Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems

An approach to dealing with missing data, both during the design and normal operation of a neuro-fuzzy classifier is presented in this paper. Missing values are processed within a general fuzzy min–max neural network architecture utilising hyperbox fuzzy sets as input data cluster prototypes. An emphasis is put on ways of quantifying the uncertainty which missing data might have caused. This takes a form of classification procedure whose primary objective is the reduction of a number of viable alternatives rather than attempting to produce one winning class without supporting evidence. If required, the ways of selecting the most probable class among the viable alternatives found during the primary classification step, which are based on utilising the data frequency information, are also proposed. The reliability of the classification and the completeness of information is communicated by producing upper and lower classification membership values similar in essence to plausibility and belief measures to be found in the theory of evidence or possibility and necessity values to be found in the fuzzy sets theory. Similarities and differences between the proposed method and various fuzzy, neuro-fuzzy and probabilistic algorithms are also discussed. A number of simulation results for well-known data sets are provided in order to illustrate the properties and performance of the proposed approach.     

Selective alterations of the antibody response to HIV-1

HIV infection leads to progressive alterations of humoral immune functions, including B-cell hyperplasia, hypergammaglobulinemia, elevated autoantibody titers, a poor response to neoantigens and mitogens, polyclonal B-cell activation, monoclonal gammopathies, and a significant deterioration of the antigen-specific humoral response. There is also an important isotypic imbalance of the antibody (Ab) response in the systemic compartment and a profound modification of mucosal immune functions. These abnormalities may contribute to disease progression and development of opportunistic infections, despite the presence of serum-neutralizing anti-HIV Abs. Equally important are the abnormal selection mechanisms of the Ab repertoire that seem to be responsible for B-cell clonal deletions. The V_H3 gene family, which encodes for approx 50% of immunoglobulins expressed by peripheral B-cells from normal adults, is underrepresented in human monoclonal antibodies to HIV-1 and in the peripheral B-cells of AIDS patients. These abnormalities, together with features of germinal center alteration, could be responsible for the clonal elimination of a subset of B-cells, and could contribute to HIV pathogenesis.     

Applications of maximum likelihood principal component analysis: incomplete data sets and calibration transfer

The application of a new method to the multivariate analysis of incomplete data sets is described. The new method, called maximum likelihood principal component analysis (MLPCA), is analogous to conventional principal component analysis (PCA), but incorporates measurement error variance information in the decomposition of multivariate data. Missing measurements can be handled in a reliable and simple manner by assigning large measurement uncertainties to them. The problem of missing data is pervasive in chemistry, and MLPCA is applied to three sets of experimental data to illustrate its utility. For exploratory data analysis, a data set from the analysis of archeological artifacts is used to show that the principal components extracted by MLPCA retain much of the original information even when a significant number of measurements are missing. Maximum likelihood projections of censored data can often preserve original clusters among the samples and can, through the propagation of error, indicate which samples are likely to be projected erroneously. To demonstrate its utility in modeling applications, MLPCA is also applied in the development of a model for chromatographic retention based on a data set which is only 80% complete. MLPCA can predict missing values and assign error estimates to these points. Finally, the problem of calibration transfer between instruments can be regarded as a missing data problem in which entire spectra are missing on the ‘slave’ instrument. Using NIR spectra obtained from two instruments, it is shown that spectra on the slave instrument can be predicted from a small subset of calibration transfer samples even if a different wavelength range is employed. Concentration prediction errors obtained by this approach were comparable to cross-validation errors obtained for the slave instrument when all spectra were available.     

Synthesis and Expression in Escherichia coli of a Human Neutrophil Activating Protein-1/Interleukin-8 Gene

The complete gene coding for human neutrophilactivating protein-1/interleukin-8 was synthesized using a semi-chemical semi-enzymatic method. The synthetic gene was then overexpressed in Escherichia coli under the temperature-regulated control of the P_RP_L tandem promoters. As determined by SDS-PAGE and densitometry, the overexpressed protein comprised up to 18.5% and 10.9% of the total soluble protein in E. coli cells grown in shake flasks and in batch fermentation, respectively. The recombinant NAP-1/IL-8 was then purified to>95% homogeneity by gel filtration and cation exchange chromatography. The purified protein appeared as a single band on the SDS-PAGE gel and possessed potent chemotactic activity in the concentration of <10 ng/ml, as assayed by the agarose plate method. An early skin reactivity was also observed when the pure NAP-1/IL-8 was injected subcutaneously into the rabbits. The N-terminal 36 amino acid sequence of the recombinant NAP1/IL-8 was determined using the Edman method and was sho     

