Muhammad Hamraz¹, Dost Muhammad Khan¹, Naz Gul¹, Amjad Ali¹, Zardad Khan¹, Shafiq Ahmad², Mejdal Alqahtani², Akber Abid Gardezi³, Muhammad Shafiq^4,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3663-3677, 2023, DOI:10.32604/cmc.2023.030064

Abstract The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio (SNR). The proposed method utilizes the robust measures of location i.e., the “Median” as well as the measures of variation i.e., “Median absolute deviation (MAD) and Interquartile range (IQR)” in the SNR. By this way, two independent robust signal-to-noise ratios have been proposed. The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio (RSNR).… More >

Wei Tian¹, Lingdi Liu¹, Zhongxing Song², Zhishu Tang², Chunxiu Wen¹, Tao Jiang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.2, pp. 369-382, 2023, DOI:10.32604/phyton.2022.023184

Abstract The extract from Semen Ziziphi Spinosae (SZS) contains many secondary metabolites (flavonoids, alkaloids, and terpenoids), widely reported for their high medicinal value. In order to know the number and type of flavonoids and the regulating mechanism of flavonoid biosynthesis during the growth and development of SZS, we identified and analyzed the flavonoid metabolites and genes in SZS using metabolomic and transcriptomic. A total of 13,232 differentially expressed genes and 83 flavonoid metabolites were identified at three different growth and development stages (T1, T2, and T3) of SZS. The main flavonoid metabolic components of SZS were catechin, More >

G. Anurekha^*, P. Geetha

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3049-3064, 2023, DOI:10.32604/iasc.2023.029127

Abstract Autism Spectrum Disorder (ASD) is a complicated neurodevelopmental disorder that is often identified in toddlers. The microarray data is used as a diagnostic tool to identify the genetics of the disorder. However, microarray data is large and has a high volume. Consequently, it suffers from the problem of dimensionality. In microarray data, the sample size and variance of the gene expression will lead to overfitting and misclassification. Identifying the autism gene (feature) subset from microarray data is an important and challenging research area. It has to be efficiently addressed to improve gene feature selection and… More >

Qiang Ai, Cuijing Liu^*, Mei Han^*, Limin Yang

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2537-2548, 2022, DOI:10.32604/phyton.2022.021889

Abstract Iris domestica is a plant of the Iridaceae family and is drought-tolerant, but its drought-resistance mechanism is not yet clear. Analysing the gene expression changes of I. domestica by qRT-PCR is an important mean to understand its drought resistance characteristics. Nevertheless, a lack of reference genes greatly hinders investigation and research on the adaptation of I. domestica to drought at the molecular and genetic levels. In this study, we assessed the expression stability of 11 candidate gene in I. domestica under drought stress conditions and different tissues using geNorm, NormFinder, BestKeeper and RefFinder tools. The results showed that EF1β was More >

Minjie Liu^*, Na Gao, Yaqiong Zhao, Yingpeng Wu, Zongying Yuan

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2367-2382, 2022, DOI:10.32604/phyton.2022.021406

Abstract Lysin motif (LysM)-containing proteins (LYPs) are important pattern recognition receptors in plants. However, the evolutionary history and characteristics of LYP genes remain largely unclear in wheat. In this study, 62 LYPs were identified at genome wide in wheat. Based on phylogenetic and domain analysis, wheat LYPs were classified into 6 subgroups (group LysMe, LysMn, LYP, LYK, LysMFbox). Syntenic analysis showed the evolution of LYP genes in wheat. RNA-seq data showed that 22 genes were not expressed at any tissue or stress stimulation period. Some LYP and LYK genes were tissue- or stage- specific. The majority of TaLYK5s, More >

Yue Cai^*†‡, Chizhi Zhang^*†‡, Lei Zhan^*†, Liangbin Cheng^*†, Dingbo Lu^*†, Xiaodong Wang^*†, Hanlin Xu^§, Shuxue Wang^¶, Deng Wu^*†, Lianguo Ruan^#

Oncology Research, Vol.27, No.8, pp. 889-899, 2019, DOI:10.3727/096504018X15482423944678

