Orthologous gene-expression profiling in multi-species models: search for candidate genes

Microarray-driven gene-expression profiles are generally produced and analyzed for a single specific experimental model. We have assessed an analytical approach that simultaneously evaluates multi-species experimental models within a particular biological condition using orthologous genes as linkers for the various Affymetrix microarray platforms on multi-species models of ventilator-associated lung injury. The results suggest that this approach may be a useful tool in the evaluation of biological processes of interest and selection of process-related candidate genes.     

Membrane stability

Rupture and buckling of artificial and biological membranes is an important part of many biological processes. In this review, we present some of the main experimental facts and their analysis. Recent theoretical work, in particular thin film models and nucleation mechanisms of membrane instability, are discussed in detail. Possible applications to membrane adhesion and fusion are pointed out. Attempts are made to explain biological phenomena and experimental results for biological membranes based on a rigorous physicochemical approach developed previously for thin films in colloid systems.     

Evaluation of accuracy and applicability of protein models: retrospective analysis of biological and biomedical predictions

In order to study protein function and activity structural data is required. Since experimental structures are available for just a small fraction of all known protein sequences, computational methods such as protein modelling can provide useful information. Over the last few decades we have predicted, with homology modelling methods, the structures for numerous proteins. In this study we assess the structural quality and validity of the biological and medical interpretations and predictions made based on the models. All the models had correct scaffolding and were ranked at least as correct or good by numerical evaluators even though the sequence identity with the template was as low as 8%. The biological explanations made based on models were well in line with experimental structures and other experimental studies. Retrospective analysis of homology models indicates the power of protein modelling when made carefully from sequence alignment to model building and refinement. Modelling can be applied to studying and predicting different kinds of biological phenomena and according to our results it can be done so with success.     

Comparative actions of barbiturates studied by pollen gran germination

A simple experimental system is described whereby the comparative actions of long-, medium-, and short-acting barbiturates can be demonstrated in a relatively short period of time under optical microscopy using pollen grains as the biological test or assay system. This experimental system yields results which are both readily obtainable and consistently reproducible. In addition, the Meyer—Overton principle regarding lipid solubility in relation to drug or anaesthetic potency in animals and in humans is demonstrable in this experimental system which employs a haploid microscopic plant material.     

Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.     

Qualitative modeling of normal blood coagulation and its pathological states using stochastic activity networks

We have developed a method for representing biological pathways and simulating their behavior based on the use of stochastic activity networks (SANs). SANs, an extension of the original Petri net, have been used traditionally to model flow systems including data-communications networks and manufacturing processes. We apply the methodology to the blood coagulation cascade, a biological flow system, and present the representation method as well as results of simulation studies based on published experimental data. In addition to describing the dynamic model, we also present the results of its utilization to perform simulations of clinical states including hemophilia's A and B as well as sensitivity analysis of individual factors and their impact on thrombin production.     

Biosystematic status of three allopatric populations ofAphytis maculicornis [Hym.: Aphelinidae]

Biological differences among 3 morphologically identical populations ofAphytis which would key down toA. maculicornis (Masi) are presented through studies conducted on their reproductive isolation, host preferences and adult suvivorships at different temperatures. These results supplement results on experimental hydridization and provide ample evidence that from a practical biological control stand-point as well as from basic biosystematics, these 3 populations are valid species, distinct from each other. The significance of such sibling species in relation to biological control is discussed.     

生物组织散射元平均间距估计的一种新方法

生物组织散射元平均间中划描述生物组织微观结构特性和生物组织超微散射特性的重要参数。本文在对生物组织超声背向散射随机模的基础上,提出了基于生物组织超声背向散射信号突变点检测的工用射元平均间距估计的新方法。该方法是生物组织超声散射分析的有效方法。     

A DIRECT-SPRAY TECHNIQUE FOR THE BIOLOGICAL EVALUATION OF PYRETHRUM-IN-OIL INSECTICIDES FOR USE AGAINST STORED PRODUCT INSECTS IN WAREHOUSES

A direct-spray technique for the biological assay of pyrethrins in Shell oil P31 is described, together with the experiments leading to its adoption. The technique is such that film effects are reduced to the minimum practicable, but it is otherwise as similar as possible to the film technique described by Parkin & Green (1943). Methods for statistical analysis of the results are discussed. For the biological assay of pyrethrins in Shell oil P31, the direct-spray method is slightly superior to Parkin & Green's film method, but both techniques should have their uses in general experimental work.     

