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 cha...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 feature selection technique is used to reduce the high dimensionality in the biomedical data.Moreover,deep neural network(DNN)model is applied for the classification of microarray gene expression data and the hyperparameter tuning of the DNN model is carried out using the Symbiotic Organisms Search(SOS)algorithm.The utilization of IFFO and SOS algorithms pave the way for accomplishing maximum gene expression classification outcomes.For examining the improved outcomes of the ODNN-MGEC technique,a wide ranging experimental analysis is made against benchmark datasets.The extensive comparison study with recent approaches demonstrates the enhanced outcomes of the ODNN-MGEC technique in terms of different measures.展开更多
Differences between healthy subjects and associated disease risks are of substantial interest in clinical medicine. Based on clinical presentations, Traditional Chinese Medicine (TCM) classifies healthy people into ...Differences between healthy subjects and associated disease risks are of substantial interest in clinical medicine. Based on clinical presentations, Traditional Chinese Medicine (TCM) classifies healthy people into nine constitutions: Balanced, Qi, Yang or Yin deficiency, Phlegm-dampness, Damp-heat, Blood stasis, Qi stagnation, and Inherited special constitutions. In particular, Yang and Yin deficiency constitutions exhibit cold and heat aversion, respectively. However, the intrinsic molecular characteristics of unbal- anced phenotypes remain unclear. To determine whether gene expression-based clustering can reca- pitulate TCM-based classification, peripheral blood mononudear cells (PBMCs) were collected from Chinese Han individuals with Yang/Yin deficiency (n = 12 each) and Balanced (n = 8) constitutions, and global gene expression profiles were determined using the Affymetrix HC-UI33A Plus 2.0 array. Notably, we found that gene expression-based classifications reflected distinct TCM-based subtypes. Consistent with the clinical observation that subjects with Yang deficiency tend toward obesity, series-clustering analysis detected several key lipid metabolic genes (diacylglycerol acyltransferase (DGAT2), acyl-CoA synthetase (ACSL1), and ATP-hinding cassette subfamily A member 1 (ABCAI)) to be down- and up- regulated in Yin and Yang deficiency constitutions, respectively. Our findings suggest that Yin]Yang deficiency and Balanced constitutions are unique entities in their mRNA expression profiles. Moreover, the distinct physical and clinical characteristics of each unbalanced constitution can be explained, in part, by specific gene expression signatures.展开更多
Most of adult female mosquitoes secrete saliva to facilitate blood sucking, digestion and nutrition, and mosquito-borne disease prevention. The knowledge of classification and characteristics of sialotranscriptome gen...Most of adult female mosquitoes secrete saliva to facilitate blood sucking, digestion and nutrition, and mosquito-borne disease prevention. The knowledge of classification and characteristics of sialotranscriptome genes are still quite limited, Anopheles sinensis is a major malaria vector in China and southeast Asian countries. In this study, the An. sinensis sialotranscriptome was sequenced using Illumina sequencing technique with a total of 10 907 unigenes to be obtained and annotated in biological functions and pathways, and 10 470 tmigenes were mapped to An. sinensis reference genome with 70.46% of genes having 90%- 100% genome mapping through bioinformatics analysis. These mapped genes were classified into four categories: housekeeping (6632 genes), secreted (1177), protein-coding genes with function-unknown (2646) and transposable element (15). The housekeeping genes were divided into 27 classes, and the secreted genes were divided into 11 classes and 96 families. The classification, characteristics and evolution of these classes/families of secreted genes are further described and discussed. The comparison of the 1177 secreted genes in An. sinensis in the Anophelinae subfamily with 811 in Psorophora albipes in the Culicinae subfamily show that six classes/subclasses have the gene number more than twice and two classes (uniquely found in anophelines, and Orphan proteins of unique standing) are unique in the former compared with the latter, whereas four classes/subclasses are much expanded and uniquely found in the Aedes class and is unique in the later. The An. sinensis sialotranscriptome sequence data is the most complete in mosquitoes to date, and the analyses provide a comprehensive information frame for further research of mosquito sialotranscriptome.展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP 2/42/43)This work was supported by Taif University Researchers Supporting Program(project number:TURSP-2020/200),Taif University,Saudi Arabia.
