ISHAN: sequence homology analysis package

Sequence based homology studies play an important role in evolutionary tracing and classification of proteins. Various methods are available to analyze biological sequence information. However, with the advent of proteomics era, there is a growing demand for analysis of huge amount of biological sequence information, and it has become necessary to have programs that would provide speedy analysis. ISHAN has been developed as a homology analysis package, built on various sequence analysis tools viz FASTA, ALIGN, CLUSTALW, PHYLIP and CODONW (for DNA sequences). This JAVA application offers the user choice of analysis tools. For testing, ISHAN was applied to perform phylogenetic analysis for sets of Caspase 3 DNA sequences and NF-kappaB p105 amino acid sequences. By integrating several tools it has made analysis much faster and reduced manual intervention.     

Ontological analysis of gene expression data: current tools, limitations, and open problems

Independent of the platform and the analysis methods used, the result of a microarray experiment is, in most cases, a list of differentially expressed genes. An automatic ontological analysis approach has been recently proposed to help with the biological interpretation of such results. Currently, this approach is the de facto standard for the secondary analysis of high throughput experiments and a large number of tools have been developed for this purpose. We present a detailed comparison of 14 such tools using the following criteria: scope of the analysis, visualization capabilities, statistical model(s) used, correction for multiple comparisons, reference microarrays available, installation issues and sources of annotation data. This detailed analysis of the capabilities of these tools will help researchers choose the most appropriate tool for a given type of analysis. More importantly, in spite of the fact that this type of analysis has been generally adopted, this approach has several important intrinsic drawbacks. These drawbacks are associated with all tools discussed and represent conceptual limitations of the current state-of-the-art in ontological analysis. We propose these as challenges for the next generation of secondary data analysis tools.     

Real-time DNA quantification of nuclear and mitochondrial DNA in forensic analysis

The rapid development of molecular genetic analysis tools has made it possible to analyze most biological materialfound at the scene of a crime. Evidence materials containing DNA quantities too low to be analyzed using nuclear markers can be analyzed using the highly abundant mtDNA. However, there is a shortage of sensitive nDNA and mtDNA quantification assays. In this study, an assay for the quantification of very small amounts of DNA, based on the real-time Taq-Man assay, has been developed. This analysis will provide an estimate of the total number of nDNA copies and the total number of mtDNA molecules in a particular evidence material. The quantification is easy to perform, fast, and requires a minimum of the valuable DNA extracted from the evidence materiaL The results will aid in the evaluation of whether the specific sample is suitable for nDNA or mtDNA analysis. Furthermore, the optimal amount of DNA to be used in further analysis can be estimated ensuring that the analysis is successful and that the DNA is retained for future independent analysis. This assay has significant advantages over existing techniques because of its high sensitivity, accuracy, and the combined analysis of nDNA and mtDNA. Moreover, it has the potential to provide additional information about the presence of inhibitors in forensic samples. Subsequent mitochondrial and nuclear analysis of quantified samples illustrated the potential to predict the number of DNA copies required for a successful analysis in a certain typing assay.     

Missing Plot Technique in Diallel Crosses for Griffing Method-III

The method of combining ability analysis of diallel crosses for Griffing method-3 for one and two missing observations has been presented. The formulae for estimating the parameters, the variances of different estimates and the sum of squares for various effects have been presented. The given analysis can easily be extended for the case of missing of more than two observations. The procedure of analysis has been illustrated through an example.     

High content cellular screening

Over the past few years, high content screening has firmly established itself as a high-throughput technology for the analysis of microscopy-based cellular assays. In particular, it has opened new areas of cell biology for the large-scale analysis of cellular phenotypes and has enabled the application of increasingly sophisticated assays for large-scale genetic and compound screening, benefiting both the academic and pharmaceutical research environment.     

