DCSNE: Density-based clustering using graph shared neighbors and entropy

R Maheshwari, SK Mohanty, AC Mishra - Pattern Recognition, 2023 - Elsevier
Density-based clustering techniques identify arbitrary shaped clusters in the presence of
outliers by capturing the intrinsic distribution of data and separating high and low-density …

An entropy-based density peak clustering for numerical gene expression datasets

R Maheshwari, AC Mishra, SK Mohanty - Applied Soft Computing, 2023 - Elsevier
In molecular biology, gene expression analysis is one of the important research areas which
deals with identifying the genes having similar functionality known as co-expressed genes …

Multiple-kernel learning for genomic data mining and prediction

CM Wilson, K Li, X Yu, PF Kuan, X Wang - BMC bioinformatics, 2019 - Springer
Background Advances in medical technology have allowed for customized prognosis,
diagnosis, and treatment regimens that utilize multiple heterogeneous data sources. Multiple …

[HTML][HTML] Clustering and classification of virus sequence through music communication protocol and wavelet transform

T Paul, S Vainio, J Roning - Genomics, 2021 - Elsevier
The coronavirus pandemic became a major risk in global public health. The outbreak is
caused by SARS-CoV-2, a member of the coronavirus family. Though the images of the virus …

Data convexity and parameter independent clustering for biomedical datasets

MA Rahman, LM Ang, KP Seng - IEEE/ACM Transactions on …, 2020 - ieeexplore.ieee.org
In machine learning, the nature of the dataset itself such as convexity of the data point sets
affects the right choice of clustering algorithm to give good performance. This brief paper first …

[PDF][PDF] Modified graph-theoretic clustering algorithm for mining international linkages of philippine higher education institutions

SR Lingaya, BD Gerardo… - International Journal of …, 2019 - researchgate.net
Graph-theoretic clustering either uses limited neighborhood or construction of a minimum
spanning tree to aid the clustering process. The latter is challenged by the need to identify …

[PDF][PDF] HSCS: Hybridization of self-organized clustering scheme for flying ad-hoc network

S BHANDARI, ER RAJAN - 2020 - researchgate.net
Flying ad-hoc network (FANET) is a collection of unnamed aerial vehicles that communicate
without any predefined infrastructure. It having dynamic topology because it is based on …

[PDF][PDF] Small-World-Like Structured MST-Based Clustering Algorithm

SR Lingaya, BD Gerardo, RP Medina - International Journal of Machine …, 2019 - ijmlc.org
Graph-theoretic clustering is one method of clustering where dataset is represented with a
connected undirected graph having the distance between these points as the weights of the …