Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

Subjects: “…Microarray gene selection…”
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DurdusTools—An Online Genetic Distance Calculation Tool for Efficient Variety Testing in Durum Wheat (<i>Triticum turgidum</i> L. subsp. <i>durum</i> (Desf.) Husn.) by Alexandra Ribarits, Svenja Bomers, Tadej Zerak, Oliver Alber, Jakob Seereiter, Antonio Escolano García, Ana Lázaro Somoza, Anna Pia Maria Giulini, Ferenc Somogyi, Sándor Kőrösi, Jutta Taferner-Kriegl

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A two stage grading approach for feature selection and classification of microarray data using Pareto based feature ranking techniques: A case study by Rasmita Dash

“…High dimensional search space in microarray data with large number of genes and few dozen of samples increases the complexity of analysis of such databases. …”
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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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Microarray-Based Cancer Diagnosis with Artificial Neural Networks by Markus Ringnér, Carsten Peterson

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Listen to genes: dealing with microarray data in the frequency domain. by Jianfeng Feng, Dongyun Yi, Ritesh Krishna, Shuixia Guo, Vicky Buchanan-Wollaston

“…<h4>Background</h4>We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes.…”
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Identification and characterization of gene networks and key genes related to the high-yield production of milk in high-yield cows using meta-analysis of microarray data by Mahdi Rahmatzadeh, Reza Shokri-Gharelo, Morteza Derakhti-Dizaji, Asghar Bazzaz, Bizhan Mahmoudi

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Identification of intragenic variants in pediatric patients with intellectual disability in Peru by Hugo Hernán Abarca-Barriga, Flor Vásquez Sotomayor, Renzo Punil-Luciano, María Cristina Laso-Salazar, Heli Jaime Barrón-Pastor

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The miRNA‐mRNA Regulatory Network in Human Hepatocellular Carcinoma by Transcriptomic Analysis From GEO by Razieh Heidari, Vahideh Assadollahi, Seyedeh Negar Marashi, Fatemeh Elahian, Seyed Abbas Mirzaei

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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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Transfer learning for accelerated failure time model with microarray data by Yan-Bo Pei, Zheng-Yang Yu, Jun-Shan Shen

“…Abstract Background In microarray prognostic studies, researchers aim to identify genes associated with disease progression. …”
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Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma by Metoboroghene O. Mowoe, Metoboroghene O. Mowoe, Hisham Allam, Joshua Nqada, Marc Bernon, Karan Gandhi, Sean Burmeister, Urda Kotze, Miriam Kahn, Christo Kloppers, Suba Dharshanan, Zafirah Azween, Pamela Maimela, Paul Townsend, Eduard Jonas, Jonathan M. Blackburn, Jonathan M. Blackburn

“…Autoantibodies (AAbs) in principle make attractive biomarkers as they arise early in disease, report on disease-associated perturbations in cellular proteomes, and are static in response to other common stimuli, yet are measurable in the periphery, potentially well in advance of the onset of clinical symptoms.MethodsHere, we used high-throughput, custom cancer antigen microarrays to identify a clinically relevant autoantibody biomarker combination able to differentially detect PDAC. …”
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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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LIMA1-alpha staining predicts curative intent surgery response in HPV negative head and neck cancer by Xi Qiao, Johannes Routila, Mari Tienhaara, Heikki Irjala, Priyadharshini Parimelazhagan Santhi, Teemu Huusko, Linda Nissi, Ilkka Paatero, Noora Lehtinen, Juha Rantala, Toni Viljanen, Ilmo Leivo, Petri Koivunen, Anna Jouppila-Mättö, Rami Taulu, Leif Bäck, Tommy Wilkman, Eeva Haapio, Ilpo Kinnunen, Kari Kurppa, Jukka Westermarck, Sami Ventelä

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Transcriptional responses in different mouse models of septic liver injury differ from those in patients with septic liver injury by Qin Yan, Qin Yan, Qin Yan, Wei Fan, Wei Fan, Wei Fan, Xinsen He, Xinsen He, Xinsen He, Shi Zheng, Shi Zheng, Shi Zheng, Xiaolin Zhong, Xiaolin Zhong, Xiaolin Zhong

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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

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A Novel Ensemble Feature Selection Technique for Cancer Classification Using Logarithmic Rank Aggregation Method by Hüseyin Öztoprak, Hüseyin Güney

“…Recent studies have shown that ensemble feature selection (EFS) has achieved outstanding performance in microarray data classification. …”
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Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction by John H. Phan, Andrew N. Young, May D. Wang

“…Combining multiple microarray datasets increases sample size and leads to improved reproducibility in identification of informative genes and subsequent clinical prediction. …”
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High reproducibility using sodium hydroxide-stripped long oligonucleotide DNA microarrays by Zhiyuan Hu, Melissa Troester, Charles M. Perou

“…In addition, when there is limited availability of mRNA from tissue sources, RNA amplification can and is being used to produce sufficient quantities of cRNA for microarray hybridization. Taking advantage of the selective degradation of RNA under alkaline conditions, we have developed a method to “strip” glass-based oligonucleotide microarrays that use fluorescent RNA in the hybridization, while leaving the DNA oligonucleotide probes intact and usable for a second experiment. …”
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Microarray Data Analysis: From Hypotheses to Conclusions Using Gene Expression Data by Nicola J. Armstrong, Mark A. van de Wiel

“…We review several commonly used methods for the design and analysis of microarray data. To begin with, some experimental design issues are addressed. …”
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