smaller synthesis problems, one for each agent. We prove that the algorithm runs in time linear in the total number of agents. The size of the synthesis problem for each agent is exponential only in the number of neighboring agents, which is typically much smaller than the number of agents. We demonstrate the algorithm in case studies on disease control and urban security. The numerical examples show that the algorithm can scale to hundreds of agents.3 days ago

7/10 relevant

arXiv

7/10 relevant

arXiv

On the enhanced power **graph** of a group

The enhanced power graph $\mathcal{P}_e(G)$ of a group $G$ is a graph with vertex set $G$ and two vertices are adjacent if they belong to the same cyclic subgroup. Expand abstract.

The enhanced power

**graph**$\mathcal{P}_e(G)$ of a group $G$ is a**graph**with vertex set $G$ and two vertices are adjacent if they belong to the same cyclic subgroup. In this paper, we consider the minimum degree, independence number and matching number of enhanced power**graphs**of finite groups. We first study these**graph**invariants for $\mathcal{P}_e(G)$ when $G$ is any finite group, and then determine them when $G$ is a finite abelian $p$-group, $U_{6n} = \langle a, b : a^{2n} = b^3 = e, ba =ab^{-1} \rangle$, the dihedral group $D_{2n}$, or the semidihedral group $SD_{8n}$. If $G$ is any of these groups, we prove that $\mathcal{P}_e(G)$ is perfect and then obtain its strong metric dimension. Additionally, we give an expression for the independence number of $\mathcal{P}_e(G)$ for any finite abelian group $G$. These results along with certain known equalities yield the edge connectivity, vertex covering number and edge covering number of enhanced power**graphs**of the respective groups as well.3 days ago

9/10 relevant

arXiv

9/10 relevant

arXiv

On $\sigma$-arithmetic **graphs** of finite groups

Let $G$ be a finite group and $\sigma$ a partition of the set of all? primes $\Bbb{P}$, that is, $\sigma =\{\sigma_i \mid i\in I \}$, where $\Bbb{P}=\bigcup_{i\in I} \sigma_i$ and $\sigma_i\cap \sigma_j= \emptyset $ for all $i\ne j$. Expand abstract.

Let $G$ be a finite group and $\sigma$ a partition of the set of all? primes $\Bbb{P}$, that is, $\sigma =\{\sigma_i \mid i\in I \}$, where $\Bbb{P}=\bigcup_{i\in I} \sigma_i$ and $\sigma_i\cap \sigma_j= \emptyset $ for all $i\ne j$. If $n$ is an integer, we write $\sigma(n)=\{\sigma_i \mid \sigma_{i}\cap \pi (n)\ne \emptyset \}$ and $\sigma (G)=\sigma (|G|)$. We call a

**graph**$\Gamma$ with the set of all vertices $V(\Gamma)=\sigma (G)$ ($G\ne 1$) a $\sigma$-arithmetic**graph**of $G$, and we associate with $G\ne 1$ the following three directed $\sigma$-arithmetic graphs: (1) the $\sigma$-Hawkes**graph**$\Gamma_{H\sigma }(G)$ of $G$ is a $\sigma$-arithmetic**graph**of $G$ in which $(\sigma_i, \sigma_j)\in E(\Gamma_{H\sigma }(G))$ if $\sigma_j\in \sigma (G/F_{\{\sigma_i\}}(G))$; (2) the $\sigma$-Hall**graph**$\Gamma_{\sigma Hal}(G)$ of $G$ in which $(\sigma_i, \sigma_j)\in E(\Gamma_{\sigma Hal}(G))$ if for some Hall $\sigma_i$-subgroup $H$ of $G$ we have $\sigma_j\in \sigma (N_{G}(H)/HC_{G}(H))$; (3) the $\sigma$-Vasil'ev-Murashko**graph**$\Gamma_{{\mathfrak{N}_\sigma }}(G)$ of $G$ in which $(\sigma_i, \sigma_j)\in E(\Gamma_{{\mathfrak{N}_\sigma}}(G))$ if for some ${\mathfrak{N}_{\sigma }}$-critical subgroup $H$ of $G$ we have $\sigma_i \in \sigma (H)$ and $\sigma_j\in \sigma (H/F_{\{\sigma_i\}}(H))$. In this paper, we study the structure of $G$ depending on the properties of these three**graphs**of $G$.3 days ago

