Themed collection Computational and systems biology

M. Madan Babu and Hirotada Mori introduce this themed issue of Molecular BioSystems focusing on Computational and systems biology

The use of qualitative approaches for modelling the cell cycle is presented and discussed.

Many important questions in the haematopoietic system remain unanswered or even unanswerable with current experimental tools. Scientists have therefore increasingly turned to modelling to tackle complexity at multiple levels ranging from networks of genes to the behaviour of cells and tissues.

Topological properties such as the power law, small world and scale-freeness have been claimed as “universal laws” for biological and other complex networks. However these properties are contradicted by statistical or even by visual comparison of the observed distribution (green) with the power law (blue). We review and discuss the field of network biology and its relevance in terms of function and evolution.

An accessible and comprehensive introduction to decision tree-based methods for supervised learning in computational and systems biology.

We review the contribution that systems approaches have made to the understanding of the circadian clock in Arabidopsis thaliana and compare this to systems analyses of mammalian circadian clocks.

Large-scale technology has enabled us to measure and compare protein and mRNA expression in different organisms. From these data we gain insights on the underlying regulation of translation and protein degradation.

This review addresses whether a genomic code for nucleosome positioning exists and how nucleosome arrays are organised in vivo.

Mapping protein–DNA interactions in vivo via chromatin immunoprecipitation and microarrays or sequencing provides powerful insights into genome organisation and transcriptional regulation.

This review focuses on the use of structural interactomics in the development of novel therapeutics.

The authors review different aspects of the problem of conformational averaging in structural biology experiments, discuss the pitfalls of the associated “single-structure paradigm” and describe different computational solutions to address the problem.

This review focuses on the methodologies currently available for using and interpreting large datasets of genetic interactions for functional gene groups, elaborates on the challenges ahead and highlights the need for comprehensive integrative analysis to extract the wealth of information found.

This historical overview on modelling pattern formation in the early Drosophila embryo shows how experimental and theoretical approaches have converged over the past decades to create a powerful new methodology for the systems-level study of developmental gene regulatory networks.

We review existing quantitative methods to score overlaps, and to cluster binding events in ChIP and DamID profiles. We provide a simple guide to some of the statistical tools used by these methods.

Droplets with femto- to nanolitre volumes, handled in microfluidic devices, are an increasingly popular platform for high-throughput experiments that can be carried out under controlled conditions with a quantitative readout.

Extracellular glycoprotein interactions are not detected by most high throughput assays creating “blind-spots” in protein interaction maps. This review examines this problem and discusses recent advances that have begun to address it.

In the developing retina, nearby neurons are spontaneously active, producing progagating patterns of activity, known as retinal waves. In this article we review several computational models used to help evaluate the mechanisms that might be responsible for the generation of retinal waves.

Recent explosion in the amount of “omics” data opens new ways of predicting novel drugs and drug targets using network-based approaches.

The metabolic, defensive, communicative and pathogenic capabilities of eubacteria depend on their repertoire of genes and ability to regulate the expression of them. Sigma and transcription factors have fundamental roles in controlling these processes.

Escherichia coli may hold the key to understanding the unique biomolecular properties of prokaryotic cells. Recent advances in high-throughput screening techniques and subsequent results are discussed here.

We investigate the relationship between mRNA expression levels and protein aggregation propensities at the proteomic level, and find that these quantities exhibit a significant correlation when they are averaged across subcellular localisations.

We discuss a statistical approach—approximate Bayesian computation (ABC)—which allows us to approximate the posterior distribution over model-parameters and show how this can add insights into our understanding of the system dynamics.

A novel energy based approach for identifying the binding site residues in protein–protein complexes showed the importance of cation–π, electrostatic and aromatic interactions with charged and aromatic residues at binding sites.

We evaluated the contribution of transposable elements (TEs) to the c-Myc regulatory network by searching for c-Myc binding sites derived from TEs and by analyzing the expression and function of target genes with nearby TE-derived c-Myc binding sites.

Homodimeric protein tryptophanyl tRNA synthetase (TrpRS) has a Rossmann fold domain and belongs to the 1c subclass of aminoacyl tRNA synthetases. In this study, we have modeled the structure of human TrpRS bound to the activated ligand and the cognate tRNA.

Pyknons are non-random sequence patterns significantly repeated throughout non-coding genomic DNA. DNA sequence patterns from the Arabidopsis thaliana genome were detected using a probability-based method. We postulate that RNA-mediated gene silencing leads to the accumulation of gene sequences in non-coding DNA regions.

A combined high resolution ¹H NMR and gas chromatography mass spectrometry based metabolomic approach was used to monitor and distinguish different genotoxic compounds from other types of toxic lesion.

The relative lower stability of promoter regions as compared to neighboring genomic sequences has been used to develop an algorithm ‘PromPredict' for promoter identification. It is found to be very reliable when applied to whole genome annotation for microbial genome sequences.

