Global effects of DNA replication and DNA replication origin activity on eukaryotic gene expression by Larsson Omberg, Joel R Meyerson, Kayta Kobayashi, Lucy S Drury, John F X Diffley, Orly Alter

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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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A microarray platform-independent classification tool for cell of origin class allows comparative analysis of gene expression in diffuse large B-cell lymphoma. by Matthew A Care, Sharon Barrans, Lisa Worrillow, Andrew Jack, David R Westhead, Reuben M Tooze

“…This shows superior survival separation for assigned Activated B-cell (ABC) and Germinal Center B-cell (GCB) DLBCL classes relative to a range of other classifiers. DAC is effective on data derived from multiple microarray platforms and formalin fixed paraffin embedded samples and is parsimonious, using 20 classifier genes. …”
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Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment by Ali Shakeri Abroudi, Melika Djamali, Hossein Azizi

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Hemizygous contiguous gene deletion within Xq28 that includes BCAP31, ABCD1, SRPK3 and SSR4: case report and literature review by Joan Chern-Hui Lien, Vinay D. Chandrasekaran, Tarachandra M. Narumanchi, Melissa S. Napoli, Jo Elle G. Peterson, Charles A. Williams

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Copula-Based Bayesian Model for Detecting Differential Gene Expression by Prasansha Liyanaarachchi, N. Rao Chaganty

“…Finally, we apply our model to <i>Escherichia coli</i> microarray data, illustrating its practical utility in gene expression analysis.…”
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Higher expression of mir‐31‐5p is associated with reduced risk of head and neck keloid recurrence following surgical resection by Albert M. Levin, Oghenefejiro Okifo, Katherine Buhl, Takahiro Ouchi, Bianca Parker, Jessica Tan, Indrani Datta, Xiangguo Dai, Yalei Chen, Nallasivam Palanisamy, Jesse Veenstra, Shannon Carskadon, Jia Li, David Ozog, Christian E. Keller, Dhananjay Chitale, Kevin R. Bobbitt, Howard C. Crawford, Nina Steele, Qing‐Sheng Mi, Lamont R. Jones

“…Methods Using a tissue microarray, mir‐31‐5p expression was measured with miRNAscope, and mir‐31‐5p cell positivity was determined with QuPath. …”
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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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Dissection of a complex transcriptional response using genome‐wide transcriptional modelling by Martino Barenco, Daniel Brewer, Efterpi Papouli, Daniela Tomescu, Robin Callard, Jaroslav Stark, Michael Hubank

“…We examined the transcriptional response to DNA damage in a human T cell line (MOLT4) using microarrays. By measuring both mRNA accumulation and degradation over a short time course, we were able to construct a mechanistic model of the transcriptional response. …”
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Genome-wide profiling of micro-RNA expression in gefitinib-resistant human lung adenocarcinoma using microarray for the identification of miR-149-5p modulation by Yong Hu, Xiaobing Qin, Dali Yan, Haixia Cao, Leilei Zhou, Fan Fan, Jialan Zang, Jie Ni, Xiaoyue Xu, Huanhuan Sha, Siwen Liu, Shaorong Yu, Jianzhong Wu, Rong Ma, Jifeng Feng

“…We compared the micro-RNA expression profiles of the HCC827 cells HCC827/GR-8-1 using Agilent micro-RNA microarrays. The micro-RNAs, such as the miR-149-5p, were up- or downregulated and associated with acquired gefitinib resistance. …”
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A Versatile High‐Throughput Single‐Cell Screening Platform for Profiling Antigen‐Specific Long‐Lived B Cells in Blood and Bone Marrow by Tian Zhao, Yuqing Lei, Chang Liu, Dong Zhang, Kaiyi Li, Sisi Shan, Chenyu Li, Zimeng Wei, Yuhan Yang, Ting Zhang, Kai Sun, Haoran Sun, Linqi Zhang, Peng Liu

