WEI LIANG^1,2,*, QIANG LUO^1,2,#, ZONGWEI ZHANG^1,2,#, KEJU YANG^1,2,3, ANKANG YANG^1,2, QINGJIA CHI⁴, HUAN HU⁵

BIOCELL, Vol.46, No.8, pp. 1989-2002, 2022, DOI:10.32604/biocell.2022.019300

Abstract Diabetic nephropathy (DN) is a common microvascular complication that easily leads to end-stage renal disease. It is important to explore the key biomarkers and molecular mechanisms relevant to diabetic nephropathy (DN). We used highthroughput RNA sequencing to obtain the genes related to DN glomerular tissues and healthy glomerular tissues of mice. Then we used LIMMA to analyze differentially expressed genes (DEGs) between DN and non-diabetic glomerular samples. And we performed KEGG, gene ontology functional (GO) enrichment, and gene set enrichment analysis to reveal the signaling pathway of the disease. The CIBERSORT algorithm based on support vector machine was used to… More >

Medhat A. Tawfeek^1,2,*, Saad Alanazi¹, A. A. Abd El-Aziz^3,4

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6091-6106, 2022, DOI:10.32604/cmc.2022.028391

Abstract The alignment operation between many protein sequences or DNA sequences related to the scientific bioinformatics application is very complex. There is a trade-off in the objectives in the existing techniques of Multiple Sequence Alignment (MSA). The techniques that concern with speed ignore accuracy, whereas techniques that concern with accuracy ignore speed. The term alignment means to get the similarity in different sequences with high accuracy. The more growing number of sequences leads to a very complex and complicated problem. Because of the emergence; rapid development; and dependence on gene sequencing, sequence alignment has become important in every biological relationship analysis… More >

Huimin Cui, Shuo Qu, Abraham Lamboro, Yaolei Jiao, Piwu Wang^*

Phyton-International Journal of Experimental Botany, Vol.91, No.7, pp. 1445-1464, 2022, DOI:10.32604/phyton.2022.020010

Abstract In agricultural production, a single insect-resistant and disease-resistant variety can no longer meet the demand. In this study, the expression vector pCAMBIA-3301-PR1 containing the disease-resistant gene PR1 was constructed by means of genetic engineering, and the PR1 gene was genetically transformed to contain the PR1 gene through the pollen tube method. In CryAb-8Like transgenic high-generation T₇ receptor soybean, a new material that is resistant to insects and diseases is obtained. For T₂ transformed plants, routine PCR detection, Southern Blot hybridization, fluorescence quantitative PCR detection, indoor and outdoor pest resistance identification and indoor disease resistance identification were performed. The results showed… More >

Mahmoud Ragab^1,2,3,*, Khalid Eljaaly⁴, Maha Farouk S. Sabir⁵, Ehab Bahaudien Ashary⁶, S. M. Abo-Dahab^7,8, E. M. Khalil^3,9

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5751-5764, 2022, DOI:10.32604/cmc.2022.024658

Abstract The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological systems. Due to the advancements of medical imaging in healthcare decision making, significant attention has been paid by the computer vision and deep learning (DL) models. At the same time, the detection and classification of colorectal cancer (CC) become essential to reduce the severity of the disease at an earlier stage. The existing methods are commonly based on the combination of textual features to examine the classifier results or machine learning (ML)… More >

RUI XU¹, QIBIAO WU¹, YUHAN GONG², YONGZHE WU¹, QINGJIA CHI^1,*, DA SUN^3,*

BIOCELL, Vol.46, No.5, pp. 1261-1288, 2022, DOI:10.32604/biocell.2022.018427

Abstract There is currently no effective solution to the problem of poor prognosis and recurrence of HCC. The technology of immunotherapy and prognosis of genetic material has made continuous progress in recent years. In the study, a 5-gene signature was established for the prognosis of HCC through biological information, and the immune infiltration of HCC patients was studied. After studied HCC patients’ immune infiltration, the paper screened the differential target genes of miR-126-3p in HCC downloaded from TCGA database, and uses WGCNA method to select the modular genes highly relevant to M2 macrophage. Then we use LASSO and COX regression analysis… More >

