Recently, in situ protein microarrays have been developed for large scale analysis and high throughput studies of proteins. In situ protein microarrays produce proteins directly on the solid surface from pre-arrayed DNA or RNA. The advances in in situ protein microarrays are exemplified by the ease of cDNA cloning and cell free protein expression. These technologies can evaluate, validate and monitor protein in a cost effective manner and address the issue of a high quality protein supply to use in the array. Here we review the importance of recently employed methods: PISA (protein in situ array), DAPA (DNA array to protein array), NAPPA (nucleic acid programmable protein array) and TUSTER microarrays and the role of these methods in proteomics.
Cell-Free System ; DNA ; metabolism ; Oligonucleotide Array Sequence Analysis ; Protein Array Analysis ; Proteins ; metabolism ; RNA ; metabolism

No Abstract Available.
DNA* ; Oligonucleotide Array Sequence Analysis*

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.
Cluster Analysis ; DNA ; Oligonucleotide Array Sequence Analysis

No abstract available.
DNA* ; Genome* ; Genomics* ; Oligonucleotide Array Sequence Analysis*

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.
DNA ; Ecosystem ; Oligonucleotide Array Sequence Analysis

The identification of differential gene expression between gray and black hairs is an important study in modern hair pigment research. In this experiment, the authors have applied new methods by the integration of three updated molecular biological tools, T7 RNA polymerase-based RNA amplification, representational difference analysis (RDA), and microarray analysis, to screen the differentially expressed genes in gray and black hairs. The genes more abundantly expressed in black hairs were pigment related proteins, such as Pmel17, 95kD melanocyte-specific secreted glycoprotein, MART-1, tyrosinase, tyrosinase-related protein 1 etc. Also, expression of the selenium-binding protein (hSBP) gene and the spast gene for spastin protein were up-regulated in black hairs compared to those in gray hairs. In gray hairs, many kinds of genes related with keratin, trichohyalin and transmembrane glycoprotein were more expressed. In particular ch 17, hRPK.142_H_19 was expressed in gray hairs as high signal intensity.
DNA* ; Gene Expression* ; Glycoproteins ; Hair* ; Mass Screening* ; Microarray Analysis ; Monophenol Monooxygenase ; Oligonucleotide Array Sequence Analysis* ; RNA

AIMTo investigate the genetic polymorphism of several species of Fritillaria and to develop a DNA chip for the genotyping and identification of the origin of various species of Fritillaria at molecular level.

METHODSGenomic DNA from bulbs of several Fritillaria species was extracted and the polymorphisms of the D2 and D3 regions inside the 26S rDNA gene were identified by direct sequencing. Oligonucleotide probes specific for these polymorphisms were designed and printed on the poly-lysine coated slides to prepare the DNA chip. PCR products from the Fritillaria species were labeled with fluorescence by incorporation of dye-labeled dideoxyribonucleotides and hybridized to the immobilized probes on the chip.

RESULTSThe polymorphisms were used as markers for discrimination among various species. Specific oligonucleotide probes were designed and immobilized on a DNA chip. Differentiation of the various Fritillaria species was accomplished based on hybridization of fluorescent labeled PCR products with the DNA chip.

CONCLUSIONThe results demonstrated the reliability of using DNA chips to identify different species of Fritillaria, and the DNA chip technology can provide a rapid, high throughput tool for genotyping and quality assurance of the plant species verification.

Base Sequence ; DNA, Plant ; analysis ; Fritillaria ; classification ; genetics ; Genotype ; Molecular Sequence Data ; Oligonucleotide Array Sequence Analysis ; methods ; Plants, Medicinal ; genetics ; Polymorphism, Single Nucleotide ; RNA, Ribosomal ; genetics ; Species Specificity

BACKGROUNDKeloid is an intricate lesion that is probably regulated by many genes. In this study, the authors used the technique of complementary DNA (cDNA) microarray to analyse abnormal gene expression in keloids and normal control skins.

