Comprehensive Review of Hybrid Feature Selection Methods for Microarray-Based Cancer Detection by Azka Khoirunnisa, Didit Adytia, Mustafa Mat Deris, Adiwijaya

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Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fathima Fajila, Yuhanis Yusof

Subjects: “…Biomarker detection…”
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Exploring Feature Selection with Deep Learning for Kidney Tissue Microarray Classification Using Infrared Spectral Imaging by Zachary Caterer, Jordan Langlois, Connor McKeown, Mikayla Hady, Samuel Stumo, Suman Setty, Michael Walsh, Rahul Gomes

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Xq12q13.2 duplication detected in a child in selective exome screening by A. A. Dokshukina, Je. Shubina, D. N. Maslennikov, I. O. Sadelov, E. R. Tolmacheva, S. V. Ionushene, T. A. Bairova, L. V. Rychkova, D. Yu. Trofimov, D. N. Degtyarev

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Consistency and Stability in Feature Selection for High-Dimensional Microarray Survival Data in Diffuse Large B-Cell Lymphoma Cancer by Kazeem A. Dauda, Rasheed K. Lamidi

“…High-dimensional survival data, such as microarray datasets, present significant challenges in variable selection and model performance due to their complexity and dimensionality. …”
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Phenotypic Profiling of Selected Cellulolytic Strains to Develop a Crop Residue-Decomposing Bacterial Consortium by Arman Shamshitov, Egidija Satkevičiūtė, Francesca Decorosi, Carlo Viti, Skaidrė Supronienė

“…All strains demonstrated effective straw biomass degradation compared to the negative control, with significant differences detected only in oil seed rape straw biodegradation estimations. …”
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Effective detection of 148 cases chromosomal mosaicism by karyotyping, chromosomal microarray analysis and QF-PCR in 32,967 prenatal diagnoses by Yi Deng, Lan Zeng, Zhiling Wu, Jin Wang, Mengling Ye, Chun Chen, Ping Wei, Danni Wang, Guangming Deng, Shuyao Zhu

“…Methods A total of 148 fetuses diagnosed with chromosomal mosaicism by karyotyping with copy number variant sequencing (CNV-seq)/ chromosomal microarray analysis (CMA) and quantitative fluorescent polymerase chain reaction (QF-PCR) were selected, and the results from three the methods were compared and further analyzed. …”
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FEATURE SELECTION IN THE TASK OF MEDICAL DIAGNOSTICS ON MICROARRAY DATA by N. G. Zagoruiko, O. A. Kutnenko, I. A. Borisova, V. V. Dyubanov, D. A. Levanov, O. A. Zyranov

“…On this basis, methods of quantitative estimation of compactness of patterns, construction of decision rules, and feature selection are developed. All these techniques are implemented in the FRiS-GRAD algorithm. …”
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Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

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A Network Analysis Approach to Detect and Differentiate Usher Syndrome Types Using miRNA Expression Profiles: A Pilot Study by Rama Krishna Thelagathoti, Wesley A. Tom, Chao Jiang, Dinesh S. Chandel, Gary Krzyzanowski, Appolinaire Olou, Rohan M. Fernando

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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

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A hybrid of an automated multi-filter with a spatial bound particle swarm optimization for gene selection and cancer classification by Anas Arram, Masri Ayob, Musatafa Abbas Abbood Albadr, Dheeb Albashish, Alaa Sulaiman

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Monitoring of Representational Difference Analysis Subtraction Procedures by Global Microarrays by T. Andersson, P. Unneberg, P. Nilsson, J. Odeberg, J. Quackenbush, J. Lundeberg

“…The compromise between focusing on only the important genes in certain cellular processes and achieving a complete picture is critical for the selection of strategy. We demonstrate how global microarray technology can be used for the exploration of the differentially expressed genes extracted through representational difference analysis (RDA). …”
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Navigating the microarray landscape: a comprehensive review of feature selection techniques and their applications by Fangling Wang, Azlan Mohd Zain, Yanjie Ren, Mahadi Bahari, Azurah A. Samah, Zuraini Binti Ali Shah, Norfadzlan Bin Yusup, Rozita Abdul Jalil, Azizah Mohamad, Nurulhuda Firdaus Mohd Azmi

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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

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Optimization based tumor classification from microarray gene expression data. by Onur Dagliyan, Fadime Uney-Yuksektepe, I Halil Kavakli, Metin Turkay

“…<h4>Background</h4>An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. …”
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Application of Chromosome Microarray in Diagnosis of Amniotic Fluid in Older Pregnant Women by Guangting Lu, Weiwu Liu, Chao Ou

“…Background: To improve the detection rate of chromosome abnormalities in fetuses and to reduce the birth defects rate in elderly pregnant women using chromosome karyotype analysis combined with the chromosome microarray analysis (CMA) technique. …”
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Consensus PCR and Microarray for Diagnosis of the Genus Staphylococcus, Species, and Methicillin Resistance by S. Hamels, J.-L. Gala, S. Dufour, P. Vannuffel, N. Zammatteo, J. Remacle

“…Products were then identified on a glass array. The microarray contained five selective DNA capture probes for the simultaneous and differential identification of the five most clinically relevant staphylococcal species (S. aureus, S. epidermidis, S. haemolyticus, S. hominis, and S. saprophyticus), while a consensus capture probe could detect all femAsequences, allowing the identification of the genus Staphylococcus. …”
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Silver coated porous silicon microarray SERS platform for detecting aflatoxin B1 fumonisin B1 and ochratoxin A by Rohit Kumar Singh, Narsingh R. Nirala, Sudharsan Sadhasivam, Divagar Muthukumar, Edward Sionov, Giorgi Shtenberg

“…Herein, we present a newly developed nanostructured microarray based on silver-coated porous silicon (Ag-pSi) used as a surface-enhanced Raman scattering (SERS) transducer. …”
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