Effective simulation techniques for biological systems

In this paper we give an overview of some very recent work on the stochastic simulation of systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the Balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and discuss how novel computing implementations can enhance the performance of these simulations

Microbiology and atmospheric processes: Biological, physical and chemical characterization of aerosol particles

The interest in bioaerosols has traditionally been linked to health hazards for humans, animals and plants. However, several components of bioaerosols exhibit physical properties of great significance for cloud processes, such as ice nucleation and cloud condensation. To gain a better understanding of their influence on climate, it is therefore important to determine the composition, concentration, seasonal fluctuation, regional diversity and evolution of bioaerosols. In this paper, we will review briefly the existing techniques for detection, quantification, physical and chemical analysis of biological particles, attempting to bridge physical, chemical and biological methods for analysis of biological particles and integrate them with aerosol sampling techniques. We will also explore some emerging spectroscopy techniques for bulk and single-particle analysis that have potential for in-situ physical and chemical analysis. Lastly, we will outline open questions and further desired capabilities (e. g., in-situ, sensitive, both broad and selective, on-line, time-resolved, rapid, versatile, cost-effective techniques) required prior to comprehensive understanding of chemical and physical characterization of bioaerosols

Toll Based Measures for Dynamical Graphs

Biological networks are one of the most studied object in computational biology. Several methods have been developed for studying qualitative properties of biological networks. Last decade had seen the improvement of molecular techniques that make quantitative analyses reachable. One of the major biological modelling goals is therefore to deal with the quantitative aspect of biological graphs. We propose a probabilistic model that suits with this quantitative aspects. Our model combines graph with several dynamical sources. It emphazises various asymptotic statistical properties that might be useful for giving biological insightsComment: 11 page

Biological water quality monitoring using chemiluminescent and bioluminescent techniques

Automated chemiluminescence and bioluminescence sensors were developed for the continuous monitoring of microbial levels in water supplies. The optimal chemical procedures were determined for the chemiluminescence system to achieve maximum sensitivity. By using hydrogen peroxide, reaction rate differentiation, ethylene diamine tetraacetic acid (EDTA), and carbon monoxide pretreatments, factors which cause interference were eliminated and specificity of the reaction for living and dead bacteria was greatly increased. By employing existing technology with some modifications, a sensitive and specific bioluminescent system was developed

Advanced Fluorescence Microscopy Techniques-FRAP, FLIP, FLAP, FRET and FLIM

Fluorescence microscopy provides an efficient and unique approach to study fixed and living cells because of its versatility, specificity, and high sensitivity. Fluorescence microscopes can both detect the fluorescence emitted from labeled molecules in biological samples as images or photometric data from which intensities and emission spectra can be deduced. By exploiting the characteristics of fluorescence, various techniques have been developed that enable the visualization and analysis of complex dynamic events in cells, organelles, and sub-organelle components within the biological specimen. The techniques described here are fluorescence recovery after photobleaching (FRAP), the related fluorescence loss in photobleaching (FLIP), fluorescence localization after photobleaching (FLAP), Forster or fluorescence resonance energy transfer (FRET) and the different ways how to measure FRET, such as acceptor bleaching, sensitized emission, polarization anisotropy, and fluorescence lifetime imaging microscopy (FLIM). First, a brief introduction into the mechanisms underlying fluorescence as a physical phenomenon and fluorescence, confocal, and multiphoton microscopy is given. Subsequently, these advanced microscopy techniques are introduced in more detail, with a description of how these techniques are performed, what needs to be considered, and what practical advantages they can bring to cell biological research

Computational methods in cancer gene networking

In the past few years, many high-throughput techniques have been developed and applied to biological studies. These techniques such as “next generation” genome sequencing, chip-on-chip, microarray and so on can be used to measure gene expression and gene regulatory elements in a genome-wide scale. Moreover, as these technologies become more affordable and accessible, they have become a driving force in modern biology. As a result, huge amount biological data have been produced, with the expectation of increasing number of such datasets to be generated in the future. High-throughput data are more comprehensive and unbiased, but ‘real signals’ or biological insights, molecular mechanisms and biological principles are buried in the flood of data. In current biological studies, the bottleneck is no longer a lack of data, but the lack of ingenuity and computational means to extract biological insights and principles by integrating knowledge and high-throughput data. 

Here I am reviewing the concepts and principles of network biology and the computational methods which can be applied to cancer research. Furthermore, I am providing a practical guide for computational analysis of cancer gene networks

Development and validation of computational models of cellular interaction

In this paper we take the view that computational models of biological systems should satisfy two conditions – they should be able to predict function at a systems biology level, and robust techniques of validation against biological models must be available. A modelling paradigm for developing a predictive computational model of cellular interaction is described, and methods of providing robust validation against biological models are explored, followed by a consideration of software issues

Application of Raman Microspectroscopic and Raman imaging techniques for cell biological studies

Raman spectroscopy is being used to study biological molecules for some three decades now. Thanks to continuing advances in instrumentation more and more applications have become feasible in which molecules are studied in situ, and this has enabled Raman spectroscopy to enter the realms of biomedicine and cell biology [1-5].\ud Here we will describe some of the recent work carried out in our laboratory, concerning studies of human white blood cells and further instrumentational developments

Static Analysis for Systems Biology

This paper shows how static analysis techniques can help understanding biological systems. Based on a simple example will illustrate the outcome of performing three different analyses extracting information of increasing precision. We conclude by reporting on the potential impact and exploitation of these techniques in systems biology

Beyond DNA: Epigenetics and Proteomics in Forensic Science

The use of genetic evidence in criminal cases is well established and has improved the public opinion and credibility of forensic science. However, several shortcomings associated with current genetic profiling techniques exist. Scientific research aimed at increasing the overall knowledge and understanding of biological factors will lead to the development of methods capable of improving the discriminating power of DNA evidence, overcoming limitations associated with DNA evidence, or complementing current methods of DNA profiling. Increased research in the fields of epigenetics and proteomics are particularly promising and relevant to forensic science. Research suggests that epigenetic biomarkers can be used to approximate the age of biological sample donors, differentiate between DNA of monozygotic twins, distinguish between natural and synthesized DNA, and identify body fluid sources from forensic material. Proteomic research studies indicate that mass spectrometry can be used to identify biological matrices and tissue sources from forensic biological samples without compromising DNA evidence. The demand for improved forensic techniques necessitates further research into these fields and, specifically, how the associated methods can be used in forensic science