We performed a comprehensive analysis of a literature-mined human signaling network by integrating data on ubiquitin-mediated protein half-lives. Our findings have implications for the development of cancer treatments and prognostic markers focused on the ubiquitination machinery.

Bacteria such as Escherichia coli can detect remarkably low concentrations of nutrients such as amino acids. We explain this sensitivity by postulating an amplification step in the signal cascade due to cooperative interactions between molecules of the protein kinase CheA.

We have performed sequence analysis and molecular modeling of 5-HT_2A that has revealed a set of conserved residues and motifs considered to play an important role in maintaining structural integrity and function of the receptor.

Integrating the topological characteristics of protein–protein interaction networks and the gene sequence properties, we present a machine learning approach for the prediction of essential genes.

We present a new computational method for predicting metabolic gene–nutrient interactions (GNI) that uncovers the dependence of gene essentiality on the presence or absence of nutrients in the growth medium.

Tuberculosis remains a disease that causes havoc despite efforts to conquer the pathogen using structure-based rational drug design. We try to unravel thirteen intrinsically disordered essential proteins as potential drug targets with particular focus on GlmU, FtsW and Obg.

This paper provides a detailed map of ubiquitin specific protease (USP) catalytic domains from human and yeast, revealing large insertions that intersperse the catalytic fold at five points.

The Escherichia coli Rsd protein forms 1 : 1 complexes with σ⁷⁰ protein, which is the major factor in determining promoter recognition by RNA polymerase. Here we describe measurements of the levels of Rsd, RNA polymerase, σ⁷⁰ and the alternative σ³⁸ factor.

This manuscript presents a logical compositional modelling method and its application to the budding yeast cell cycle. The resulting model couples three regulatory modules: the core cycling engine, the morphogenetic checkpoint and mitotic exit, and qualitatively accounts for the wild-type and numerous mutant behaviours.

We demonstrate the efficacy of combined graph theoretical and machine learning approaches in ranking essential nodes from a large network of genome-wide functional linkages, which yields predictions with high accuracy. We therefore perceive such predictions as highly useful in applications such as defining and prioritizing drug targets.

We propose a strategy that incorporates genomic sequence data and metabolite profiles into modelling approaches to arrive at improved gene annotations and more complete genome-scale metabolic networks.

We illustrate the value of the reverse-engineering algorithm LeMoNe as a biological hypothesis generator for differential gene expression.

By integrating known and de novo predicted motifs with a comprehensive gene expression compendium, we expand the current Bacillus subtilis regulatory network and provide insight into its condition dependency.

Intrinsically disordered regions (IDRs) of helical bundle and beta barrel integral transmembrane proteins as well as the IDRs of water soluble proteins all exhibit statistically distinct amino acid compositional biases. This suggested that developing new predictors can increase the accuracy of disorder prediction for integral transmembrane proteins.

Interactions of extracellular protein domains in H. pylori with human proteins have been predicted. Analysis of some of the examples reveals that the interactions are consistent with the structural compatibility of binding partners. Examples of interactions with discernible biological relevance are discussed.

Structural data, efficient structural comparison algorithms and appropriate datasets and filters can assist in getting an insight into time dimensionality in interaction networks; in predicting which interactions can and cannot co-exist; and in obtaining concrete predictions consistent with experiment.

We show that regulatory G-quadruplexes found upstream of transcription start sites are located in a region depleted of nucleosomes. Generally in Caenorhabditis elegans and humans, stable G-quadruplexes are located outside nucleosome-bound regions, hence making it easier for them to form in vivo.

We extract the minimal core of causal relations, uncovering the hierarchical and modular organisation from a novel dynamical/causal perspective in a comparative study for Escherichia coli, Bacillus subtilis and Saccharomyces cerevisiae gene regulatory networks.

This paper describes the construction principles of a dependency network representing human protein coding genes integrating genomic, transcriptomic and proteomic profiles. We demonstrate the improved analysis of differential gene expression profiles at the level of this network.

Several factors are known to determine chromatin organization. Recent observations indicate a widespread role of G-quadruplexes, or G4 motifs, in gene regulation. Our results show a structural motif as a possible nucleosome exclusion signal and predict an alternate/additional regulatory role of G4 motifs.

Schematic illustration of metabolism in a mycobacterial cell. Network construction and graph analysis identifies strategic nodes for maximal and efficient disruption of metabolism, suggesting highly potent drug target combinations.

Crosstalk between signals emanating from two distinct cell surface receptors resulted in an additive effect on gene expression. Products of these genes then counteracted to fine-tune the cellular phenotypic response.

The genome-wide microarray analysis of stress-dependent gene expression due to changes in DNA supercoiling has been performed in the cyanobacterium Synechocystis. Gene expression profiles are presented for responses to cold, heat, and salt stresses.