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Toplam kayıt 11, listelenen: 1-10
Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020)
The accurate identification of lactobacilli is essential for the effective management of industrial practices associated with lactobacilli strains, such as the production of fermented foods or probiotic supplements. For ...
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
(PEERJ INC341-345 OLD ST, THIRD FLR, LONDON EC1V 9LL, ENGLAND, 2021)
A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high ...
PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
(BMC, 2023)
BackgroundCell homeostasis relies on the concerted actions of genes, and dysregulated genes can lead to diseases. In living organisms, genes or their products do not act alone but within networks. Subsets of these networks ...
TextNetTopics Pro, a topic model-based text classification for short text by integration of semantic and document-topic distribution information
(FRONTIERS MEDIA SA, 2023)
With the exponential growth in the daily publication of scientific articles, automatic
classification and categorization can assist in assigning articles to a predefined
category. Article titles are concise descriptions ...
GeNetOntology: identifying affected gene ontology terms via grouping, scoring, and modeling of gene expression data utilizing biological knowledge-based machine learning
(FRONTIERS MEDIA SA, 2023)
Introduction: Identifying significant sets of genes that are up/downregulated under specific conditions is vital to understand disease development mechanisms at the molecular level. Along this line, in order to analyze ...
Topological feature generation for link prediction in biological networks
(PEERJ INC, 2023)
Graph or network embedding is a powerful method for extracting missing or
potential information from interactions between nodes in biological networks. Graph
embedding methods learn representations of nodes and interactions ...
Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many ...
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
Human gut microbiota is a complex community of organisms including trillions of bacteria. While these microorganisms are considered as essential regulators of our immune system, some of them can cause several diseases. In ...
miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
(Frontiers Media S.A., 2023)
During recent years, biological experiments and increasing evidence have shown that microRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex ...
A toolbox of machine learning software to support microbiome analysis
(Frontiers Media SA, 2023)
The human microbiome has become an area of intense research due to its
potential impact on human health. However, the analysis and interpretation
of this data have proven to be challenging due to its complexity and ...