Studies of folding and misfolding using simplified models

Computer simulations are as vital to our studies of biological systems as experiments. They bridge and rationalize experimental observations, extend the experimental "field of view", which is often limited to a specific time or length scale, and, most importantly, provide novel insights into biological systems, offering hypotheses about yet-to-be uncovered phenomena. These hypotheses spur further experimental discoveries. Simplified molecular models have a special place in the field of computational biology. Branded as less accurate than all-atom protein models, they have offered what all-atom molecular dynamics simulations could not--the resolution of the length and time scales of biological phenomena. Not only have simplified models proven to be accurate in explaining or reproducing several biological phenomena, they have also offered a novel multiscale computational strategy for accessing a broad range of time and length scales upon integration with traditional all-atom simulations. Recent computer simulations of simplified models have shaken or advanced the established understanding of biological phenomena. It was demonstrated that simplified models can be as accurate as traditional molecular dynamics approaches in identifying native conformations of proteins. Their application to protein structure prediction yielded phenomenal accuracy in recapitulating native protein conformations. New studies that utilize the synergy of simplified protein models with all-atom models and experiments yielded novel insights into complex biological processes, such as protein folding, aggregation and the formation of large protein complexes.     

Conformational stability and folding mechanisms of dimeric proteins

The folding of multisubunit proteins is of tremendous biological significance since the large majority of proteins exist as protein-protein complexes. Extensive experimental and computational studies have provided fundamental insights into the principles of folding of small monomeric proteins. Recently, important advances have been made in extending folding studies to multisubunit proteins, in particular homodimeric proteins. This review summarizes the equilibrium and kinetic theory and models underlying the quantitative analysis of dimeric protein folding using chemical denaturation, as well as the experimental results that have been obtained. Although various principles identified for monomer folding also apply to the folding of dimeric proteins, the effects of subunit association can manifest in complex ways, and are frequently overlooked. Changes in molecularity typically give rise to very different overall folding behaviour than is observed for monomeric proteins. The results obtained for dimers have provided key insights pertinent to understanding biological assembly and regulation of multisubunit proteins. These advances have set the stage for future advances in folding involving protein-protein interactions for natural multisubunit proteins and unnatural assemblies involved in disease.     

BIOREL: the benchmark resource to estimate the relevance of the gene networks

The progress of high-throughput methodologies in functional genomics has lead to the development of statistical procedures to infer gene networks from various types of high-throughput data. However, due to the lack of common standards, the biological significance of the results of the different studies is hard to compare. To overcome this problem we propose a benchmark procedure and have developed a web resource (BIOREL), which is useful for estimating the biological relevance of any genetic network by integrating different sources of biological information. The associations of each gene from the network are classified as biologically relevant or not. The proportion of genes in the network classified as "relevant" is used as the overall network relevance score. Employing synthetic data we demonstrated that such a score ranks the networks fairly in respect to the relevance level. Using BIOREL as the benchmark resource we compared the quality of experimental and theoretically predicted protein interaction data.     

Chemically-induced aneuploidy in mammalian oocytes

The ability of certain chemicals to elevate the frequency of aneuploidy above spontaneous levels in mammalian experimental models prompts the concern that a similar situation might exist in humans. Validation of experimental models for aneuploidy studies is in progress since there is much to be learned about the causes and mechanisms of chemically-induced aneuploidy. Several biological variables have been shown to influence the results from aneuploidy assays. In this review, we examine these variables as they relate to female germ cell aneuploid assays. Also, we have found that the aneuploidy results obtained from different cell types, sexes, and experimental models cannot necessarily be expected to agree due to certain anatomic and physiologic differences and the end points measured.     