Recent advances in mass spectrometry analysis of histone post-translational modifications: potential clinical impact of the PAT-H-MS approach

Histone post-translational modifications (hPTMs) contribute to the regulation of gene expression and increasing evidence links them to the development of various pathologies, highlighting their potential as biomarkers for prognostic, diagnostic and therapeutic applications. Mass spectrometry (MS) has emerged as a powerful analytical tool for hPTM analysis, which has also been applied to the analysis of epigenetic aberrations in diseases. However, the potential offered by the MS-based hPTM analysis of clinical samples for epigenetic biomarker discovery has been left largely unexploited. This article summarizes the contribution of MS-based approaches to clinical epigenetics, with a special focus on the PAThology tissue analysis of Histones by Mass Spectrometry (PAT-H-MS) approach – which represents the first application of MS-based hPTM analysis to formalin-fixed paraffin-embedded clinical samples – discussing its strengths and limitations, as well as possible implementations.     

The Drosophila genome

The past year has been a spectacular one for Drosophila research. The sequencing and annotation of the Drosophila melanogaster genome has allowed a comprehensive analysis of the first three eukaryotes to be sequenced-yeast, worm and fly-including an analysis of the fly's influences as a model for the study of human disease. This year has also seen the initiation of a full-length cDNA sequencing project and the first analysis of Drosophila development using high-density DNA microarrays containing several thousand Drosophila genes. For the first time homologous recombination has been demonstrated in flies and targeted gene disruptions may not be far off.     

Design of proteome-based studies in combination with serology for the identification of biomarkers and novel targets

Recently proteome analysis has rapidly developed in the post-genome era and is now widely accepted as a complementary technology to genetic profiling. The improvement in the technology of both two-dimensional electrophoresis (2-DE) analysis as well as protein identification has made proteomics a valuable and powerful tool to study human diseases. A combination of conventional proteome analysis with serology has been developed as a promising experimental approach for the discovery of serological markers in different malignancies. However, the design of proteome-based studies has to be carefully performed since there are a number of critical needs for systematic and reproducible proteome analysis. In particular, the selection of tissue and its preparation represent an important step in proteome analysis. Besides the preparation of protein samples, the 2-DE and protein identification is a further critical issue. So far proteome-based technologies have been successfully used in tumor immunnology for the identification of tumor-specific autoantigens. Similarly, this technology has been employed for the detection of virulence factors, antigens and vaccine candidates in infectious diseases, as well as for the identification of diagnostic and prognostic markers, suggesting that proteome-based analysis is a promising tool for the identification of prognostic, diagnostic markers as well as for novel therapeutic targets which could be used for treatment of diseases. The integration of proteome-based approaches with data from genomic or genetic profiling will lead to a better understanding of different diseases, which will then contribute to the direct translation of the research findings into clinical practice.     

Tackling an essential problem in functional proteomics of <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>

Gene inactivation is the cornerstone of functional genetic analysis, but the analysis of essential genes requires conditional inactivation of the gene product. A new study has adapted a simple method for creating conditional alleles to allow large-scale analysis of essential genes in Saccharomyces cerevisiae and has identified a role in DNA replication for a newly identified protein complex.     

Approaches for extracting practical information from gene co-expression networks in plant biology

Gene co-expression, in many cases, implies the presence of a functional linkage between genes. Co-expression analysis has uncovered gene regulatory mechanisms in model organisms such as Escherichia coli and yeast. Recently, accumulation of Arabidopsis microarray data has facilitated a genome-wide inspection of gene co-expression profiles in this model plant. An approach using network analysis has provided an intuitive way to represent complex co-expression patterns between many genes. Co-expression network analysis has enabled us to extract modules, or groups of tightly co-expressed genes, associated with biological processes. Furthermore, integrated analysis of gene expression and metabolite accumulation has allowed us to hypothesize the functions of genes associated with specific metabolic processes. Co-expression network analysis is a powerful approach for data-driven hypothesis construction and gene prioritization, and provides novel insights into the system-level understanding of plant cellular processes.     

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

Background  

The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes.     

