Methods for the assessment of human body composition: skinfold thickness and bioelectrical impedance measurements

Research to establish indirect methods of determining human body composition began during the 1940s. Renewed interest in the assessment of human body composition has stimulated the need for a balanced understanding of available methodologies of estimating fat-free mass and fat mass. Subsequently a variety of methods has been introduced. However, attempts to describe the theory and practice of individual methods have been limited. The review summarizes the background and to describe the precision or error of skinfold thickness measurement and to highlight the strengths and the limitations of bioelectrical impedance method.     

Statistical alignment of retropseudogenes and their functional paralogs

We describe a model for the sequence evolution of a processed pseudogene and its paralog from a common protein-coding ancestor. The model accounts for substitutions, insertions, and deletions and combines nucleotide- and codon-level mutation models. We give a dynamic programming method for calculating the likelihood of homology between two sequences in the model and describe the accompanying alignment algorithm. We also describe how ancestral codons can be computed when the same gene produced multiple pseudogene homologs. We apply our methods to the evolution of human cytochrome c.     

Purification of replication factors using insect and mammalian cell expression systems

Purification of factors for DNA replication in an amount sufficient for detailed biochemical characterization is essential to elucidating its mechanisms. Insect cell expression systems are commonly used for purification of the factors proven to be difficult to deal with in bacteria. We describe first the detailed protocols for purification of mammalian Mcm complexes including the Mcm2/3/4/5/6/7 heterohexamer expressed in insect cells. We then describe a convenient and economical system in which large-sized proteins and multi-factor complexes can be transiently overexpressed in human 293T cells and be rapidly purified in a large quantity. We describe various expression vectors and detailed methods for transfection and purification of various replication factors which have been difficult to obtain in a sufficient amount in other systems. Availability of efficient methods to overproduce and purify the proteins that have been challenging would facilitate the enzymatic analyses of the processes of DNA replication.     

Group sequential distribution-free methods for the analysis of multivariate observations.

Many studies involve the collection of multivariate observations, such as repeated measures, on two groups of subjects who are recruited over time, i.e., with staggered entry of subjects. Various marginal distribution-free multivariate methods have been proposed for the analyses of such multivariate observations where some measures may be missing at random. Using the multivariate U statistic of Wei and Johnson (1985, Biometrika 72, 359-364), we describe the group sequential analysis of such a study where the multivariate observations are observed sequentially--both within and among subjects. We describe a multivariate generalization of the Hodges and Lehmann (1963, Annals of Mathematical Statistics 34, 598-611) estimator of a location shift that can be obtained via the multivariate U statistic with the Mann-Whitney-Wilcoxon kernel. We then describe large-sample group sequential interval estimators and tests based on an aggregate estimate of the location shift combined over all of the repeated measures. We also describe how the same steps could be employed to perform a group sequential analysis based on any one of the variety of marginal multivariate methods that have been proposed. These methods are applied to a real-life example.     

Assigning significance to peptides identified by tandem mass spectrometry using decoy databases

Automated methods for assigning peptides to observed tandem mass spectra typically return a list of peptide-spectrum matches, ranked according to an arbitrary score. In this article, we describe methods for converting these arbitrary scores into more useful statistical significance measures. These methods employ a decoy sequence database as a model of the null hypothesis, and use false discovery rate (FDR) analysis to correct for multiple testing. We first describe a simple FDR inference method and then describe how estimating and taking into account the percentage of incorrectly identified spectra in the entire data set can lead to increased statistical power.     

Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-space models

A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a posteriori (MAP) path of the hidden state variable in these models, given spike train observations. If the state transition density is log-concave and the observation model satisfies certain standard assumptions, then the optimization problem is strictly concave and can be solved rapidly with Newton–Raphson methods, because the Hessian of the loglikelihood is block tridiagonal. We can further exploit this block-tridiagonal structure to develop efficient parameter estimation methods for these models. We describe applications of this approach to neural decoding problems, with a focus on the classic integrate-and-fire model as a key example.     

Systematic computational prediction of protein interaction networks

Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use.     

Protein function from the perspective of molecular interactions and genetic networks

Protein function is a complex notion, which is now receiving renewed attention from a bioinformatics and genomics perspective. After a general discussion of the principles of experimental methods employed to decipher gene/protein function, the contributions made by new, high-throughput methods in terms of function discovery are discussed. Recent work on functional ontologies and the necessity to describe function within the context of hierarchical levels of complexity are presented. The concepts of molecular interactions and genetic networks are then discussed, leading to a useful new framework with which to describe protein function using new tools such as 2D interaction maps. Finally, it is proposed that interaction data could be used to develop new methods for the functional classification of proteins. An example of functional comparisons on a real data set of yeast chromosomal proteins is presented.     

New syntax to describe local continuous structure-sequence information for recognizing new pre-miRNAs

As an important complement to experimental identification of pre-miRNA, computational prediction methods are attracting more and more attention. Features extracted from pre-miRNA are the key to computational prediction. Among the features, local continuous structure-sequence information is usually employed by existing computational methods. As more and more species-specific miRNAs have been identified, a new syntax is required to describe pre-miRNA local continuous structure-sequence features. Therefore, we proposed here the use of couplet syntax to describe pre-miRNA intrinsic features. When tested on a dataset from miRBase12.0 with the use of features extracted by couplet syntax, the SVM classifier achieves a sensitivity of 81.98% and specificity of 87.16% on a human test set and a sensitivity of 86.71% on all other species. The obtained results indicate that the proposed couplet syntax can describe the intrinsic features of pre-miRNA better than traditional methods. By means of describing pre-miRNA secondary structure more precisely and masking frequently mutated nucleotides, couplet syntax provides a powerful feature-describing method that can be applied to many computational prediction methods.     

