Results 101 to 110 of about 6,396 (182)

Classifying pairs with trees for supervised biological network inference [PDF]

, 2014
Networks are ubiquitous in biology and computational approaches have been largely investigated for their inference. In particular, supervised machine learning methods can be used to complete a partially known network by integrating various measurements ...
Babu, M. Madan, Geurts, Pierre, Schrynemackers, Marie, Wehenkel, Louis   +3 more
core  

BiETech : Bicluster Ensemble Techniques

International Journal on Recent and Innovation Trends in Computing and Communication, 2023
Various biclustering algorithms have emerged now a days that try to deliver good biclusters from gene expression data which satisfy a particular objective function. Users are lost in finding the best out of these algorithms. Ensemble techniques come to rescue     of these users by aggregating all the solutions and providing a single solution which is ...
openaire   +1 more source

A probabilistic coevolutionary biclustering algorithm for discovering coherent patterns in gene expression dataset

BMC Bioinformatics, 2012
Background Biclustering has been utilized to find functionally important patterns in biological problem. Here a bicluster is a submatrix that consists of a subset of rows and a subset of columns in a matrix, and contains homogeneous patterns. The problem
Joung Je-Gun, Kim Soo-Jin, Shin Soo-Yong, Zhang Byoung-Tak   +3 more
doaj   +1 more source

An Evaluation of the Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Components

Data, 2018
This paper presents the results of research concerning the evaluation of stability of information technology of gene expression profiles processing with the use of gene expression profiles, which contain different levels of noise components.
Sergii Babichev
doaj   +1 more source

A New Heuristic for Feature Selection by Consistent Biclustering

, 2010
Given a set of data, biclustering aims at finding simultaneous partitions in biclusters of its samples and of the features which are used for representing the samples.
Cafieri, Sonia, Mucherino, Antonio
core   +1 more source

Identifying Poverty Vulnerability Patterns in Indonesia using Cheng and Chruch’s Algorithm

JTAM (Jurnal Teori dan Aplikasi Matematika)
Poverty remains a significant issue in developing countries, including Indonesia, where in 2022, the number of people living in poverty reached 26.36 million, with a poverty rate of 9.57%.
Irsyifa Mayzela Afnan, Hari Wijayanto, Aji Hamim Wigena   +2 more
doaj   +1 more source

Biclustering a dataset using photonic quantum computing

Frontiers in Computer Science
Biclustering is a problem in machine learning and data mining that seeks to group together rows and columns of a dataset according to certain criteria. In this work, we highlight the natural relation that quantum computing models like boson and Gaussian ...
Ajinkya Borle, Ameya Bhave
doaj   +1 more source

Integrating Data Mining, Deep Learning, and Gene Ontology Analysis for Gene Expression-Based Disease Diagnosis Systems

IEEE Access
The manuscript details the outcomes of a comprehensive study on the application of cluster-bicluster analysis, gene ontology analysis, and convolutional neural network (CNN) for diagnosing cancer and Alzheimer’s disease using gene expression data ...
Sergii Babichev, Igor Liakh, Jiri Skvor
doaj   +1 more source

scDBic: a novel deep learning-based biclustering algorithm for analyzing scRNA-seq data. [PDF]

Bioinformatics
Tang X, Liu C, Lan C.
europepmc   +1 more source

A formal explanation space for the simultaneous clustering of neurologic diseases based on their signs and symptoms. [PDF]

BMC Med Inform Decis Mak
Yelugam R, Hier DB, Obafemi-Ajayi T, Carrithers MD, Wunsch Ii DC.   +4 more
europepmc   +1 more source