Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

“…However, the late enriched understanding of the genetic underpinnings of AD has been made possible due to recent advancements in data mining analysis methods, machine learning, and microarray technologies. However, the “curse of dimensionality” caused by the high-dimensional microarray datasets impacts the accurate prediction of the disease due to issues of overfitting, bias, and high computational demands. …”
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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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Automated evaluation and normalization of immunohistochemistry on tissue microarrays with a DNA microarray scanner by Wolfgang Haedicke, Helmut H. Popper, Charles R. Buck, Kurt Zatloukal

“…Importantly, double-label indirect immunofluorescence detection with the cDNA scanner demonstrates that one reference antigen can normalize tumor marker immunosignal for the cellular content of tissue microarray tissue cores. …”
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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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Laboratory validation of formal concept analysis of the methylation status of microarray-detected genes in primary breast cancer by Samar K Kassim, Hanan H Shehata, Marwa M Abou-Alhussein, Maha M Sallam, Islam Ibrahim Amin

“…These results validate the methylation-based microarray analysis, thus trust their output in the future.…”
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Evaluation of the performance of two carbodiimide-based cyanine dyes for detecting changes in mRNA expression with DNA microarrays by Naoki Kimura, Taka-aki Tamura, Masahiro Murakami

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Portable Fluorescence Microarray Reader-Enabled Biomarker Panel Detection System for Point-of-Care Diagnosis of Lupus Nephritis by Aygun Teymur, Iftak Hussain, Chenling Tang, Ramesh Saxena, David Erickson, Tianfu Wu

“…This study introduces an LED-based fluorescence reader designed for POC applications, enabling multiplex detection of lupus nephritis (LN) biomarkers using a biomarker microarray (BMA) slide. …”
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Copula-Based Bayesian Model for Detecting Differential Gene Expression by Prasansha Liyanaarachchi, N. Rao Chaganty

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Advancing Dermatomycosis Diagnosis: Evaluating a Microarray-Based Platform for Rapid and Accurate Fungal Detection—A Pilot Study by Vittorio Ivagnes, Elena De Carolis, Carlotta Magrì, Riccardo Torelli, Brunella Posteraro, Maurizio Sanguinetti

“…This study evaluates the EUROArray Dermatomycosis Platform, a microarray-based molecular assay, for its performance in identifying fungi causing dermatomycosis. …”
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Comparative analysis of hybrid-SNP microarray and nanopore sequencing for detection of large-sized copy number variants in the human genome by Catarina Silva, José Ferrão, Bárbara Marques, Sónia Pedro, Hildeberto Correia, Ana Valente, António Sebastião Rodrigues, Luís Vieira

“…In this work, we used nanopore sequencing technology to sequence 2 human cell lines at low depth of coverage to call copy number variations (CNV), and compared the results variant by variant with chromosomal microarray (CMA) results. Results We analysed sequencing data using CuteSV and Sniffles2 variant callers, compared breakpoints based on hybrid-SNP microarray, nanopore sequencing and Sanger sequencing, and analysed CNV coverage. …”
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Case of 7p22.1 Microduplication Detected by Whole Genome Microarray (REVEAL) in Workup of Child Diagnosed with Autism by Veronica Goitia, Marcial Oquendo, Robert Stratton

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Using effective subnetworks to predict selected properties of gene networks. by Gemunu H Gunaratne, Preethi H Gunaratne, Lars Seemann, Andrei Török

“…Steady state measurements of these influence networks can be obtained from DNA microarray experiments. However, since they contain a large number of nodes, the computation of influence networks requires a prohibitively large set of microarray experiments. …”
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Genetic feature selection algorithm as an efficient glioma grade classifier by Ting-Han Lin, Hung-Yi Lin

“…Genetic testing is a rapidly evolving modality for cancer management. The advent of DNA microarrays enabled the utility of computational analyses in such management on a molecular basis. …”
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Robust molecular subgrouping and reference-free aneuploidy detection in medulloblastoma using low-depth whole genome bisulfite sequencing by Dean Thompson, Jemma Castle, Martin Sill, Stefan M. Pfister, Simon Bailey, Debbie Hicks, Steven C. Clifford, Edward C. Schwalbe