文摘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 feature selection technique is used to reduce the high dimensionality in the biomedical data.Moreover,deep neural network(DNN)model is applied for the classification of microarray gene expression data and the hyperparameter tuning of the DNN model is carried out using the Symbiotic Organisms Search(SOS)algorithm.The utilization of IFFO and SOS algorithms pave the way for accomplishing maximum gene expression classification outcomes.For examining the improved outcomes of the ODNN-MGEC technique,a wide ranging experimental analysis is made against benchmark datasets.The extensive comparison study with recent approaches demonstrates the enhanced outcomes of the ODNN-MGEC technique in terms of different measures.
基金supported by the National Key Basic Research Program of China (973 Program No. 2011CB505400)
文摘Differences between healthy subjects and associated disease risks are of substantial interest in clinical medicine. Based on clinical presentations, Traditional Chinese Medicine (TCM) classifies healthy people into nine constitutions: Balanced, Qi, Yang or Yin deficiency, Phlegm-dampness, Damp-heat, Blood stasis, Qi stagnation, and Inherited special constitutions. In particular, Yang and Yin deficiency constitutions exhibit cold and heat aversion, respectively. However, the intrinsic molecular characteristics of unbal- anced phenotypes remain unclear. To determine whether gene expression-based clustering can reca- pitulate TCM-based classification, peripheral blood mononudear cells (PBMCs) were collected from Chinese Han individuals with Yang/Yin deficiency (n = 12 each) and Balanced (n = 8) constitutions, and global gene expression profiles were determined using the Affymetrix HC-UI33A Plus 2.0 array. Notably, we found that gene expression-based classifications reflected distinct TCM-based subtypes. Consistent with the clinical observation that subjects with Yang deficiency tend toward obesity, series-clustering analysis detected several key lipid metabolic genes (diacylglycerol acyltransferase (DGAT2), acyl-CoA synthetase (ACSL1), and ATP-hinding cassette subfamily A member 1 (ABCAI)) to be down- and up- regulated in Yin and Yang deficiency constitutions, respectively. Our findings suggest that Yin]Yang deficiency and Balanced constitutions are unique entities in their mRNA expression profiles. Moreover, the distinct physical and clinical characteristics of each unbalanced constitution can be explained, in part, by specific gene expression signatures.
基金This research was supported by the following, Par-Eu Scholars Program (20136666), The National Natural Science Foundation of China (31672363, 31372265), Co- ordinated Research Project of the International Atomic Energy Agency (18268/R1), National Key Program of Science and Technology Foundation Work of China (2015FY210300) and Chongqing graduate research innovation project (CYS14139). Conceived and designed the research: BC, YJE Performed the analysis: YJF, BC, ZTY. Wrote the paper: YJF, BC.
文摘Most of adult female mosquitoes secrete saliva to facilitate blood sucking, digestion and nutrition, and mosquito-borne disease prevention. The knowledge of classification and characteristics of sialotranscriptome genes are still quite limited, Anopheles sinensis is a major malaria vector in China and southeast Asian countries. In this study, the An. sinensis sialotranscriptome was sequenced using Illumina sequencing technique with a total of 10 907 unigenes to be obtained and annotated in biological functions and pathways, and 10 470 tmigenes were mapped to An. sinensis reference genome with 70.46% of genes having 90%- 100% genome mapping through bioinformatics analysis. These mapped genes were classified into four categories: housekeeping (6632 genes), secreted (1177), protein-coding genes with function-unknown (2646) and transposable element (15). The housekeeping genes were divided into 27 classes, and the secreted genes were divided into 11 classes and 96 families. The classification, characteristics and evolution of these classes/families of secreted genes are further described and discussed. The comparison of the 1177 secreted genes in An. sinensis in the Anophelinae subfamily with 811 in Psorophora albipes in the Culicinae subfamily show that six classes/subclasses have the gene number more than twice and two classes (uniquely found in anophelines, and Orphan proteins of unique standing) are unique in the former compared with the latter, whereas four classes/subclasses are much expanded and uniquely found in the Aedes class and is unique in the later. The An. sinensis sialotranscriptome sequence data is the most complete in mosquitoes to date, and the analyses provide a comprehensive information frame for further research of mosquito sialotranscriptome.