Results 261 to 270 of about 411,688 (293)
Some of the next articles are maybe not open access.
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 Suresh Hettiarachchi +2 more
openaire +1 more source
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 Suresh Hettiarachchi +2 more
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
2023
AbstractIn 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 deconvolution methods ...
Wei Zhang +7 more
openaire +1 more source
AbstractIn 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 deconvolution methods ...
Wei Zhang +7 more
openaire +1 more source
International Journal of Data Mining and Bioinformatics, 2016
Class retrieval in gene expression microarray data analysis is highly challenging task. Because of high class imbalance, highly dimensional feature space and small number of samples most of the algorithms fail to capture real complex structures in data 'golden standard'.
Vukićević, Milan +3 more
openaire +2 more sources
Class retrieval in gene expression microarray data analysis is highly challenging task. Because of high class imbalance, highly dimensional feature space and small number of samples most of the algorithms fail to capture real complex structures in data 'golden standard'.
Vukićević, Milan +3 more
openaire +2 more sources
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 ...
J.S. Shaik, M. Yeasin
openaire +1 more source
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 ...
J.S. Shaik, M. Yeasin
openaire +1 more source
International Journal of Laboratory Hematology, 2018
AbstractIntroductionT‐cell receptor gene (TRG) rearrangement profiling is an essential component of the workup at diagnosis of T‐cell malignancies. TRG amplification by polymerase chain reaction (PCR) and analysis by capillary electrophoresis (PCR‐CE) is mostly widely used but is hampered by a subjective interpretation of its results and possible false‐
Friedel Nollet +6 more
openaire +2 more sources
AbstractIntroductionT‐cell receptor gene (TRG) rearrangement profiling is an essential component of the workup at diagnosis of T‐cell malignancies. TRG amplification by polymerase chain reaction (PCR) and analysis by capillary electrophoresis (PCR‐CE) is mostly widely used but is hampered by a subjective interpretation of its results and possible false‐
Friedel Nollet +6 more
openaire +2 more sources
Gene expression programming algorithm based on multi-threading evaluator
Journal of Computer Applications, 2013Sheng-qiao NI +3 more
openaire +1 more source
2021 17th International Conference on Mobility, Sensing and Networking (MSN), 2021
Shunbao Li +2 more
openaire +1 more source
Shunbao Li +2 more
openaire +1 more source
2013
The Job Shop Scheduling Problem (JSSP) is one of the most general and difficult of all traditional scheduling problems. Search based on traditional ghenetic algorithms has a major drawback: large computational time and memory usage if a large population and / or a large number of generations are used but on the other hand larger population and larger ...
Janeš, Gordan +2 more
openaire +2 more sources
The Job Shop Scheduling Problem (JSSP) is one of the most general and difficult of all traditional scheduling problems. Search based on traditional ghenetic algorithms has a major drawback: large computational time and memory usage if a large population and / or a large number of generations are used but on the other hand larger population and larger ...
Janeš, Gordan +2 more
openaire +2 more sources