Contrastive hierarchical clustering

M Znalezniak, P Rola, P Kaszuba, J Tabor… - … European Conference on …, 2023‏ - Springer
Deep clustering has been dominated by flat models, which split a dataset into a predefined
number of groups. Although recent methods achieve an extremely high similarity with the …

Pharmacoprint: A combination of a pharmacophore fingerprint and artificial intelligence as a tool for computer-aided drug design

D Warszycki, Ł Struski, M Smieja, R Kafel… - Journal of chemical …, 2021‏ - ACS Publications
Structural fingerprints and pharmacophore modeling are methodologies that have been
used for at least 2 decades in various fields of cheminformatics, from similarity searching to …

Clustered distribution of natural product leads of drugs in the chemical space as influenced by the privileged target-sites

L Tao, F Zhu, C Qin, C Zhang, S Chen, P Zhang… - Scientific reports, 2015‏ - nature.com
Some natural product leads of drugs (NPLDs) have been found to congregate in the
chemical space. The extent, detailed patterns and mechanisms of this congregation …

Determining the optimum number of clusters in hierarchical clustering using Pseudo-F

SJ Sinaga, N Satyahadewi… - Euler: Jurnal Ilmiah …, 2023‏ - ejurnal.ung.ac.id
Poverty refers to the condition where a person cannot meet the basic necessities based on
the minimum living standards. Statistics Indonesia proxied an increase in the poverty rate in …

General split gaussian cross–entropy clustering

P Spurek - Expert Systems with Applications, 2017‏ - Elsevier
Robust mixture models approaches, which use non-normal distributions have recently been
upgraded to accommodate asymmetric data. In this article we propose a new method based …

The choice of an appropriate information dissimilarity measure for hierarchical clustering of river streamflow time series, based on calculated Lyapunov exponent and …

DT Mihailović, E Nikolić-Đorić, S Malinović-Milićević… - Entropy, 2019‏ - mdpi.com
The purpose of this paper was to choose an appropriate information dissimilarity measure
for hierarchical clustering of daily streamflow discharge data, from twelve gauging stations …

Average information content maximization—a new approach for fingerprint hybridization and reduction

M Śmieja, D Warszycki - PloS one, 2016‏ - journals.plos.org
Fingerprints, bit representations of compound chemical structure, have been widely used in
cheminformatics for many years. Although fingerprints with the highest resolution display …

Fast entropy clustering of sparse high dimensional binary data

M Śmieja, S Nakoneczny… - 2016 International Joint …, 2016‏ - ieeexplore.ieee.org
We introduce Sparse Entropy Clustering (SEC) which uses minimum entropy criterion to split
high dimensional binary vectors into groups. The idea is based on the analogy between …

CFam: a chemical families database based on iterative selection of functional seeds and seed-directed compound clustering

C Zhang, L Tao, C Qin, P Zhang, S Chen… - Nucleic Acids …, 2015‏ - academic.oup.com
Similarity-based clustering and classification of compounds enable the search of drug leads
and the structural and chemogenomic studies for facilitating chemical, biomedical …

Customer profiling and purchase decision influencers: an empirical case study from the management consulting industry

V Kivistö - 2024‏ - lutpub.lut.fi
Customer profiling and assessing the influencers of business-to-business purchase
decisions can clarify who a company's core customers are and how sales and marketing can …