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Incorporating heuristic information into ant colony optimization for epistasis detection
Junliang Shang,Junying Zhang,Xiujuan Lei,Yuanyuan Zhang,Baodi Chen 한국유전학회 2012 Genes & Genomics Vol.34 No.3
Epistasis has been receiving increasing attention in understanding the mechanism underlying susceptibility to complex diseases. Though many works have been done for epistasis detection, genome-wide association study remains a challenging task: it makes the search space excessively huge while solution quality is excessively demanded. In this study, we introduce an ant colony optimization based algorithm,AntMiner, by incorporating heuristic information into ant-decision rules. The heuristic information is used to direct ants in the search process for improving computational efficiency and solution accuracy. During iterations, chi-squared test is conducted to measure the association between an interaction and the phenotype. At the completion of the iteration process, statistically significant epistatic interactions are ordered and then screened by a post-procedure. Experiments of AntMiner and its comparison with existing algorithms epiMODE, TEAM and AntEpiSeeker are performed on both simulation data sets and real age-related macular degeneration data set, under the criteria of detection power and sensitivity. Results demonstrate that AntMiner is promising for epistasis detection. In terms of detection power, AntMiner performs best among all the other algorithms on all cases regardless of epistasis models and single nucleotide polymorphism size; compared with AntEpiSeeker, AntMiner can obtain better detection power but with less ants and iterations. In terms of sensitivity, AntMiner is better than AntEpiSeeker in detecting epistasis models displaying marginal effects but it has moderate sensitivity on epistasis models displaying no marginal effects. The study may provide clues on heuristics for further epistasis detection. The software package is available online at https://sourceforge.net/projects/antminer/files/.
Junliang Shang,Junying Zhang,Xiujuan Lei,Wenying Zhao,Yafei Dong 한국유전학회 2013 Genes & Genomics Vol.35 No.3
Epistasis is a ubiquitous phenomenon in genetics,and is considered to be one of the main factors in current efforts to detect missing heritability for complex diseases. Simulation is a critical tool in developing methodologies that can more effectively detect and study epistasis. Here we present a simulator, epiSIM (epistasis SIMulator), that can simulate some of the statistical properties of genetic data. EpiSIM is capable of expanding the range of the epistasis models that current simulators offer, including epistasis models that display marginal effects and those that display no marginal effects. One or more of these epistasis models can be embedded simultaneously into a single simulation data set, jointly determining the phenotype. In addition,epiSIM is independent of any outside data source in generating linkage disequilibrium patterns and haplotype blocks. We demonstrate the wide applicability of epiSIM by performing several data simulations, and examine its properties by comparing it with current representative simulators and by comparing the data that it generates with real data. Our experiments demonstrate that epiSIM is a valuable addition and a nice complement to the existing epistasis simulators. The software package is available online at https://sourceforge.net/projects/episimsimulator/files/.
The location for eigenvalues of complex matrices by a numerical method
Junliang Wu,Pingping Zhang,Yong Wang 한국전산응용수학회 2011 Journal of applied mathematics & informatics Vol.29 No.1
In this paper, we adopt a numerical method to establish the smallest set to contain all Geršgorin discs of a given complex matrix and its some similar matrices. With the smallest set, a new estimation for all eigenvalues of the matrix is obtained.
Junliang Tao,Dongxian Zhang,Yonghong Man,Weina Wang,Yongyi Bi,Yongyi Bi 대한독성 유전단백체 학회 2016 Molecular & cellular toxicology Vol.12 No.2
Vascular inflammation is an important hallmark of high-fat-induced atherosclerosis. Oxidized low-density lipoprotein (ox-LDL) is a key initiator of inflammation as it induces inflammatory gene expression in vascular endothelial cells. Sodium ferulate (SF), an active component from Chinese medicine, demonstrated anti-atherosclerotic potency. However, the mechanism is unknown. Here we investigated how SF changed the cellular gene expression profile and restored ox-LDL-triggered inflammation in HUVECs. Gene expression profile, inflammatory gene expression and NF-κB activation were investigated in human umbilical vein endothelial cells (HUVECs) with or without SF (5 μM) treatment after precondition with ox-LDL (50 μg/mL). Ox-LDL treatment increased the production of IL-1β, CCL20, IL-6, IL-8 and CXCL1. SF stimulation modulated the translocation of NF-κB between cytoplasm and nucleus, and alleviated the inflammatory response induced by ox-LDL. Collectively, SF could suppress the expression of inflammatory factors in ox-LDL-stimulated endothelial cells, and transcription factor NF-κB might be involved in such process.