9/10 relevant

arXiv

9/10 relevant

arXiv

Coordinated Reasoning for Cross-Lingual Knowledge **Graph** Alignment

Existing entity alignment methods mainly vary on the choices of encoding the knowledge

**graph**, but they typically use the same decoding method, which independently chooses the local optimal match for each source entity. Expand abstract. Existing entity alignment methods mainly vary on the choices of encoding the knowledge graph, but they typically use the same decoding method, which independently chooses the local optimal match for each source entity. This decoding method may not only cause the "many-to-one" problem but also neglect the coordinated nature of this task, that is, each alignment decision may highly correlate to the other decisions. In this paper, we introduce two coordinated reasoning methods, i.e., the Easy-to-Hard decoding strategy and joint entity alignment algorithm. Specifically, the Easy-to-Hard strategy first retrieves the model-confident alignments from the predicted results and then incorporates them as additional knowledge to resolve the remaining model-uncertain alignments. To achieve this, we further propose an enhanced alignment model that is built on the current state-of-the-art baseline. In addition, to address the many-to-one problem, we propose to jointly predict entity alignments so that the one-to-one constraint can be naturally incorporated into the alignment prediction. Experimental results show that our model achieves the state-of-the-art performance and our reasoning methods can also significantly improve existing baselines.

4 days ago

5/10 relevant

arXiv

5/10 relevant

arXiv

A Construction of Uniquely Colourable **Graphs** with Equal Colour Class
Sizes

A uniquely $k$-colourable graph is a graph with exactly one partition of the vertex set into at most $k$ colour classes. Expand abstract.

A uniquely $k$-colourable

**graph**is a**graph**with exactly one partition of the vertex set into at most $k$ colour classes. Here, we investigate some constructions of uniquely $k$-colourable**graphs**and give a construction of $K_k$-free uniquely $k$-colourable**graphs**with equal colour class sizes.4 days ago

9/10 relevant

arXiv

9/10 relevant

arXiv

A note on purely imaginary independence roots

We show that there are infinitely many connected

**graphs**with purely imaginary independence roots and that every**graph**is a subgraph of such a graph. Expand abstract. The independence polynomial of a

**graph**is the generating polynomial for the number of independent sets of each cardinality and its roots are called independence roots. We investigate here purely imaginary independence roots. We show that there are infinitely many connected**graphs**with purely imaginary independence roots and that every**graph**is a subgraph of such a**graph**. We also classify every rational purely imaginary number that is an independence root.4 days ago

6/10 relevant

arXiv

6/10 relevant

arXiv

BlastFrost: Fast querying of 100,000s of bacterial genomes in Bifrost **graphs**

BlastFrost queries a Bifrost data structure for sequences of interest, and extracts local subgraphs, thereby enabling the efficient identification of the presence or absence of individual genes or single nucleotide sequence variants. Expand abstract.

BlastFrost is a highly efficient method for querying 100,000s of genome assemblies. It builds on Bifrost, a recently developed dynamic data structure for compacted and colored de Bruijn

**graphs**from bacterial genomes. BlastFrost queries a Bifrost data structure for sequences of interest, and extracts local subgraphs, thereby enabling the efficient identification of the presence or absence of individual genes or single nucleotide sequence variants. Here we describe the algorithms and implementation of BlastFrost. We also present two exemplar practical applications. In the first, we determined the presence of the individual genes within the SPI-2 Salmonella pathogenicity island within a collection of 926 representative genomes in minutes. In the second application, we determined the existence of known single nucleotide polymorphisms associated with fluoroquinolone resistance in the genes gyrA, gyrB and parE among 190,209 Salmonella genomes.5 days ago

6/10 relevant

bioRxiv

6/10 relevant

bioRxiv

A Neural Architecture for Person Ontology population

A person ontology comprising concepts, attributes and relationships of people has a number of applications in data protection, didentification, population of knowledge

**graphs**for business intelligence and fraud prevention. Expand abstract. A person ontology comprising concepts, attributes and relationships of people has a number of applications in data protection, didentification, population of knowledge

**graphs**for business intelligence and fraud prevention. While artificial neural networks have led to improvements in Entity Recognition, Entity Classification, and Relation Extraction, creating an ontology largely remains a manual process, because it requires a fixed set of semantic relations between concepts. In this work, we present a system for automatically populating a person ontology**graph**from unstructured data using neural models for Entity Classification and Relation Extraction. We introduce a new dataset for these tasks and discuss our results.5 days ago

5/10 relevant

arXiv

5/10 relevant

arXiv