Computational cell biology. Methods and protocols.(English)Zbl 1417.92006

Methods in Molecular Biology 1819. Springer Protocols. New York, NY: Humana Press (ISBN 978-1-4939-8617-0/hbk; 978-1-4939-8618-7/ebook). xi, 436 p. (2018).
This book, presents itself as a heterogenous collection of novel directions of research in data mining approaches tailored for biological/medical questions. It comprises of five parts structured as an overview of the recent advances in the context of big data analyses.
Part one “Big data and implications in cell biology” comprises of two chapters, reviewing rule-based models and their applications (Chapter 1) and the applications of context filtering for the optimisation of protein-protein interaction network usage (Chapter 2). The former describes the framework provided by the quantitative associations between concentrations that aids the characterisation of dynamic relationships. The rule-based simulations (presented in Kappa [$$kappa$$] and PISKaS [parallel implementation of a spatial Kappa simulator]) are built on the stochastic simulation algorithm (SSA) and on ordinary differential equations (ODEs). In the second chapter, the authors illustrate context filtering on PPIs on HIPPIE and STRING and their effect on the downstream pathway analyses.
The second part comprises of three chapters and focuses on data driven analysis of high-throughput datasets. In the third chapter, the authors present SignaLink, a tool for the characterisation of multi-layered regulatory networks; in particular, they make use of the inter-connections between consecutive layers of regulations such as protein interactions and the underlaying transcriptional and post-transcriptional interactions. In the fourth chapter, the authors describe approaches to quantify the interplay between long non-coding RNAs (including lincRNAs, lncRNAs and circRNAs) and microRNAs in cancer; a particular emphasis is allocated to a new functional class (the competing endogenous RNAs, ceRNAs) which is used to describe the interactions between classes of non-coding RNAs. In the next chapter, the authors overview and perform a side-by-side comparison of methods and tools in genome wide association studies, nicely decorated with examples of their application.
The third part comprises of seven chapters and presents different angles of the network-based modelling of cellular phenotypes. In the sixth chapter, the authors present a yet another angle for the identification of depression expressed genes using FACS sorting combined with RNA sequencing from low input samples (around 40 cells per sample); the approach is illustrated on samples from Arabidopsis root protoplasts. In the seventh chapter, the focus is on host-parasite interactions presented from the protein-protein (and the integrations of multiple omics) angle. In the next chapter, an integrative approach for PPIs in virus-host systems is presented. This is followed by an overview of the SQUAD method for quantitative modelling, based on patterns of expression, of regulatory networks; it is based on Boolean approaches used for approximating continuous signals. In the tenth chapter yet another, interaction-driven, angle is tackled; the authors present miRNet an easy to use, web-based tool for functional analysis and visual exploration of miRNA-target interactions in a network context. In the eleventh chapter, an approach based on systems biology (functional characterization of interactions) is presented, for understanding of miRNA regulatory networks. The last chapter in this part describes a method for spatial analysis of functional enrichment (SAFE) applicable in large biological networks; the approach detects sub-networks that are statistically over-represented (in terms of functional groups or transcript quantification of the target phenotype).
The fourth part comprises of six chapters and covers the mathematical modelling of cellular phenotypes. In the thirteenth chapter, an overview of the large-scale computational prediction of protein structures (using mass-spectometry input) is presented. Next, in Chapter 14, a computational models for the cell cycle transitions is described; it is based on the analysis of differential equation models of switch-like behaviours. The authors also discuss the combination of multiple switches that lead to fast and robust transitions. In the fifteenth chapter, the integration of two high throughput methods: ATAC-seq and expression analysis, is presented for the simultaneous profiling of DNA accessibility and its effect on expression; both the laboratory protocol and the computational analysis (with examples) are provided. In the sixteenth chapter, methods for the computational network analysis of drug toxicity prediction are presented; the focus is mainly on the identification and characterization of adverse outcome pathways, to facilitate both the statistical quantification of differential expression and the functional annotation of genes. In the next chapter (17) the authors present models for assessing the epigenetic landscape in plant development; the aim of the study is on approaches that extend the gene regulatory network modelling to incorporate patterns of cell state transitions events that occur under diver genetic and environmental background conditions. In the last chapter of this part, the authors describe network models (based on Boolean implementations) for multi-scale host responses in infections and diseases.
The fifth part comprises of only one chapter which focuses on the analysis of heterogeneous cell populations by providing an approach for exploring the dynamics and effect of noise in a particular hormone signalling pathway.
The book recommends itself as an optimal starting point for understanding the current state of the art of data driven analyses, applied on high throughput datasets, with the aim of deciphering the regulatory interactions (either through computational or mathematical approaches) that could explain cellular phenotypes. This heterogeneous collection of chapters that covers various approaches also provides an overview of the complexity of this field and highlights some future challenges that will have to be addressed. The layout of the chapters makes them accessible to a wide variety of audiences from undergraduates, graduates and established researchers from a wide spectrum of fields from mathematics, computer science to biology and medicine. Alongside other collections of chapters from the methods in molecular biology collection (such as “gene regulatory networks”, edited by Guido Sanguinetti and Van Anh Huynh-Thu, see [G. Sanguinetti (ed.) and V. A. Huynh-Thu (ed.), Gene regulatory networks. Methods and protocols. New York, NY: Humana Press (2019; Zbl 1417.92005)]) this book is a must have for the current research in this field.

MSC:

 92-06 Proceedings, conferences, collections, etc. pertaining to biology 92C42 Systems biology, networks 92C40 Biochemistry, molecular biology 92C37 Cell biology 92-08 Computational methods for problems pertaining to biology

Zbl 1417.92005
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