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Investigation of local corrosion behavior and mechanism for TA2/HAl77-2/316L SS coupling systems under seawater liquid film by Hong Ju, Hanzhi Li, Lu Fang, Haitong Lu, Yifan Wei

“…Local corrosion parameters, such as the maximum potential difference (ΔEmax), the maximum anode current density (Ia,max), the local corrosion intensity factor (LCII), and the cathode to anode area ratio (Sc/Sa) were obtained to quantitatively characterize the local corrosion degree of microarray electrodes. The results showed that HAl77-2 and most of the 316L SS electrode wires in the microarray electrodes served as anodes, while TA2 and the remainder of the 316L SS electrode wires performed as cathodes. …”
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Exposing Optimal Feature Sets for Enhancing Machine Learning Performance by Hiba Mohammed Al-Marwai, Ghaleb H. Al-Gaphari, Mohammed Mohammed Zayed

“…The opposition based learning (OBL) technique is used to mitigate the risk of CSA converging towards local optima. To evaluate the effectiveness of our approach, we conduct experiments on benchmark microarray datasets from the ADNI database. …”
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Successful strategy of comprehensive pre-implantation genetic testing for Duchenne muscular dystrophy and chromosome balance using karyomapping and fluorescent PCR by Suchada Mongkolchaipak, Sirivipa Piyamongkol, Chutithep Teekaput, Rungthiwa Sirapat, Wanwisa Suriya, Tawiwan Pantasri, Theera Tongsong, Wirawit Piyamongkol

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SINGLE NUCLEOTIDE POLYMORPHISMS IN BREAST TUMOR AND EXPRESSION OF ABC-TRANSPORTERS AFTER NEOADJUVANT CHEMOTHERAPY by M. M. Tsyganov, M. K. Ibragimova, E. M. Slonimskaya, N. V. Cherdyntseva, N. V. Litviakov

“…Using a quantitative Real-time PCR, the expression of 4 multidrug resistence (MDR) genes (ABCB1, ABCC1, ABCC2, ABCG2) was studied in surgical samples after NAC. Microarray analysis was performed using high density DNA microarrays, which contain more than 750.000 SNPs. …”
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Search for polymorphic variants of candidate genes contributing to individual radiosensitivity by D. S. Isubakova, N. V. Litviakov, O. S. Tsymbal, T. V. Usova, M. Yu. Tsyplenkova, I. V. Milto, R. M. Takhauov

“…DNA was genotyped using 257 SNPs of cyclin genes and neighboring intergenic regions using DNA microarrays from the high-density CytoScan HD Array (Affymetrix, USA).Results. …”
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Role of transcriptomics in the study of oral cancer by Prabhu Manickam Natarajan, Vidhya Rekha Umapathy

“…We delve into RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), long non-coding RNA sequencing (lncRNA-seq), microarray analysis, and small RNA profiling, showcasing their unique contributions to unraveling the complexities of oral cancer. …”
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Rapid Whole-Genome Sequencing in Critically Ill Infants and Children with Suspected, Undiagnosed Genetic Diseases: Evolution to a First-Tier Clinical Laboratory Test in the Era of... by Rina Kansal

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Structure preserving t-SNE of matrix framed data by Soohyun Ahn, Johan Lim, Wei Jiang, Sungim Lee, Xinlei Wang

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Genetic testing for diagnosing neurodevelopmental disorders and epilepsy: a systematic review and meta-analysis by Yu-Ming Chang, Yen-Ta Huang, Pei-Chun Lai

“…Abstract Background Identifying the genetic causes of neurodevelopmental disorders (NDDs) and epilepsy is crucial for effective treatment and genetic counseling. Our objective was to determine the diagnostic yield of chromosomal microarray (CMA) and next-generation sequencing (NGS) methods—including targeted sequencing (TS), whole-exome sequencing (WES), and whole-genome sequencing (WGS)—in individuals with NDDs or epilepsy. …”
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