Hot off the presses! Mar 18 Cell

The Mar 18 issue of the Cell is now up on Pubget (About Cell): if you're at a subscribing institution, just click the link in the latest link at the home page. (Note you'll only be able to get all the PDFs in the issue if your institution subscribes to Pubget.)

Latest Articles Include:

• In This Issue
  - cell 144(6):827, 829 (2011)
  In thinking about complexity, it's frequently invoked that the whole is greater than the sum of its parts. This notion serves as one of the motivating principles of systems biology, which seeks to understand the emergent properties of complex biological systems. Among many biologists, systems biology is also synonymous with the use of particular approaches, including high-throughput techniques, large-scale integration of datasets, and computational modeling to probe system behaviors. There is indeed little doubt that the recent growth of the field has been fueled by the massive expansion in the amount of data being generated in the biological sciences—first from genome sequencing and more recently from such sources as transcriptomics, proteomics, and high-throughput imaging. Given this rising tide of data, there is an urgent need for new ways of analyzing large datasets and for conceptualizing biological complexity. It is in this context that we present our 2011 Spec! ial Review Issue on systems biology. The overarching goal of this collection is to highlight biological insights revealed by the quantitative and computational approaches associated with systems biology. To accomplish this, the issue includes topics that span vastly different size and time scales, from protein-protein interactions to disease models, from transcriptional dynamics to evolutionary processes. For the issue's diversity, depth, and thought-provoking insights, we would like to thank the many distinguished authors and reviewers who generously contributed their time and effort. In reading the issue, we hope that you will find that the collection, like biological systems, is more than the sum of its individual parts, providing a new perspective on this rapidly changing field.
• Control of Biomolecule Abundance
  - cell 144(6):831, 833 (2011)
  Like any company that manages its resources with an eye on profitability, a cell regulates its constituent biomolecules, compensating for changes in internal function, external conditions, and sector or organismal trends. This issue's Select focuses on new findings that reveal broad insights into how dynamic changes in RNAs and proteins are made and how those changes impact cellular function and fitness.
• Systems Biology: What's the Next Challenge?
  - cell 144(6):837-838 (2011)
  
• Systems Biology: Evolving into the Mainstream
  - cell 144(6):839-841 (2011)
  Systems approaches to biology are steadily widening their reach, but the road to integration and acceptance has been fraught with skepticism and technical hurdles. Interdisciplinary research teams at systems biology centers around the globe are working to win over the critics.
• Don't Fear the Command Line!
  - cell 144(6):842-843 (2011)
  