亚毫米波激光对生物活体作用机理的讨论

本文应用H.Froehlich生物玻色（Bose）凝聚理论,讨论微弱的亚毫米波激光辐射对生物活体作用的机理,并介绍相关的实验结果。     

Gene Function Hypotheses for the Campylobacter jejuni Glycome Generated by a Logic-Based Approach

Increasingly, experimental data on biological systems are obtained from several sources and computational approaches are required to integrate this information and derive models for the function of the system. Here, we demonstrate the power of a logic-based machine learning approach to propose hypotheses for gene function integrating information from two diverse experimental approaches. Specifically, we use inductive logic programming that automatically proposes hypotheses explaining the empirical data with respect to logically encoded background knowledge. We study the capsular polysaccharide biosynthetic pathway of the major human gastrointestinal pathogen Campylobacter jejuni. We consider several key steps in the formation of capsular polysaccharide consisting of 15 genes of which 8 have assigned function, and we explore the extent to which functions can be hypothesised for the remaining 7. Two sources of experimental data provide the information for learning—the results of knockout experiments on the genes involved in capsule formation and the absence/presence of capsule genes in a multitude of strains of different serotypes. The machine learning uses the pathway structure as background knowledge. We propose assignments of specific genes to five previously unassigned reaction steps. For four of these steps, there was an unambiguous optimal assignment of gene to reaction, and to the fifth, there were three candidate genes. Several of these assignments were consistent with additional experimental results. We therefore show that the logic-based methodology provides a robust strategy to integrate results from different experimental approaches and propose hypotheses for the behaviour of a biological system.     

Mechanisms of the regulation of the biological activity of the cell by 2',5-oligoadenylate

The problems of regulation of biological activity of the cell, in particular, of such complicated processes as cell growth, differentiation, etc., rank highest among the most burning problems of present-day biology. A great majority of regulatory systems have been discovered, which control the biological activity of the cell. Among those, a most multifunctional and thoroughly investigated one is the cAMP system. The mechanisms of cAMP-dependent regulation, cAMP-dependent enzymes and other aspects of the system function have become the subject of numerous experimental papers, reviews and monographs. Another regulatory system which presently attracts the wide attention of investigators is the 2',5'-oligoadenylate system. The aim of the present review is to summarize the current data on the action mechanism and biological significance of 2',5'-oligoadenylate. Besides, the authors analyze some experimental results concerning the mechanisms of interaction and mutual regulation of the two above-mentioned systems.     

SWISS MADE: Standardized WithIn Class Sum of Squares to Evaluate Methodologies and Dataset Elements

Contemporary high dimensional biological assays, such as mRNA expression microarrays, regularly involve multiple data processing steps, such as experimental processing, computational processing, sample selection, or feature selection (i.e. gene selection), prior to deriving any biological conclusions. These steps can dramatically change the interpretation of an experiment. Evaluation of processing steps has received limited attention in the literature. It is not straightforward to evaluate different processing methods and investigators are often unsure of the best method. We present a simple statistical tool, Standardized WithIn class Sum of Squares (SWISS), that allows investigators to compare alternate data processing methods, such as different experimental methods, normalizations, or technologies, on a dataset in terms of how well they cluster a priori biological classes. SWISS uses Euclidean distance to determine which method does a better job of clustering the data elements based on a priori classifications. We apply SWISS to three different gene expression applications. The first application uses four different datasets to compare different experimental methods, normalizations, and gene sets. The second application, using data from the MicroArray Quality Control (MAQC) project, compares different microarray platforms. The third application compares different technologies: a single Agilent two-color microarray versus one lane of RNA-Seq. These applications give an indication of the variety of problems that SWISS can be helpful in solving. The SWISS analysis of one-color versus two-color microarrays provides investigators who use two-color arrays the opportunity to review their results in light of a single-channel analysis, with all of the associated benefits offered by this design. Analysis of the MACQ data shows differential intersite reproducibility by array platform. SWISS also shows that one lane of RNA-Seq clusters data by biological phenotypes as well as a single Agilent two-color microarray.