THE LOCATION FOR EIGENVALUES OF COMPLEX MATRICES BY A NUMERICAL METHOD
Wu, Junliang,Zhang, Pingping,Wang, Yong The Korean Society for Computational and Applied M 2011 Journal of applied mathematics & informatics Vol.29 No.1
In this paper, we adopt a numerical method to establish the smallest set to contain all Ger$\v{s}$gorin discs of a given complex matrix and its some similar matrices. With the smallest set, a new estimation for all eigenvalues of the matrix is obtained.
Kinetics studies of dimethyl carbonate synthesis from urea and methanol over ZnO catalyst
Wei Wei,Junliang Zhang,Feng Wang,Fukui Xiao,Yuhan Sun 한국화학공학회 2010 Korean Journal of Chemical Engineering Vol.27 No.6
A kinetic experiment of dimethyl carbonate (DMC) synthesis by urea methanol over ZnO catalyst was carried out in an isothermal fixed-bed reactor. A kinetic model based on the mole fraction was proposed and the kinetic parameters were estimated from the experimental results. The model predictions were compared with the experimental data and fair agreements were found. The effects of the reaction temperature (443-473 K), space time (0-4.7 h mol−1kgcat) and urea mass percent (5-9%) in feed on DMC mole fraction were investigated. It was found that the reactions are mainly influenced by the reaction temperature and space time rather than urea mass percent in feed. The experimental and simulated results indicated that the reaction from MC to DMC was the rate-controlling step in the DMC synthesis process from urea and methanol. It is important to remove the DMC and byproduct ammonia to achieve a high selectivity of DMC. This implies that reactive distillation might be used in the DMC synthesis on an industrial scale to achieve a higher selectivity of DMC.
Ultrafast epitaxial growth of metre-sized single-crystal graphene on industrial Cu foil
Xu, Xiaozhi,Zhang, Zhihong,Dong, Jichen,Yi, Ding,Niu, Jingjing,Wu, Muhong,Lin, Li,Yin, Rongkang,Li, Mingqiang,Zhou, Jingyuan,Wang, Shaoxin,Sun, Junliang,Duan, Xiaojie,Gao, Peng,Jiang, Ying,Wu, Xiaoson Elsevier 2017 Science bulletin Vol.62 No.15
Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques
Fu Chen,Zhang Bangxing,Guo Tiankang,Li Junliang 대한영상의학회 2024 Korean Journal of Radiology Vol.25 No.1
Early diagnosis, accurate assessment, and localization of peritoneal metastasis (PM) are essential for the selection of appropriate treatments and surgical guidance. However, available imaging modalities (computed tomography [CT], conventional magnetic resonance imaging [MRI], and 18fluorodeoxyglucose positron emission tomography [PET]/CT) have limitations. The advent of new imaging techniques and novel molecular imaging agents have revealed molecular processes in the tumor microenvironment as an application for the early diagnosis and assessment of PM as well as real-time guided surgical resection, which has changed clinical management. In contrast to clinical imaging, which is purely qualitative and subjective for interpreting macroscopic structures, radiomics and artificial intelligence (AI) capitalize on high-dimensional numerical data from images that may reflect tumor pathophysiology. A predictive model can be used to predict the occurrence, recurrence, and prognosis of PM, thereby avoiding unnecessary exploratory surgeries. This review summarizes the role and status of different imaging techniques, especially new imaging strategies such as spectral photon-counting CT, fibroblast activation protein inhibitor (FAPI) PET/CT, near-infrared fluorescence imaging, and PET/MRI, for early diagnosis, assessment of surgical indications, and recurrence monitoring in patients with PM. The clinical applications, limitations, and solutions for fluorescence imaging, radiomics, and AI are also discussed.
Junjing Li,Bo Li,Jiejing Li,Junliang Liu,Liang Wang,Hongwei Zhang,Zhaohui Zhang,Bin Zhao 한국공업화학회 2015 Journal of Industrial and Engineering Chemistry Vol.25 No.-
In this study, La, N codoped TiO2 (La–N–TiO2) nano-photocatalyst was fabricated through simple sol–gel method. The resulting samples were characterized through X-ray diffraction (XRD), scanning electrons microscope (SEM), transmission electrons microscope (TEM), X-ray photoelectron spectroscopy (XPS) and UV–visible light diffuse reflection spectroscopy (UV–vis DRS). Results revealed that La elements were not implanted into the structure of TiO2 but existed as the form of Ti–O–La bonds in the interstitial site, while N dopants were incorporated into the lattice of TiO2 and coexisted in the substitutional N (N– Ti–O) and interstitial N (Ti–O–N) in the La–N–TiO2 catalyst, thereby resulting in the formation of new impurity energy level between the forbidden band and greatly enhancement of light absorption ability in visible light region. The enhanced visible light driven (VLD) photocatalytic (PC) performance for the degradation of phenol aqueous solution could be attributed to the intense light absorbance in visible light region and high separation efficiency of photogenerated charge carriers.