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LSHADE Algorithm with Rank-Based Selective Pressure Strategy for Solving CEC 2017 Benchmark Problems
IEEE Congress on Evolutionary Computation, 2018Solving single-objective real-parameter optimization problems can still cause difficulties, for example if the optimized function is multimodal or has rotated trap problems.
V. Stanovov, S. Akhmedova, E. Semenkin
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2013 IEEE Congress on Evolutionary Computation, 2013
Evolutionary algorithms (EAs) have been successfully used in many studies for evolving both the structure and parameters of biological networks including gene regulatory networks that demonstrate different functionalities. However, most of these studies have used only mutation as the genetic operator in the evolutionary framework, perhaps due to the ...
Dhammika S. Hettiarachchi +2 more
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Evolutionary algorithms (EAs) have been successfully used in many studies for evolving both the structure and parameters of biological networks including gene regulatory networks that demonstrate different functionalities. However, most of these studies have used only mutation as the genetic operator in the evolutionary framework, perhaps due to the ...
Dhammika S. Hettiarachchi +2 more
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A comprehensive evaluation of connectivity methods for L1000 data
Briefings Bioinform., 2019The methodologies for evaluating similarities between gene expression profiles of different perturbagens are the key to understanding mechanisms of actions (MoAs) of unknown compounds and finding new indications for existing drugs.
Kequan Lin +7 more
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Gene, 2018
Molecular alterations that occur in cancer have the potential to be considered as either cancer biomarkers or targeted therapies or even both. In the presented study, we aimed to elucidate the gene regulatory network of metastatic colorectal cancer using
Elaheh Eskandari +2 more
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Molecular alterations that occur in cancer have the potential to be considered as either cancer biomarkers or targeted therapies or even both. In the presented study, we aimed to elucidate the gene regulatory network of metastatic colorectal cancer using
Elaheh Eskandari +2 more
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Anais da I Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região Sul (ERAMIA-RS 2025)
Cancer driver genes (CDGs) play a central role in tumorigenesis and represent important targets for diagnosis and therapy. In this study, we evaluate the impact of hyperparameter optimization on the predictive performance of traditional machine learning algorithms using multi-omics data. We perform systematic searches across different configurations to
Ana Laura Schardosim +3 more
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Cancer driver genes (CDGs) play a central role in tumorigenesis and represent important targets for diagnosis and therapy. In this study, we evaluate the impact of hyperparameter optimization on the predictive performance of traditional machine learning algorithms using multi-omics data. We perform systematic searches across different configurations to
Ana Laura Schardosim +3 more
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Cancer Research, 2015
Abstract Introduction RNA sequencing (RNA-seq) has rapidly become one of the main methods to study transcriptome. It has become an important and popular issue to identify biomarkers based on their differential expression patterns in NGS data. Currently, more than 10 different algorithms can be used to detect differentially
Chin-Ting Wu +4 more
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Abstract Introduction RNA sequencing (RNA-seq) has rapidly become one of the main methods to study transcriptome. It has become an important and popular issue to identify biomarkers based on their differential expression patterns in NGS data. Currently, more than 10 different algorithms can be used to detect differentially
Chin-Ting Wu +4 more
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2023
Abstract In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based ...
Wei Zhang +7 more
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Abstract In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based ...
Wei Zhang +7 more
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DPEBic: detecting essential proteins in gene expressions using encoding and biclustering algorithm
, 2021Anooja Ali +3 more
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2012 International Conference on Advances in Computing and Communications, 2012
Reliable predictive model build using semi supervised learning utilising classification algorithm has evolved rapidly in successful cancer treatment. In order to optimise the data integration problem, such as hypergraph based learning to integrate microarray gene expressions and protein interactions for predicting cancer outcome, novice optimization ...
Seena Mary Augusty, Sminu Izudheen
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Reliable predictive model build using semi supervised learning utilising classification algorithm has evolved rapidly in successful cancer treatment. In order to optimise the data integration problem, such as hypergraph based learning to integrate microarray gene expressions and protein interactions for predicting cancer outcome, novice optimization ...
Seena Mary Augusty, Sminu Izudheen
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The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
This paper presents the implementation and evaluation of subspace-based clustering algorithm for robust selection of differentially expressed genes as well as the classification of tissue types from microarray data. The performance of the proposed algorithm is compared against other well known clustering algorithms and the quality of clusters is ...
Jahangheer S. Shaik, Mohammed Yeasin
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This paper presents the implementation and evaluation of subspace-based clustering algorithm for robust selection of differentially expressed genes as well as the classification of tissue types from microarray data. The performance of the proposed algorithm is compared against other well known clustering algorithms and the quality of clusters is ...
Jahangheer S. Shaik, Mohammed Yeasin
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