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

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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

“…The high efficiency of the algorithm is illustrated by results of solving the task of disease recognition on a microarray dataset.…”
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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

Subjects: “…Early diabetes detection…”
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Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion. by Doris Steger, David Berry, Susanne Haider, Matthias Horn, Michael Wagner, Roman Stocker, Alexander Loy

“…Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias.<h4>Conclusions</h4>Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.…”
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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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Photopolymerization as an innovative detection technique for low-density microarrays by Laura R. Kuck, Amber W. Taylor

“…One limitation that accounts in part for the scarcity of commercially available diagnostic microarrays is the expense associated with fluorescence detection. …”
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Oral Bacteria of Children with Turner Syndrome by Gülcan Ünsal, Nursen Topçuoğlu, Yeliz Güven, Şükran Poyrazoğlu, Güven Külekçi, Oya Aktören

“…Plaque index and gingival index levels were significantly higher in the Turner group and dft was significantly higher in the control group (p<0.05). As a result, microarray analysis, Prevotella intermedia, Fusobacterium nucleatum, Eikenella corrodens, Aggregatibacter actinomycetemcomitans, Actinomyces viscosus were detected at high levels in the Turner group (p<0.05).Conclusion:Besides dental and craniofacial anomalies, clinicians should be alert to the early diagnosis and treatment of periodontal problems in patients with TS.…”
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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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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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A standardized fold change method for microarray differential expression analysis used to reveal genes involved in acute rejection in murine allograft models by Weichen Zhou, Yi Wang, Masayuki Fujino, Leming Shi, Li Jin, Xiao‐Kang Li, Jiucun Wang

“…We suggest that SFC can be utilized to stably and effectively detect differential gene expression and to explore microarray data in further studies.…”
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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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CCD Standard Curve Fitting for Microarray Detection Base on Multi-Layer Perceptron by Zhenhua Gan, Dongyu He, Peishu Wu, Baoping Xiong, Nianyin Zeng, Fumin Zou, Feng Guo, Qin Bao, Fengyan Zhao

“…The gray-level of the fluorescent probe in detection image was obtained as the data set acquired by the microarray scanner at different exposure time. …”
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Evaluating methods for identifying and quantifying Streptococcus pneumoniae co-colonization using next-generation sequencing data by Jada Hackman, Martin L. Hibberd, Todd D. Swarthout, Jason Hinds, James Ashall, Carmen Sheppard, Gerry Tonkin-Hill, Kate Gould, Comfort Brown, Jacquline Msefula, Andrew A. Mataya, Michiko Toizumi, Lay-Myint Yoshida, Neil French, Robert S. Heyderman, Stefan Flasche, Brenda Kwambana, Stéphane Hué

“…Across the 24 individuals, the microarray detected 77 non-unique serotypes, of which 42 occurred at high relative abundance (>10%) (per individual, median, 3; range, 1–6 serotypes). …”
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Microarray construction of antimicrobial resistance genes from Salmonella by MA Meng-gen, WANG Hong-ning, YU Yong, ZHANG Dong, LIU Shi-gui

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Development and Validation of Protein Microarray Technology for Simultaneous Inflammatory Mediator Detection in Human Sera by Senthooran Selvarajah, Ola H. Negm, Mohamed R. Hamed, Carolyn Tubby, Ian Todd, Patrick J. Tighe, Tim Harrison, Lucy C. Fairclough

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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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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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Assessment of centrifugation using for accelerated immunological microarray analysis for blood cells investigation by A. V. Shishkin, N. G. Ovchinina, S. S. Bessmeltsev

Subjects: “…immunological microarray…”
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Pico-Scale Digital PCR on a Super-Hydrophilic Microarray Chip for Multi-Target Detection by Qingyue Xian, Jie Zhang, Yu Ching Wong, Yibo Gao, Qi Song, Na Xu, Weijia Wen

“…In this study, we present a super-hydrophilic microarray chip specifically designed for dPCR, featuring streamlined loading methods compatible with micro-electro-mechanical systems (MEMS) technology. …”
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