“…We further assessed and optimised reference-free aneuploidy detection using low-pass WGBS and assessed concordance with microarray-derived calls. …”
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Whole genome uniparental isodisomy detected using single nucleotide polymorphism (SNP) microarray in molar pregnancy: a case report by Onyinye O. Okonkwo, Veronica Ortega, Sheila Kane, Galina Aldrete, Paulina Ramirez, Philip T. Valente, Gopalrao V.N. Velagaleti

“…High-resolution SNP microarray studies detected whole genome uniparental isodisomy. …”
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CFS-MOES Ensemble Model on Metaheuristic Search-Based Feature Selection by Santosini Bhutia, Bichitrananda Patra, Mitrabinda Ray

“…Due to the availability of highly specialized cancer datasets, molecular classification of cancer by gene expression, machine learning, and deep learning, a part of artificial intelligence (AI) techniques is used in detecting the disease. The application of several classification and feature selection methods on microarray gene expression datasets helps learn models that are able to predict a given disease. …”
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Expression of long non-coding RNA in patients with non-IgA mesangial proliferative glomerulonephritis by CONG Shan, SUI Wei-guo, ZOU Gui-mian, XUE Wen, LI Huan, YAN Qiang, CHEN Jie-jing, LUO Ya-dan, CHEN Huai-zhou

“…Objective To study differential expression profile of mRNA and long non-coding RNA(IncRNA) through microarray analysis between non-IgA mesangial proliferative glomerulonephritis(MsPGN) patients and the controls,and then explore the potential role of IncRNA in the pathogenesis of non-IgA MsPGN.Methods Through simple random sampling,4 patients with non-IgA MsPGN and 2 controls were selected as disease group and control group,respectively.Renal cortical tissues from two groups were collected.Total RNA was extracted,quantified and prepared to ds-cDNA through reverse transcription ds-cDNA was labeled with NimbleGen one-color DNA labeling kit and used for array hybridization.All experimental data were processed through GO analysis,Pathway analysis and the gene loci correlation analysis of mRNA and IncRNA.Some IncRNAs that were closely related to non-IgA MsPGN were screened out.Finally,part of the array results was detected by PCR to verify the reliability of array test Results By fold change filtering,4317 differentially expressed mRNAs and 3502 differentially expressed IncRNAs were screened out.Five IncRNAs were found to play potential roles in the pathogenesis of non-IgA MsPGN:AF1180924(close to coding gene FGG),AK092233(close to coding gene COL18A1),AK130579(close to coding gene CREBBP),AK023598(close to coding gene LEPR),and AK055915(close to coding gene CDC42EP3).These results provided an important basis for revealing the pathogenesis of non-IgA MsPGN.Conclusions Some IncRNAs can potentially regulate related genes and plays an important role in the pathogenesis and development of non-IgA MsPGN.…”
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A Highly Discriminative Hybrid Feature Selection Algorithm for Cancer Diagnosis by Tarneem Elemam, Mohamed Elshrkawey

“…To examine the proposed algorithm, many tests have been carried out on four cancerous microarray datasets, employing in the process 10-fold cross-validation and hyperparameter tuning. …”
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Optimized T7 Amplification System for Microarray Analysis by C. Pabón, Z. Modrusan, M.V. Ruvolo, I.M. Coleman, S. Daniel, H. Yue, L.J. Arnold, M.A. Reynolds

“…Glass cDNA microarray technologies offer a highly parallel approach for profiling expressed gene sequences in disease-relevant tissues. …”
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Analysis of a Series of 26 Cases With Prenatal Skeletal Dysplasia via Multiplatform Genetic Detection by Li‐min Cui, Hua‐ying Hu, Xiao‐mei Zhai, Ming‐fei Qi, Yan‐ming Liu, Cong‐ying Han, Jing Zhang, Ming Shen, Yu‐lan Xiang, Wen‐qi Chen, Kai Yang, Dong‐liang Zhang, Huan‐xia Xing

“…Materials and Methods In this study, we recruited 26 cases of SD and analyzed them with a designed sequential genetic detection. Chromosome karyotyping, microarray analysis (CMA), and whole exome sequencing (WES) techniques are performed as needed. …”
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