<i>ANCA</i>: Alignment-Based Network Construction Algorithm

Chow, Kevin; Sarkar, Aisharjya; Elhesha, Rasha; Cinaglia, Pietro; Ay, Ahmet; Kahveci, Tamer

doi:10.1109/tcbb.2019.2923620

Cited by 16 publications

(7 citation statements)

References 48 publications

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“…STRING and GeneMANIA are two well-known and simple-to-use web tools, with no need for the user to have advanced knowledge in programming to use them. When compared to other tools such as the Alignment-Based Network Construction Algorithm (ANCA) [53], their simple interface, web access, and the possibility that they can produce a list of associated genes from a query based on several biological associations make these tools more attractive for users.…”

Section: Discussionmentioning

confidence: 99%

Network Analysis of Biomarkers Associated with Occupational Exposure to Benzene and Malathion

Santos

Feltrin

Costa‐Amaral

et al. 2023

IJMS

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Complex diseases are associated with the effects of multiple genes, proteins, and biological pathways. In this context, the tools of Network Medicine are compatible as a platform to systematically explore not only the molecular complexity of a specific disease but may also lead to the identification of disease modules and pathways. Such an approach enables us to gain a better understanding of how environmental chemical exposures affect the function of human cells, providing better perceptions about the mechanisms involved and helping to monitor/prevent exposure and disease to chemicals such as benzene and malathion. We selected differentially expressed genes for exposure to benzene and malathion. The construction of interaction networks was carried out using GeneMANIA and STRING. Topological properties were calculated using MCODE, BiNGO, and CentiScaPe, and a Benzene network composed of 114 genes and 2415 interactions was obtained. After topological analysis, five networks were identified. In these subnets, the most interconnected nodes were identified as: IL-8, KLF6, KLF4, JUN, SERTAD1, and MT1H. In the Malathion network, composed of 67 proteins and 134 interactions, HRAS and STAT3 were the most interconnected nodes. Path analysis, combined with various types of high-throughput data, reflects biological processes more clearly and comprehensively than analyses involving the evaluation of individual genes. We emphasize the central roles played by several important hub genes obtained by exposure to benzene and malathion.

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Section: Discussionmentioning

confidence: 99%

Network Analysis of Biomarkers Associated with Occupational Exposure to Benzene and Malathion

Santos

Feltrin

Costa‐Amaral

et al. 2023

IJMS

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“…These regions form clusters that will be assembled to make a local alignment. Then, using local interactions between clusters, a second alignment is performed: global alignment ( Malod-Dognin, Ban and Pržulj, 2017 ; Alcalá et al, 2020 ; Chow et al, 2021 ). Other horizontal integration algorithms applied propagation algorithms as the random walk with restart (RWR) process (detailed in vertical integration of a PPI network).…”

Section: Methods Based On Text Miningmentioning

confidence: 99%

Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context

Robin

Bodein

Scott‐Boyer

et al. 2022

Front. Mol. Biosci.

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At the heart of the cellular machinery through the regulation of cellular functions, protein–protein interactions (PPIs) have a significant role. PPIs can be analyzed with network approaches. Construction of a PPI network requires prediction of the interactions. All PPIs form a network. Different biases such as lack of data, recurrence of information, and false interactions make the network unstable. Integrated strategies allow solving these different challenges. These approaches have shown encouraging results for the understanding of molecular mechanisms, drug action mechanisms, and identification of target genes. In order to give more importance to an interaction, it is evaluated by different confidence scores. These scores allow the filtration of the network and thus facilitate the representation of the network, essential steps to the identification and understanding of molecular mechanisms. In this review, we will discuss the main computational methods for predicting PPI, including ones confirming an interaction as well as the integration of PPIs into a network, and we will discuss visualization of these complex data.

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“…( 2020 ); Chow et al. ( 2021 ); Ren et al. ( 2021 ) implemented variants of node colored motif discovery , constrained to be paths, in temporal graphs (Temporal-patterns-mk2), Rozenshtein et al.…”

Section: Software Tools For Temporal Networkmentioning

confidence: 99%

Temporal networks in biology and medicine: a survey on models, algorithms, and tools

Hosseinzadeh

Cannataro

Guzzi

et al. 2022

Netw Model Anal Health Inform Bioinforma

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The use of static graphs for modelling and analysis of biological and biomedical data plays a key role in biomedical research. However, many real-world scenarios present dynamic behaviours resulting in both node and edges modification as well as feature evolution. Consequently, ad-hoc models for capturing these evolutions along the time have been introduced, also referred to as dynamic, temporal, time-varying graphs. Here, we focus on temporal graphs, i.e., graphs whose evolution is represented by a sequence of time-ordered snapshots. Each snapshot represents a graph active in a particular timestamp. We survey temporal graph models and related algorithms, presenting fundamentals aspects and the recent advances. We formally define temporal graphs, focusing on the problem setting and we present their main applications in biology and medicine. We also present temporal graph embedding and the application to recent problems such as epidemic modelling. Finally, we further state some promising research directions in the area. Main results of this study include a systematic review of fundamental temporal network problems and their algorithmic solutions considered in the literature, in particular those having application in computational biology and medicine. We also include the main software developed in this context.

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ANCA: Alignment-Based Network Construction Algorithm

Cited by 16 publications

References 48 publications

Network Analysis of Biomarkers Associated with Occupational Exposure to Benzene and Malathion

Network Analysis of Biomarkers Associated with Occupational Exposure to Benzene and Malathion

Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context

Temporal networks in biology and medicine: a survey on models, algorithms, and tools

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