KATARINA BARALIć^1,*, KATARINA ŽIVANčEVIć¹, DRAGICA BoŽIĆ¹, DANYEL JENNEN², ALEKSANDRA BUHA DJORDJEVIC¹, EVICA ANTONIJEVIć MILJAKOVIć¹, DANIJELA ĐUKIć-ĆOSIć¹

BIOCELL, Vol.46, No.2, pp. 519-533, 2022, DOI:10.32604/biocell.2022.018271

Abstract This in silico toxicogenomic study aims to explore the relationship between phthalates and bisphenol A (BPA) co-exposure and obesity, as well as its comorbid conditions, in order to construct a possible set of genomic biomarkers. The Comparative Toxicogenomics Database (CTD; http://ctd.mdibl.org) was used as the main data mining tool, along with GeneMania (https://genemania.org), ToppGene Suite (https://toppgene.cchmc.org) and DisGeNET (http://www.disgenet.org). Among the phthalates, bis(2-ethylhexyl) phthalate (DEHP) and dibutyl phthalate (DBP) were chosen as the most frequently curated phthalates in CTD, which also share similar mechanisms of toxicity. DEHP, DBP and BPA interacted with 84, 90 and 194 obesity-related genes/proteins, involved in… More >

S. Sathiya Devi¹, S. Vidivelli^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3049-3066, 2022, DOI:10.32604/cmc.2022.019917

Abstract Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer. The present research work is useful in image processing for characterizing shape and gray-scale complexity. The proposed Modified Differential Box Counting (MDBC) extract Fractal features such as Fractal Dimension (FD), Lacunarity, and Succolarity for shape characterization. In traditional DBC method, the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels. The problem is overcome by the proposed MDBC method that uses box over counting and under counting that covers the… More >

Lejun Gong^1,2,*, Xingxing Zhang¹, Li Zhang³, Zhihong Gao⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 31-45, 2021, DOI:10.32604/cmes.2021.016622

Abstract Novel coronavirus disease 2019 (COVID-19) is an ongoing health emergency. Several studies are related to COVID-19. However, its molecular mechanism remains unclear. The rapid publication of COVID-19 provides a new way to elucidate its mechanism through computational methods. This paper proposes a prediction method for mining genotype information related to COVID-19 from the perspective of molecular mechanisms based on machine learning. The method obtains seed genes based on prior knowledge. Candidate genes are mined from biomedical literature. The candidate genes are scored by machine learning based on the similarities measured between the seed and candidate genes. Furthermore, the results of… More >

Khalid Mahmood Aamir¹, Muhammad Bilal², Muhammad Ramzan^1,3, Muhammad Attique Khan⁴, Yunyoung Nam^5,*, Seifedine Kadry⁶

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3829-3844, 2021, DOI:10.32604/cmc.2021.017835

Abstract Retroviruses are a large group of infectious agents with similar virion structures and replication mechanisms. AIDS, cancer, neurologic disorders, and other clinical conditions can all be fatal due to retrovirus infections. Detection of retroviruses by genome sequence is a biological problem that benefits from computational methods. The National Center for Biotechnology Information (NCBI) promotes science and health by making biomedical and genomic data available to the public. This research aims to classify the different types of rotavirus genome sequences available at the NCBI. First, nucleotide pattern occurrences are counted in the given genome sequences at the preprocessing stage. Based on… More >

Fahad Alotaibi¹, Muhammad Attique^2,3, Yaser Daanial Khan^2,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1039-1055, 2021, DOI:10.32604/cmc.2021.017297

Abstract Several autoimmune ailments and inflammation-related diseases emphasize the need for peptide-based therapeutics for their treatment and established substantial consideration. Though, the wet-lab experiments for the investigation of anti-inflammatory proteins/peptides (“AIP”) are usually very costly and remain time-consuming. Therefore, before wet-lab investigations, it is essential to develop in-silico identification models to classify prospective anti-inflammatory candidates for the facilitation of the drug development process. Several anti-inflammatory prediction tools have been proposed in the recent past, yet, there is a space to induce enhancement in prediction performance in terms of precision and efficiency. An exceedingly accurate anti-inflammatory prediction model is proposed, named AntiFlamPred… More >