Anion activation of dopamine beta-hydroxylase: a kinetic model

1. A theoretical analysis has been made of the mechanism of anion activation of dopamine beta-hydroxylase on the basis of accumulated experimental data. A model is presented that accounts for the numerous different effects of activating anions on the enzyme kinetics. This model has a general validity, since it holds for any of the kinetic mechanisms thus far proposed for dopamine beta-hydroxylase. 2. It has been shown that the results of this analysis have direct implications for the experimental conditions to be used in the study of the dopamine beta-hydroxylase reaction. 3. The present analysis has proved that, under appropriate assumptions, theoretical treatment of nonessential activation, so far limited to the single-substrate case, can be easily extended to steady-state multireactant enzymes.     

Protein interaction network analysis—Approach for potential drug target identification in Mycobacterium tuberculosis

In host-parasite diseases like tuberculosis, non-homologous proteins (enzymes) as drug target are first preference. Most potent drug target can be identified among large number of non-homologous protein through protein interaction network analysis. In this study, the entire promising dimension has been explored for identification of potential drug target. A comparative metabolic pathway analysis of the host Homo sapiens and the pathogen M. tuberculosis H37Rv has been performed with three level of analysis. In first level, the unique metabolic pathways of M. tuberculosis have been identified through its comparative study with H. sapiens and identification of non-homologous proteins has been done through BLAST similarity search. In second level, choke-point analysis has been performed with identified non-homologous proteins of metabolic pathways. In third level, two type of analysis have been performed through protein interaction network. First analysis has been done to find out the most potential metabolic functional associations among all identified choke point proteins whereas second analysis has been performed to find out the functional association of high metabolic interacting proteins to pathogenesis causing proteins. Most interactive metabolic proteins which have highest number of functional association with pathogenesis causing proteins have been considered as potential drug target. A list of 18 potential drug targets has been proposed which are various stages of progress at the TBSGC and proposed drug targets are also studied for other pathogenic strains.As a case study, we have built a homology model of identified drug targets histidinol-phosphate aminotransferase (HisC1) using MODELLER software and various information have been generated through molecular dynamics which will be useful in wetlab structure determination. The generated model could be further explored for insilico docking studies with suitable inhibitors.     

山珍补益膏的营养研究

山珍补益膏含有较高含量的各种必需氨基酸、微量元素和维生素。     

Translational applications of flow cytometry in clinical practice

Flow cytometry has evolved over the past 30 y from a niche laboratory technique to a routine tool used by clinical pathologists and immunologists for diagnosis and monitoring of patients with cancer and immune deficiencies. Identification of novel patterns of expressed Ags has led to the recognition of cancers with unique pathophysiologies and treatment strategies. FACS had permitted the isolation of tumor-free populations of hematopoietic stem cells for cancer patients undergoing stem cell transplantation. Adaptation of flow cytometry to the analysis of multiplex arrays of fluorescent beads that selectively capture proteins and specific DNA sequences has produced highly sensitive and rapid methods for high through-put analysis of cytokines, Abs, and HLA genotypes. Automated data analysis has contributed to the development of a "cytomics" field that integrates cellular physiology, genomics, and proteomics. In this article, we review the impact of the flow cytometer in these areas of medical practice.     

Analysis of ligand-receptor binding by the difference method

A new method has been proposed for analysis of experimental data on ligand-receptor binding at equilibrium. This method makes it possible to detect heterogeneity of a receptor system in cases where the contribution of the high-affinity site to total binding is rather small and the problem of graphic discrimination of a model cannot be solved unambiguously by other methods. The difference method permits us to exclude experiments on measuring nonspecific binding. A computer program for analysis of ligand-receptor binding has been worked out in which the difference method and traditional methods of binding isotherm analysis are realized. Numerical modeling has shown that the best strategy in experimental data processing is the treatment of total binding isotherms by both the difference method and regression analysis, including the nonspecific binding constant as one of the regression parameters.