RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks. [PDF]
PLoS ONE, 2011 RegnANN is a novel method for reverse engineering gene networks based on an ensemble of multilayer perceptrons. The algorithm builds a regressor for each gene in the network, estimating its neighborhood independently.
Marco Grimaldi +2 more
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A realistic assessment of methods for extracting gene/protein interactions from free text [PDF]
BMC Bioinformatics, 2009 Background The automated extraction of gene and/or protein interactions from the literature is one of the most important targets of biomedical text mining research.
Shepherd Adrian J +2 more
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Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
Iraqi Journal for Computer Science and Mathematics, 2022 The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster.
Omar Al-Janabee, Basad Al-Sarray
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From knockouts to networks: establishing direct cause-effect relationships through graph analysis. [PDF]
PLoS ONE, 2010 BACKGROUND: Reverse-engineering gene networks from expression profiles is a difficult problem for which a multitude of techniques have been developed over the last decade.
Andrea Pinna +3 more
doaj +1 more source
Detecting Cooperativity between Transcription Factors Based on Functional Coherence and Similarity of Their Target Gene Sets. [PDF]
PLoS ONE, 2016 In eukaryotic cells, transcriptional regulation of gene expression is usually achieved by cooperative transcription factors (TFs). Therefore, knowing cooperative TFs is the first step toward uncovering the molecular mechanisms of gene expression ...
Wei-Sheng Wu, Fu-Jou Lai
doaj +1 more source
Frontiers in Neuroscience, 2022 An IA is an abnormal swelling of cerebral vessels, and a subset of these IAs can rupture causing aneurysmal subarachnoid hemorrhage (aSAH), often resulting in death or severe disability.
Qingqing Li +9 more
doaj +1 more source
Inferring causal relations from multivariate time series : a fast method for large-scale gene expression data [PDF]
, 2009 Various multivariate time series analysis techniques have been developed with the aim of inferring causal relations between time series. Previously, these techniques have proved their effectiveness on economic and neurophysiological data, which normally ...
Li, Chang-Tsun, Yuan, Yinyin
core +1 more source
TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction [PDF]
Nucleic Acids Research, 2018 Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using ...
Chathura Gunasekara +4 more
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Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels [PDF]
Asian Pacific Journal of Cancer Prevention, 2016 Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor ...
Maxim D, Podolsky +5 more
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Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy [PDF]
, 2013 In this work a new way to calculate the multivariate joint entropy is presented. This measure is the basis for a fast information-theoretic based evaluation of gene relevance in a Microarray Gene Expression data context.
Belanche Muñoz, Luis Antonio +1 more
core +5 more sources