• Network News: Innovations in 21st Century Systems Biology
  - cell 144(6):844-849 (2011)
  A decade ago, seminal perspectives and papers set a strong vision for the field of systems biology, and a number of these themes have flourished. Here, we describe key technologies and insights that have elucidated the evolution, architecture, and function of cellular networks, ultimately leading to the first predictive genome-scale regulatory and metabolic models of organisms. Can systems approaches bridge the gap between correlative analysis and mechanistic insights?
• The Cell in an Era of Systems Biology
  - cell 144(6):850-854 (2011)
  The increasing use of high-throughput technologies and computational modeling is revealing new levels of biological function and organization. How are these features of systems biology influencing our view of the cell?
• Informing Biological Design by Integration of Systems and Synthetic Biology
  - cell 144(6):855-859 (2011)
  Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields.
• Boosting Signal-to-Noise in Complex Biology: Prior Knowledge Is Power
  - cell 144(6):860-863 (2011)
  A major difficulty in the analysis of complex biological systems is dealing with the low signal-to-noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal-to-noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.
• Principles and Strategies for Developing Network Models in Cancer
  - cell 144(6):864-873 (2011)
  The flood of genome-wide data generated by high-throughput technologies currently provides biologists with an unprecedented opportunity: to manipulate, query, and reconstruct functional molecular networks of cells. Here, we outline three underlying principles and six strategies to infer network models from genomic data. Then, using cancer as an example, we describe experimental and computational approaches to infer "differential" networks that can identify genes and processes driving disease phenotypes. In conclusion, we discuss how a network-level understanding of cancer can be used to predict drug response and guide therapeutics.
• Modeling the Cell Cycle: Why Do Certain Circuits Oscillate?
  - cell 144(6):874-885 (2011)
  Computational modeling and the theory of nonlinear dynamical systems allow one to not simply describe the events of the cell cycle, but also to understand why these events occur, just as the theory of gravitation allows one to understand why cannonballs fly in parabolic arcs. The simplest examples of the eukaryotic cell cycle operate like autonomous oscillators. Here, we present the basic theory of oscillatory biochemical circuits in the context of the Xenopus embryonic cell cycle. We examine Boolean models, delay differential equation models, and especially ordinary differential equation (ODE) models. For ODE models, we explore what it takes to get oscillations out of two simple types of circuits (negative feedback loops and coupled positive and negative feedback loops). Finally, we review the procedures of linear stability analysis, which allow one to determine whether a given ODE model and a particular set of kinetic parameters will produce oscillations.
• Impulse Control: Temporal Dynamics in Gene Transcription
  - cell 144(6):886-896 (2011)
  Regulatory circuits controlling gene expression constantly rewire to adapt to environmental stimuli, differentiation cues, and disease. We review our current understanding of the temporal dynamics of gene expression in eukaryotes and prokaryotes and the molecular mechanisms that shape them. We delineate several prototypical temporal patterns, including "impulse" (or single-pulse) patterns in response to transient environmental stimuli, sustained (or state-transitioning) patterns in response to developmental cues, and oscillating patterns. We focus on impulse responses and their higher-order temporal organization in regulons and cascades and describe how core protein circuits and cis-regulatory sequences in promoters integrate with chromatin architecture to generate these responses.
• Signaling from the Living Plasma Membrane
  - cell 144(6):897-909 (2011)
  Our understanding of the plasma membrane, once viewed simply as a static barrier, has been revolutionized to encompass a complex, dynamic organelle that integrates the cell with its extracellular environment. Here, we discuss how bidirectional signaling across the plasma membrane is achieved by striking a delicate balance between restriction and propagation of information over different scales of time and space and how underlying dynamic mechanisms give rise to rich, context-dependent signaling responses. In this Review, we show how computer simulations can generate counterintuitive predictions about the spatial organization of these complex processes.
• Cellular Decision Making and Biological Noise: From Microbes to Mammals
  - cell 144(6):910-925 (2011)
  Cellular decision making is the process whereby cells assume different, functionally important and heritable fates without an associated genetic or environmental difference. Such stochastic cell fate decisions generate nongenetic cellular diversity, which may be critical for metazoan development as well as optimized microbial resource utilization and survival in a fluctuating, frequently stressful environment. Here, we review several examples of cellular decision making from viruses, bacteria, yeast, lower metazoans, and mammals, highlighting the role of regulatory network structure and molecular noise. We propose that cellular decision making is one of at least three key processes underlying development at various scales of biological organization.
• Measuring and Modeling Apoptosis in Single Cells
  - cell 144(6):926-939 (2011)
  Cell death plays an essential role in the development of tissues and organisms, the etiology of disease, and the responses of cells to therapeutic drugs. Here we review progress made over the last decade in using mathematical models and quantitative, often single-cell, data to study apoptosis. We discuss the delay that follows exposure of cells to prodeath stimuli, control of mitochondrial outer membrane permeabilization, switch-like activation of effector caspases, and variability in the timing and probability of death from one cell to the next. Finally, we discuss challenges facing the fields of biochemical modeling and systems pharmacology.
• Control of the Embryonic Stem Cell State
  - cell 144(6):940-954 (2011)
  Embryonic stem cells and induced pluripotent stem cells hold great promise for regenerative medicine. These cells can be propagated in culture in an undifferentiated state but can be induced to differentiate into specialized cell types. Moreover, these cells provide a powerful model system for studies of cellular identity and early mammalian development. Recent studies have provided insights into the transcriptional control of embryonic stem cell state, including the regulatory circuitry underlying pluripotency. These studies have, as a consequence, uncovered fundamental mechanisms that control mammalian gene expression, connect gene expression to chromosome structure, and contribute to human disease.
• Pattern, Growth, and Control
  - cell 144(6):955-969 (2011)
  Systems biology seeks not only to discover the machinery of life but to understand how such machinery is used for control, i.e., for regulation that achieves or maintains a desired, useful end. This sort of goal-directed, engineering-centered approach also has deep historical roots in developmental biology. Not surprisingly, developmental biology is currently enjoying an influx of ideas and methods from systems biology. This Review highlights current efforts to elucidate design principles underlying the engineering objectives of robustness, precision, and scaling as they relate to the developmental control of growth and pattern formation. Examples from vertebrate and invertebrate development are used to illustrate general lessons, including the value of integral feedback in achieving set-point control; the usefulness of self-organizing behavior; the importance of recognizing and appropriately handling noise; and the absence of "free lunch." By illuminating such pri! nciples, systems biology is helping to create a functional framework within which to make sense of the mechanistic complexity of organismal development.
• Evolution of Gene Regulatory Networks Controlling Body Plan Development
  - cell 144(6):970-985 (2011)
  Evolutionary change in animal morphology results from alteration of the functional organization of the gene regulatory networks (GRNs) that control development of the body plan. A major mechanism of evolutionary change in GRN structure is alteration of cis-regulatory modules that determine regulatory gene expression. Here we consider the causes and consequences of GRN evolution. Although some GRN subcircuits are of great antiquity, other aspects are highly flexible and thus in any given genome more recent. This mosaic view of the evolution of GRN structure explains major aspects of evolutionary process, such as hierarchical phylogeny and discontinuities of paleontological change.
• Interactome Networks and Human Disease
  - cell 144(6):986-998 (2011)
  Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.
• SnapShot: Protein-Protein Interaction Networks
  - cell 144(6):1000-1000.e1 (2011)