METHODSThe polymerase chain reaction (PCR) products of 8400 genes were spotted in an array on chemical-material-coated-glass plates. The DNAs were fixed on the glass plates. The total RNAs were isolated from freshly excised human keloid and normal control skins, and the mRNAs were then purified. The mRNA from both keloid and normal control skins were reversely transcribed to cDNAs, with the incorporation of fluorescent dUTP, for preparing the hybridisation probes. The mixed probes were then hybridised to the cDNA microarray. After thorough washing, the cDNA microarray was scanned for differing fluorescent signals from two types of tissues. Gene expression of tissue growth factor-beta1 (TGF-beta1) and of c-myc was detected with both RT-PCR and Northern blot hybridisation to confirm the effectiveness of cDNA microarray.

RESULTSAmong the 8400 human genes, 402 were detected with different expression levels between keloid and normal control skins. Two hundred and fifty genes, including TGF-beta1 and c-myc, were up-regulated and 152 genes were down-regulated. Higher expressions of TGF-beta1 and c-myc in keloid were also revealed using RT-PCR and Northern blot methods.

CONCLUSIONcDNA microarray analysis provides a powerful tool for investigating differential gene expression in keloid and normal control skins. Keloid is a complicated lesion with many genes involved.

DNA, Complementary ; analysis ; Humans ; Keloid ; genetics ; Oligonucleotide Array Sequence Analysis ; methods ; Polymerase Chain Reaction ; RNA, Messenger ; analysis ; Skin

OBJECTIVE: To investigate the mutation characteristics of common deafness gene from 127 non-syndromic hearing loss patients in Guangxi province. METHOD: Deafness-related gene mutations detection kit was used to detect 15 mutation sites in four deafness-associated genes, and a total of 127 hearing impaired patients were tested. The samples that could not be diagnosed with DNA microarray were subjected to PCR and sequenced to detect other mutations. RESULT Among the 127 patients with non-syndromic deafness, the total mutation rate is 8.66% (11/127), including GJB2 235delC homozygous in 3 cases (2.36%), 235delC single heterozygous mutation in 2 cases (1.57%), GJB2 235delC and 109 A > G mutations in 2 cases (1.57%); SLC26A4 1229C > T homozygous in 1 case (0.79%), IVS7-2A > G, IVS11 + 47T > C and 15448insC mutaion in 2 cases (1.57%); mitochondrial 12S rRNA gene mutations were not detected. The result indicates that GJB2 and SLC26A4 were the main genes in this study, and the mutation rate is significantly lower than the national average level. Three new mutations (SLC26A4 IVS11 + 47T > C,1548insC and GJB2 109A > G) were found. There may be rare mutations among sites or genes associated with deafness in Guangxi.
China ; Connexin 26 ; Connexins ; genetics ; DNA Mutational Analysis ; Deafness ; genetics ; Heterozygote ; Homozygote ; Humans ; Membrane Transport Proteins ; genetics ; Mutation ; Oligonucleotide Array Sequence Analysis ; Polymerase Chain Reaction ; RNA, Ribosomal ; genetics ; Sulfate Transporters

The analysis of DNA microarry data is one of the most important things for functional genomics research. The matrix representation of microarray data and its successive 'optimal' incisional hyperplanes is a useful platform for developing optimization algorithms to determine the optimal partitioning of pairwise proximity matrix representing completely connected and weighted graph. We developed Deterministic Annealing (DA) approach to determine the successive optimal binary partitioning. DA algorithm demonstrated good performance with the ability to find the 'globally optimal' binary partitions. In addition, the objects that have not been clustered at small non-zero temperature, are considered to be very sensitive to even small randomness, and can be used to estimate the reliability of the clustering.
Cluster Analysis ; DNA* ; Gene Expression* ; Genomics ; Oligonucleotide Array Sequence Analysis*