Computation of writhe in modeling of supercoiled DNA

We describe four previously unpublished methods allowing the computation of the writhe for a supercoiled DNA molecule modeled by a polymer chain consisting of straight segments. These methods are compared with each other in terms of computational efficiency and the scope of their applicability is discussed.     

Gene discovery in neuropharmacological and behavioral studies using Affymetrix microarray data

We describe methods and software tools for doing data analysis based on Affymetrix microarray data, emphasizing often neglected issues. In our experience with neuroscience studies, experimental design and quality assessment are vital. We also describe in detail the pre-processing methods we have found useful for Affymetrix data. Finally, we summarize the statistical literature and describe some pitfalls in the post-processing analysis.     

Determining mutation rates in bacterial populations

When properly determined, spontaneous mutation rates are a more accurate and biologically meaningful reflection of underlying mutagenic mechanisms than are mutant frequencies. Because bacteria grow exponentially and mutations arise stochastically, methods to estimate mutation rates depend on theoretical models that describe the distribution of mutant numbers among parallel cultures, as in the original Luria-Delbr]uck fluctuation analysis. An accurate determination of mutation rate depends on understanding the strengths and limitations of these methods, and how to design fluctuation assays to optimize a given method. In this paper we describe a number of methods to estimate mutation rates, give brief accounts of their derivations, and discuss how they behave under various experimental conditions.     

Analysis of cell cycle phases and progression in cultured mammalian cells

Fluorescence activated cell sorting (FACS) analysis has become a standard tool to analyze cell cycle distributions in populations of cells. These methods require relatively large numbers of cells, and do not provide optimal resolution of the transitions between cell cycle phases. In this report we describe in detail complementary methods that utilize the incorporation of nucleotide analogs combined with microscopic examination. While often more time consuming, these protocols typically require far fewer cells, and allow accurate kinetic assessment of cell cycle progression. We also describe the use of a technique for the synchronization of adherent cells in mitosis by simple mechanical agitation (mitotic shake-off) that eliminates physiological perturbation associated with drug treatments.     

几种细胞凋亡检测方法的比较

近年来,凋亡细胞的检测方法从以形态学观察发展到生物化学、免疫化学和分子生物学等定性和定量测定技术,并在细胞、染色质到分子水平日趋完善和成熟。这些方法多用于描述DNA的片段化和细胞死亡过程中许多特定成分的检测。细胞凋亡具有其生物复杂性,检测方法要求灵敏度高、特异性强、准确性好、凋亡与坏死的区分明显等。由于每种方法各有优缺点,故应避免使用单一方法检测。     

Advancing analytical algorithms and pipelines for billions of microbial sequences

The vast number of microbial sequences resulting from sequencing efforts using new technologies require us to re-assess currently available analysis methodologies and tools. Here we describe trends in the development and distribution of software for analyzing microbial sequence data. We then focus on one widely used set of methods, dimensionality reduction techniques, which allow users to summarize and compare these vast datasets. We conclude by emphasizing the utility of formal software engineering methods for the development of computational biology tools, and the need for new algorithms for comparing microbial communities. Such large-scale comparisons will allow us to fulfill the dream of rapid integration and comparison of microbial sequence data sets, in a replicable analytical environment, in order to describe the microbial world we inhabit.     

Investigating the Endogenous Component of Human Circadian Rhythms: A Review of Some Simple Alternatives to Constant Routines

Several types of constant routine are accepted as an important means by which the endogenous component of circadian rhythms can be studied. Nevertheless, they are impracticable to perform and unsuitable for routine use in many individuals. We describe a group of simple methods with which rhythms measured in normal circumstances can be dissociated into the components due to masking and the internal clock. Each method is best suited to a particular type of experimental condition. Results from a variety of protocols are analysed by these and conventional methods to assess the validity of the new methods.     

Microfabrication of Bubbular Cavities in PDMS for Cell Sorting and Microcell Culture Applications

We describe a novel technique, low surface energy Gas Expansion Molding （GEM）, to fabricate microbubble arrays in polydimethylsiloxane （PDMS） which are incorporated into parallel plate flow chambers and tested in cell sorting and microcell cuTture applications. This architecture confers several operational advantages that distinguish this technology approach from currently used methods. Herein we describe the GEM process and the parameters that are used to control microbubble formation and a Vacuum-Assisted Coating （VAC） process developed to selectively and spatially alter the PDMS surface chemistry in the wells and on the microchannel surface. We describe results from microflow image visualization studies conducted to investigate fluid streams above and within microbubble wells and conclude with a discussion of cell culture studies in PDMS.     

Enzymatic assays for NAD-dependent deacetylase activities

The NAD-dependent deacetylases are a new class of enzymes responsible for the removal of acetyl groups from lysines on proteins. Instead of water, the NAD-dependent deacetylases use a highly reactive ADP-ribose intermediate as a recipient for the acetyl group. The products of the reaction are nicotinamide, acetyl-ADP-ribose, and a deacetylated substrate. Many assays have been developed for the measurement of NAD-dependent deacetylase activity. In this review we present assays based on each of the two reactions catalyzed by these enzymes, deacetylation and NAD hydrolysis. First we describe methods for the production of acetylated protein and peptide substrates for use in deacetylation reactions. Then we describe four methods for assaying deacetylation, three of which directly measure the loss of acetyl groups from a protein or peptide substrate, and one that measures acetate production. We also describe two indirect methods for following enzyme activity, NAD hydrolysis and a novel NAD-nicotinamide exchange reaction. Finally, a quantitative method using a monoacetylated peptide as a substrate and HPLC to measure products is described.