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71.
Ulrich Stelzl 《Proteomics. Clinical applications》2013,7(11-12):727-732
Protein–protein interaction networks are typically generated in standard cell lines or model organisms as it is prohibitively difficult to record large interaction datasets from specific tissues or disease models at a reasonable pace. Although the interaction data are of high confidence, they thus do not reflect in vivo relationships as such. A wealth of physiologically relevant protein information, obtained under different conditions and from different systems, is available including information on genetic variation, protein levels, and PTMs. However, these data are difficult to assess comprehensively because the relationships between the entities remain elusive from the measurements. Here, we exemplarily highlight recent studies that gained deeper insight from genetic variation, protein, and PTM measurements using interaction information pointing toward the importance and potential of interaction networks for the interpretation of sequencing and proteomics data. 相似文献
72.
73.
基因表达数据的出现,为人类从分子生物学的角度研究和探索癌症的发病机理提供了广阔的前景,利用基因表达数据发现与癌症相关的基因对于癌症的诊断和治疗具有重要的意义。在过去的十几年里,已经有很多种计算方法被成功地用于从基因表达数据中找出与癌症相关的关键基因,然而,不同的方法从不同的角度刻画基因对不同类型样本的区分能力,它们选择出来的关键基因可能不一致,这将给医学解释和应用带来困扰。现提出一种融合的方法,即将基因在不同方面对样本的判别能力结合起来,首先计算每个基因的信息增益、全局判别能力和局部判别能力,再用它们的识别率进行加权,进而计算每个基因的综合判别能力,最后筛选出判别能力最高的基因子集作为关键基因子集。实验结果表明,此方法得到了比采用单独一种评价标准更好的识别效果。 相似文献
74.
基于相容关系的基因选择方法 总被引:1,自引:0,他引:1
有效的基因选择是对基因表达数据进行分析的重要内容。粗糙集作为一种软计算方法能够保持在数据集分类能力不变的基础上,对属性进行约简。由于基因表达数据的连续性,为了避免运用粗糙集方法所必需的离散化过程带来的信息丢失,将相容粗糙集应用于基因的特征选取,提出了基于相容关系的基因选择方法。首先,通过i检验对基因表达数据进行排列,选择评分靠前的若干基因;然后,通过相容粗糙集对这些基因进一步约简。在两个标准的基因表达数据上进行了实验,结果表明该方法是可行性和有效性的。 相似文献
75.
76.
Mohd Saberi Mohamad Sigeru Omatu Safaai Deris Muhammad Faiz Misman Michifumi Yoshioka 《Artificial Life and Robotics》2009,13(2):410-413
A microarray machine offers the capacity to measure the expression levels of thousands of genes simultaneously. It is used
to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer
classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes
relative to the small number of available samples, and the fact that many of the genes are not relevant to the classification.
It has been shown that selecting a small subset of genes can lead to improved accuracy in the classification. Hence, this
paper proposes a solution to the problems by using a multiobjective strategy in a genetic algorithm. This approach was tried
on two benchmark gene expression data sets. It obtained encouraging results on those data sets as compared with an approach
that used a single-objective strategy in a genetic algorithm.
This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January
31–February 2, 2008 相似文献
77.
Mohd Saberi Mohamad Sigeru Omatu Safaai Deris Muhammad Faiz Misman Michifumi Yoshioka 《Artificial Life and Robotics》2009,13(2):414-417
Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes
simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient
cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the
number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small
subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset
of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods
has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results.
This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January
31–February 2, 2008 相似文献
78.
The assembly of viral proteins into a range of macromolecular complexes of strictly defined architecture is one of Nature's wonders. Unraveling the details of these complex structures and the associated self-assembly pathways that lead to their efficient and precise construction will play an important role in the development of anti-viral therapeutics. It will also be important in bio-nanotechnology where there is a plethora of applications for such well-defined macromolecular complexes, including cell-specific drug delivery and as substrates for the formation of novel materials with unique electrical and magnetic properties. Mass spectrometry has the ability not only to measure masses accurately but also to provide vital details regarding the composition and stoichiometry of intact, non-covalently bound macromolecular complexes under near-physiological conditions. It is thus ideal for exploring the assembly and function of viruses. Over the past decade or so, significant advances have been made in this field, and these advances are summarized in this review, which covers the literature up to the end of 2007. 相似文献
79.
Xu Cai Yu Xiao Bingwen Zhang Yanhui Yang Jun Wang Huamin Chen Guozhen Shen 《Advanced functional materials》2023,33(43):2304456
MXene materials emerge as promising candidates for energy harvesting and storage application. In this study, the effect of the surface chemistry on the work function of MXenes, which determines the performance of MXene-based triboelectric nanogenerator (TENG), is elucidated. First-principles calculations reveal that the surface functional group greatly influences MXene work function: OH termination reduces the work function with respect to that of bare surface, while F and Cl increase it. Then, work functions are experimentally determined by Kelvin probe force microscopy. The MXene prepared by gentle etching at 40 °C for 48 h (GE40/48) has the largest work function. Furthermore, an electron-cloud potential-well model is established to explain the mechanism of electron emission-dominated charge transfer and assemble a triboelectric device to verify experimentally its conclusions. It is found that GE40/48 has the best performance with a 281 V open-circuit voltage, 9.7 µA short-current current, and storing 1.019 µC of charge, which is consistent with the model. Last, a patterned TENG is demonstrated for self-powered human–machine interaction application. This finding enhances the understanding of the inherent mechanism between the surface structure and the output performance of MXene-based TENG, which can be applied to other TENG based on 2D materials. 相似文献
80.
David B. Ahn Won-Yeong Kim Kwon-Hyung Lee Seong-Sun Lee Seung-Hyeok Kim Sodam Park Young-Kuk Hong Sang-Young Lee 《Advanced functional materials》2023,33(18):2211597
Conventional power sources encounter difficulties in achieving structural unitization with complex-shaped electronic devices because of their fixed form factors. Here, it is realized that an on-demand conformal Zn-ion battery (ZIB) on non-developable surfaces uses direct ink writing (DIW)-based nonplanar 3D printing. First, ZIB component (manganese oxide-based cathode, Zn powder-based anode, and UV-curable gel composite electrolyte) inks are designed to regulate their colloidal interactions to fulfill the rheological requirements of nonplanar 3D printing, and establish bi-percolating ion/electron conduction pathways, thereby enabling geometrical synchronization with non-developable surfaces, and ensuring reliable electrochemical performance. The ZIB component inks are conformally printed on arbitrary curvilinear substrates to produce embodied ZIBs that can be seamlessly integrated with complicated 3D objects (including human ears). The conformal ZIB exhibits a high fill factor (i.e., areal coverage of cells on underlying substrates, ≈100%) that ensures high volumetric energy density (50.5 mWh cmcell−3), which exceeds those of previously-reported shape-adaptable power sources. 相似文献