Performance optimization of object comparison

Hallez, Axel; Tré, Guy De; Bronselaer, Antoon

doi:10.1002/int.20373

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…The NC value of each node pair is plotted as a function of its ND value (Figure c). It can be seen that most points are located near the antidiagonal, suggesting that they follow the general rule of networks: correlation decreases with distance increase. − In addition, a certain number of points present a considerable deviation from the antidiagonal. Points located in the upper-right half of the diagram have NC values larger than those along the antidiagonal (1-ND), suggesting that the corresponding node pairs have larger correlations than the node pairs with average correlation values.…”

Section: Resultsmentioning

confidence: 93%

Unraveling the Allosteric Mechanism of Four Cancer-related Mutations in the Disruption of p53-DNA Interaction

2021

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The p53 protein plays active roles in the physiological regulation of cell cycle as well as in cancer developments. In more than half of human cancers, the protein is inactivated by mutations located primarily in its DNA-binding domain (DBD), and some mutations located in the β-sandwich region of DBD are reported to decrease p53–DNA binding affinities. To understand the long-range correlation between p53 β-sandwich and DNA, and the allosteric mechanism of β-sandwich mutations in the disruption of p53–DNA interactions, we first identify three regions with a strong correlation with DNA based on microsecond molecular dynamics (MD) simulations of wild-type p53–DNA complex and then perform multiple MD simulations on four cancer-related mutants L145Q, P151S, Y220C, and G266R, which are located in these three regions. Our simulations show that these mutations allosterically destabilize the structural stability of the DNA-binding groove in p53 and disrupt the p53–DNA interactions. Network analyses reveal optimal correlation paths through which the mutation-induced allosteric signal passes to DNA, and the disturbance effect of these mutations on the global connectivity and dynamical correlation of the p53–DNA complex. This work paves the way for the in-depth understanding of the mutation-induced loss in p53’s DNA-recognition ability and the pathological mechanism of cancer development.

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Section: Resultsmentioning

confidence: 93%

Unraveling the Allosteric Mechanism of Four Cancer-related Mutations in the Disruption of p53-DNA Interaction

2021

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“…The bibliometric method is understood as an approach to analyzing academic publications using statistical and mathematical methods (Mora et al, 2017;Li & Lei, 2021;Wang et al, 2021). This method uses a quantitative approach from the database bibliography (Naruethradhol & Gebsombut, 2020;Gomezelj, 2016;La Paz et al, 2020;Merigo & Yang, 2017;Dabiae et al, 2020;Dwekat et al, 2020;De Tre et al, 2014), to analyze the main areas of research, trending topics/themes that are developing in the Journal (Martínez-López et al, 2018;Jiang et al, 2019) and research fields. The bibliometric analysis focuses on examining themes, authors, citations, co-citations, methodology, and keyword occurrences (Kabongo, 2019;Koseoglu et al, 2016).…”

Section: Methodsmentioning

confidence: 99%

A Bibliometric Analysis of the Electoral Studies journal

Sihidi,

Suhermanto,

Kurniawan

2023

JGCS

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Elections are one of the important topics in the study of global democracy. This study aims to analyze scientific literature in the Journal of Electoral Studies as one of the highly reputable international journals from 2016 to August 2021. The data was analyzed using a bibliometric approach and visualization using VOSViewer and R Studio. This study took 618 articles from various international authors which showed that the electoral studies journal was consistently published with the most authors coming from the United States even though the origin of the university came from the Universiteit van Amsterdam Netherlands. Voting behavior and elections are two important keywords that often appear, indicating that these two issues are most often discussed by authors because they are considered to contribute greatly to electoral studies. These two keywords will also continue to be relevant in future election studies both in electoral studies journals and in other reputable journals because the development of the issue is very dynamic.Pemilu merupakan salah satu topik penting dalam kajian demokrasi global. Penelitian ini bertujuan melakukan analisis literatur ilmiah di Jurnal electoral Studies sebagai salah satu jurnal internasional bereputasi tinggi dari terbitan 2016 sampai dengan Agustus 2021. Data dianalisa dengan menggunakan pendekatan bibliometrik dan visualisasi menggunakan VOSViewer dan R Studio. Studi ini mengambil 618 artikel dari berbagai penulis internasional yang menunjukan bahwa jurnal electoral studies konsisten terbit dengan penulis terbanyak berasal dari amerika serikat meskipun untuk asal universitas berasal dari Universiteit van Amsterdam Belanda. Voting behavior dan elections adalah 2 kata kunci penting yang sering muncul yang menandakan bahwa kedua isu tersebut paling sering dibahas oleh para penulis karena dianggap sangat memberikan kontribusi dalam kajian kepemiluan. Kedua kata kunci tersebut juga akan terus relevan dalam kajian-kajian pemilu selanjutnya baik di jurnal electoral studies maupun di jurnal-jurnal bereputasi lainya karena perkembangan isunya yang sangat dinamis.

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“…Correlation-based Feature Selection (CFS) evaluates feature subsets using heuristic search functions instead of exhaustive search strategies [103]. Additionally, minimum Redundancy Maximum Relevance (mRMR) ranks the importance of feature subsets for classification problems [104,105].…”

Section: Filter-based Fs Approachesmentioning

confidence: 99%

Investigating the Performance of a Novel Modified Binary Black Hole Optimization Algorithm for Enhancing Feature Selection

Al-Eiadeh,

Qaddoura,

Abdallah

2024

Preprint

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High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

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Performance optimization of object comparison

Cited by 6 publications

References 9 publications

Unraveling the Allosteric Mechanism of Four Cancer-related Mutations in the Disruption of p53-DNA Interaction

Unraveling the Allosteric Mechanism of Four Cancer-related Mutations in the Disruption of p53-DNA Interaction

A Bibliometric Analysis of the Electoral Studies journal

Investigating the Performance of a Novel Modified Binary Black Hole Optimization Algorithm for Enhancing Feature Selection

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