Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study

Background  

A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expression. Because of the complexity and the high dimensionality of microarray gene expression profiles, the dimensional reduction of raw expression data and the feature selections necessary for, for example, classification of disease samples remains a challenge. To solve the problem we propose a two-level analysis. First self-organizing map (SOM) is used. SOM is a vector quantization method that simplifies and reduces the dimensionality of original measurements and visualizes individual tumor sample in a SOM component plane. Next, hierarchical clustering and K-means clustering is used to identify patterns of gene expression useful for classification of samples.     

A census of membrane-bound and intracellular signal transduction proteins in bacteria: Bacterial IQ,extroverts and introverts

Background  

Analysis of complete microbial genomes showed that intracellular parasites and other microorganisms that inhabit stable ecological niches encode relatively primitive signaling systems, whereas environmental microorganisms typically have sophisticated systems of environmental sensing and signal transduction.     

BioPhysConnectoR: Connecting Sequence Information and Biophysical Models

Background  

One of the most challenging aspects of biomolecular systems is the understanding of the coevolution in and among the molecule(s).     

Electrical impedance tomography imaging using a priori ultrasound data

Background  

Different imaging systems (e.g. electrical, magnetic, and ultrasound) rely on a wide variety of physical properties, and the datasets obtained from such systems provide only partial information about the unknown true state. One approach is to choose complementary imaging systems, and to combine the information to achieve a better representation.     

Co-product allocation in life cycle assessments of seafood production systems: Review of problems and strategies

Background, Aim and Scope  

As Life Cycle Assessment is being increasingly applied to study fisheries and aquaculture systems, the LCA methodology must be adapted to address the unique aspects of these systems. The focus of this methodological paper is the specific allocation problems faced in studying seafood production systems and how they have been addressed to date.     

An integrated system for genetic analysis

Background  

Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet are easy to use.     

Incremental and unifying modelling formalism for biological interaction networks

Background  

An appropriate choice of the modeling formalism from the broad range of existing ones may be crucial for efficiently describing and analyzing biological systems.     

A systematic approach for testing expression of human full-length proteins in cell-free expression systems

Background  

The growing field of proteomics and systems biology is resulting in an ever increasing demand for purified recombinant proteins for structural and functional studies. Here, we show a systematic approach to successfully express a full-length protein of interest by using cell-free and cell-based expression systems.     

Identification of metabolic system parameters using global optimization methods

Background  

The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important.     

Isothermal micro calorimetry - a new method for MIC determinations: results for 12 antibiotics and reference strains of E. coli and S. aureus

Background  

Antimicrobial susceptibility testing of microorganisms is performed by either disc diffusion or broth dilution tests. In clinical use, the tests are often still performed manually although automated systems exist. Most systems, however, are based on turbidometric methods which have well-known drawbacks.     

Simple generation of site-directed point mutations in the <Emphasis Type="Italic">Escherichia coli</Emphasis> chromosome using Red<Superscript>®</Superscript>/ET<Superscript>®</Superscript> Recombination

Background  

Introducing point mutations into bacterial chromosomes is important for further progress in studies relying on functional genomics, systems- and synthetic biology, and for metabolic engineering. For many investigations, chromosomal systems are required rather than artificial plasmid based systems.     

Parameter estimation in biochemical systems models with alternating regression

Background  

The estimation of parameter values continues to be the bottleneck of the computational analysis of biological systems. It is therefore necessary to develop improved methods that are effective, fast, and scalable.     

A versatile approach to multiple gene RNA interference using microRNA-based short hairpin RNAs

Background  

Effective and stable knockdown of multiple gene targets by RNA interference is often necessary to overcome isoform redundancy, but it remains a technical challenge when working with intractable cell systems.     

Predicted class-I aminoacyl tRNA synthetase-like proteins in non-ribosomal peptide synthesis

Background  

Recent studies point to a great diversity of non-ribosomal peptide synthesis systems with major roles in amino acid and co-factor biosynthesis, secondary metabolism, and post-translational modifications of proteins by peptide tags. The least studied of these systems are those utilizing tRNAs or aminoacyl-tRNA synthetases (AAtRS) in non-ribosomal peptide ligation.     

Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster

Background  

Reaction-diffusion systems are frequently used in systems biology to model developmental and signalling processes. In many applications, count numbers of the diffusing molecular species are very low, leading to the need to explicitly model the inherent variability using stochastic methods. Despite their importance and frequent use, parameter estimation for both deterministic and stochastic reaction-diffusion systems is still a challenging problem.     

Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study

Background  

Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modelling research, including that of auxin transport, uses numerical simulations to study the behaviour of large systems of deterministic ordinary differential equations, with little consideration of alternative modelling frameworks.     

So what do we really mean when we say that systems biology is <Emphasis Type="Italic">holistic</Emphasis>?

Background  

An old debate has undergone a resurgence in systems biology: that of reductionism versus holism. At least 35 articles in the systems biology literature since 2003 have touched on this issue. The histories of holism and reductionism in the philosophy of biology are reviewed, and the current debate in systems biology is placed in context.     

Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

Background  

Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the hypothalamus and several metabolic tissues, resulting in an energy imbalance at the systems level.     

ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes

Background  

It necessary to use highly accurate and statistics-based systems for viral and phage genome annotations. The GeneMark systems for gene-finding in virus and phage genomes suffer from some basic drawbacks. This paper puts forward an alternative approach for viral and phage gene-finding to improve the quality of annotations, particularly for newly sequenced genomes.