Abstract The thorns of Gleditsia sinensis have been historically used in Chinese medicine and are considered one of the fundamental therapeutic herbs. Its anticancer effects are currently being explored. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and still requires the development of new drugs with higher efficiency. By using a rat HCC model implanted with cancerous Walker-256 cells, the therapeutic effects of G. sinensis extract (GSE) were assessed, as well as its regulatory effects on miRNAs. GSE significantly restored liver morphology and dramatically induced cell apoptosis in HCC rats. In addition, miR-21/181b/183 was More >

Annemarie E. M. Post^*†, Johan Bussink^*, Fred C. G. J. Sweep^†, Paul N. Span^*

Oncology Research, Vol.28, No.1, pp. 33-40, 2020, DOI:10.3727/096504019X15555794826018

Abstract Tamoxifen-induced radioresistance, reported in vitro, might pose a problem for patients who receive neoadjuvant tamoxifen treatment and subsequently receive radiotherapy after surgery. Previous studies suggested that DNA damage repair or cell cycle genes are involved, and could therefore be targeted to preclude the occurrence of cross-resistance. We aimed to characterize the observed cross-resistance by investigating gene expression of DNA damage repair genes and cell cycle genes in estrogen receptor-positive MCF-7 breast cancer cells that were cultured to tamoxifen resistance. RNA sequencing was performed, and expression of genes characteristic for several DNA damage repair pathways was… More >

Andrea Lapucci^*†1, Gabriele Perrone^*†1, Antonello Di Paolo^‡§, Cristina Napoli^*†, Ida Landini^*†, Giandomenico Roviello^*†, Laura Calosi^¶, Antonio Giuseppe Naccarato^#, Alfredo Falcone^#, Daniele Bani^¶, Enrico Mini^*†§2, Stefania Nobili^*†§2,3

Oncology Research, Vol.28, No.6, pp. 631-644, 2020, DOI:10.3727/096504020X16056983169118

Abstract The benefit of adjuvant chemotherapy in the early stages of colorectal cancer (CRC) is still disappointing and the prediction of treatment outcome quite difficult. Recently, through a transcriptomic approach, we evidenced a role of PNN and KCNQ1OT1 gene expression in predicting response to fluoropyrimidine-based adjuvant chemotherapy in stage III CRC patients. Thus, the aim of this study was to validate in an independent cohort of stages II–III CRC patients our previous findings. PNN and KCNQ1OT1 mRNA expression levels were evaluated in 74 formalin-fixed paraffin-embedded tumor and matched normal mucosa samples obtained by stages II–III CRC patients treated… More >

Bo Ling, Zuliang Huang, Suoyi Huang, Li Qian, Genliang Li, Qianli Tang

Oncology Research, Vol.28, No.6, pp. 561-578, 2020, DOI:10.3727/096504020X15907428281601

Abstract There is growing evidence on the clinical significance of tumor microenvironment (TME) cells in predicting prognosis and therapeutic effects. However, cell interactions in tumor microenvironments have not been thoroughly studied or systematically analyzed so far. In this study, 22 immune cell components in the lung adenocarcinoma (LUAD) TME were analyzed using gene expression profile from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The TME-based molecular subtypes of LUAD were defined to evaluate further the relationship between molecular subtypes, prognosis, and clinical characteristics. A TME risk score model was constructed by using the More >

Areej A. Malibari¹, Reem M. Alshehri², Fahd N. Al-Wesabi³, Noha Negm³, Mesfer Al Duhayyim⁴, Anwer Mustafa Hilal^5,*, Ishfaq Yaseen⁵, Abdelwahed Motwakel⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4277-4290, 2022, DOI:10.32604/cmc.2022.027030

Abstract In bioinformatics applications, examination of microarray data has received significant interest to diagnose diseases. Microarray gene expression data can be defined by a massive searching space that poses a primary challenge in the appropriate selection of genes. Microarray data classification incorporates multiple disciplines such as bioinformatics, machine learning (ML), data science, and pattern classification. This paper designs an optimal deep neural network based microarray gene expression classification (ODNN-MGEC) model for bioinformatics applications. The proposed ODNN-MGEC technique performs data normalization process to normalize the data into a uniform scale. Besides, improved fruit fly optimization (IFFO) based… More >