先天性白内障一家系的致病基因研究

目的 对一个来自浙江省杭州地区的三代先天性白内障家系进行常染色体显性遗传基因的突变分析,以寻找其可能的致病基因及突变位点。方法 该家系共10例成员,其中包括4例患者。10 例家系成员在浙江省人民医院眼科中心接受眼科专科检查及全身检查,以排除存在白内障以外的眼部及全身疾患。10例家系成员各抽取外周血5ml,提取基因组DNA。针对国内外文献报道的与常染色体显性遗传先天性白内障相关的18 个基因（CRYAA、CRYAB、CRYBA1、CRYBA2、CRYBA4、CRYBB1、CRYBB2、CRYGC、CRYGD、CRYGS、GJA3、GJA8、MIP、BFSP、HSF4、PITX3、EPHA2、PAX6）设计引物,进行PCR 扩增,对扩产物进行测序和序列分析,了解这10例家系成员的以上基因是否存在相应的序列。结果 临床眼科检查显示该家系先天性白内障类型为粉尘状白内障。候选基因序列测定显示在CRYAA 第1 个外显子中第6 位碱基发生C→T 置换,氨基酸同为天门冬氨酸。该家系中所有患者均有此改变,而所有的正常家系成员均无此改变。结论 CRYAA 第1个外显子中第6位碱基发生C→T的同义突变可能是导致该家系先天性白内障发生的致病原因。     

Multivariate linear regression with missing values

This contribution presents and discusses an efficient algorithm for multivariate linear regression analysis of data sets with missing values. The algorithm is based on the insight that multivariate linear regression can be formulated as a set of individual univariate linear regressions. All available information is used and the calculations are explicit. The only restriction is that the independent variable matrix has to be non-singular. There is no need for imputation of interpolated or otherwise guessed values which require subsequent iterative refinement.     

4-Ketozeinoxanthin,a novel carotenoid produced in Escherichia coli through metabolic engineering using carotenogenic genes of bacterium and liverwort

In order to produce a novel keto-carotenoid in Escherichia coli, we introduced the marine bacterial carotenoid ketolase gene (crtW) into pathway-engineered E. coli producing carotenoids of plant origin, which carried the lycopene biosynthesis genes (crtE, crtB, and crtI) from soil bacterium Pantoea ananatis and the liverwort Marchantia polymorpha genes that encode lycopene β-cyclase (MpLCYb), lycopene ε-cyclase (MpLCYe), and β-carotenoid hydroxylase (MpBHY). A novel keto-carotenoid (1) was produced by these carotenoid biosynthesis genes in E. coli along with α-echinenone, adonirubin, and adonixanthin. The structure of 1 was determined as (3S,6′R)-3-hydroxy-β,ε-caroten-4-one based on Uv–vis, MS, ¹H NMR, and CD spectral data. This compound was named 4-ketozeinoxanthin and showed anti-tumor-promoting activity.     

低频液体表面波激光衍射条纹的特征

用激光衍射法实现了低频液体表面波稳定、清晰、反衬度非常高的条纹,并发现了缺级现象.理论上分析了表面波的光衍射效应,得到了衍射光场和表面波之间的解析表达式,表达式包括衍射因子和干涉因子.通过对衍射因子和干涉因子的分析,得到衍射条纹空间分布与表面波波长的关系、条纹的半角宽度与入射激光光斑覆盖表面波的个数和入射方向的关系、衍射光强度与表面波振幅的关系,并解释了条纹缺级现象.     

基于光栅衍射的晶体X射线衍射缺级的理论基础和实验研究

以光栅衍射缺级理论为切入点对晶体X射线衍射缺级的现象、产生的根源进行了理论分析,得出：(1) 晶体X射线衍射缺级存在的可能性在于某些晶体材料晶胞的几何结构因子为零;(2) 在复式格子晶体或具有某种特殊缺陷的晶体的X射线衍射图样中存在缺级是这方面实验研究的方向。这些结论在材料物相、材料结构类型和不完整性分析等方面具有一定的参考价值。     

Differentially expressed genes selection via Laplacian regularized low-rank representation method

With the rapid development of DNA microarray technology and next-generation technology, a large number of genomic data were generated. So how to extract more differentially expressed genes from genomic data has become a matter of urgency. Because Low-Rank Representation (LRR) has the high performance in studying low-dimensional subspace structures, it has attracted a chunk of attention in recent years. However, it does not take into consideration the intrinsic geometric structures in data.In this paper, a new method named Laplacian regularized Low-Rank Representation (LLRR) has been proposed and applied on genomic data, which introduces graph regularization into LRR. By taking full advantages of the graph regularization, LLRR method can capture the intrinsic non-linear geometric information among the data. The LLRR method can decomposes the observation matrix of genomic data into a low rank matrix and a sparse matrix through solving an optimization problem. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Therefore, the differentially expressed genes can be selected according to the sparse matrix. Finally, we use the GO tool to analyze the selected genes and compare the P-values with other methods.The results on the simulation data and two real genomic data illustrate that this method outperforms some other methods: in differentially expressed gene selection.