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Madison, WI, United States

Flack J.C.,Wisconsin Institute for Discovery | Flack J.C.,Santa Fe Institute
Current Biology | Year: 2013

A hallmark of human communication is vocal turn taking. Until recently, turn taking was thought to be unique to humans but new data indicate that marmosets, a new world monkey, take turns when vocalizing too. © 2013 Elsevier Ltd. Source


Fischer M.,University of Leipzig | Steiner L.,Wisconsin Institute for Discovery | Steiner L.,University of Leipzig | Engeland K.,University of Leipzig
Cell Cycle | Year: 2014

The predominant function of the tumor suppressor p53 is transcriptional regulation. It is generally accepted that p53-dependent transcriptional activation occurs by binding to a specific recognition site in promoters of target genes. Additionally, several models for p53-dependent transcriptional repression have been postulated. Here, we evaluate these models based on a computational meta-analysis of genome-wide data. Surprisingly, several major models of p53-dependent gene regulation are implausible. Meta-analysis of large-scale data is unable to confirm reports on directly repressed p53 target genes and falsifies models of direct repression. This notion is supported by experimental re-analysis of representative genes reported as directly repressed by p53. Therefore, p53 is not a direct repressor of transcription, but solely activates its target genes. Moreover, models based on interference of p53 with activating transcription factors as well as models based on the function of ncRNAs are also not supported by the meta-analysis. As an alternative to models of direct repression, the meta-analysis leads to the conclusion that p53 represses transcription indirectly by activation of the p53-p21-DREAM/RB pathway. © Martin Fischer, Lydia Steiner, and Kurt Engeland. Source


News Article | May 27, 2011
Site: www.xconomy.com

Jeffrey Leiden, MD, PhD is a Managing Director of Clarus Ventures, LLC, a life sciences venture capital firm headquartered in Cambridge, MA. Prior to joining Clarus in 2006, Dr. Leiden was President and COO of Abbott Laboratories, Pharmaceuticals Products Group, and a member of the Abbott Board of Directors and the TAP Board of Directors from 2000-2006. From 1987-2000 Dr. Leiden held several academic appointments, including Chief of Cardiology and Director of the Cardiovascular Research Institute at the University of Chicago, the Elkan R. Blout Professor of Biological Sciences at the Harvard School of Public Health, Professor of Medicine at Harvard Medical School and Assoc. Professor of Medicine and Associate Investigator of the Howard Hughes Medical Institute at the University of Michigan. During his academic career, Dr. Leiden studied the transcriptional regulation of cardiovascular and immune cell development. Dr. Leiden is currently a director of Biolex Therapeutics and Catabasis Pharmaceuticals, and is Chairman of the Board of Lycera Corp, Variation Biotechnologies and TyRx, Inc. He is also the Lead Independent Director of Vertex Pharmaceuticals (NASDAQ:VRTX), and a non-executive director and Vice Chairman of the Board of Shire plc (LSE: SHP). He is a trustee of the University of Pennsylvania School of Medicine and Vice Chairman of the Board of Trustees of the Ravinia Music Festival. Dr. Leiden received both his medical degree and PhD from the University of Chicago and an honorary MA from Harvard University. He is an elected member of both the American Academy of Arts and Sciences, and the Institute of Medicine of the National Academy of Sciences. For more information, click here.


Roy S.,University of Wisconsin - Madison | Roy S.,Wisconsin Institute for Discovery | Lagree S.,University of Wisconsin - Madison | Hou Z.,Morgridge Institute for Research | And 5 more authors.
PLoS Computational Biology | Year: 2013

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. © 2013 Roy et al. Source


Flack J.C.,Wisconsin Institute for Discovery | Flack J.C.,Santa Fe Institute
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2012

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. © 2012 The Royal Society. Source

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