The hallmarks of cancer.

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

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Initial sequencing and analysis of the human genome.

The emergence of order in natural systems is a constant source of inspiration for both physical and biological sciences. While the spatial order characterizing for example the crystals has been the basis of many advances in contemporary physics, most complex systems in nature do not offer such high degree of order. Many of these systems form complex networks whose nodes are the elements of the system and edges represent the interactions between them. 
Traditionally complex networks have been described by the random graph theory founded in 1959 by Paul Erdohs and Alfred Renyi. One of the defining features of random graphs is that they are statistically homogeneous, and their degree distribution (characterizing the spread in the number of edges starting from a node) is a Poisson distribution. In contrast, recent empirical studies, including the work of our group, indicate that the topology of real networks is much richer than that of random graphs. In particular, the degree distribution of real networks is a power-law, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network. 
The scale-free topology of real networks has very important consequences on their functioning. For example, we have discovered that scale-free networks are extremely resilient to the random disruption of their nodes. On the other hand, the selective removal of the nodes with highest degree induces a rapid breakdown of the network to isolated subparts that cannot communicate with each other. 
The non-trivial scaling of the degree distribution of real networks is also an indication of their assembly and evolution. Indeed, our modeling studies have shown us that there are general principles governing the evolution of networks. Most networks start from a small seed and grow by the addition of new nodes which attach to the nodes already in the system. This process obeys preferential attachment: the new nodes are more likely to connect to nodes with already high degree. We have proposed a simple model based on these two principles wich was able to reproduce the power-law degree distribution of real networks. Perhaps even more importantly, this model paved the way to a new paradigm of network modeling, trying to capture the evolution of networks, not just their static topology.

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Statistical mechanics of complex networks

A genetic model for colorectal tumorigenesis

http://www.maths.qmul.ac.uk/%7Elatora/report_06.pdf

Complex networks: Structure and dynamics

Activation domains are functional modules that enable sequence-specific DNA binding proteins to stimulate transcription. The structural basis for the function of activation domains is poorly understood. A combination of nuclear magnetic resonance (NMR) and biochemical experiments revealed that the minimal acidic activation domain of the herpes simplex virus VP16 protein undergoes an induced transition from random coil to α helix upon binding to its target protein, hTAFII31 (a human TFIID TATA box–binding protein-associated factor). Identification of the two hydrophobic residues that make nonpolar contacts suggests a general recognition motif of acidic activation domains for hTAFII31.

https://science.sciencemag.org/content/sci/277/5330/1310.full.pdf

Induced α Helix in the VP16 Activation Domain upon Binding to a Human TAF

Allele Specific p53 Mutant Reactivation

A common ancestor to the three p53 family members of human genes p53, p63, and p73 is first detected in the evolution of modern‐day sea anemones, in which both structurally and functionally it acts to protect the germ line from genomic instabilities in response to stresses. This p63/p73 common ancestor gene is found in almost all invertebrates and first duplicates to produce a p53 gene and a p63/p73 ancestor in cartilaginous fish. Bony fish contain all three genes, p53, p63, and p73, and the functions of these three transcription factors diversify in the higher vertebrates. Thus, this gene family has preserved its structural features and functional activities for over one billion years of evolution.

/pdf/the-origins-and-evolution-of-the-p53-family-of-genes-oqfoztokq6.pdf

The Origins and Evolution of the p53 Family of Genes

Irradiation of mammalian cells with UV light results in a dose-dependent accumulation of the p53 tumor-suppressor gene product that is evident within 2 hr. UV treatment causes a dramatic increase in p53-specific transcriptional transactivation activity and an increase in expression of the p53-responsive gene mdm-2. UV-stimulated mdm-2 expression is not directly correlated with the level of p53 protein in a cell because mdm-2 induction is delayed at high UV doses even though p53 levels rise almost immediately. Cells lacking p53 protein do not respond to UV by increasing their expression of mdm-2. The delayed induction of mdm-2 at high UV doses suggests that, in addition to p53 protein levels, other factors contribute to the regulation of mdm-2 expression following UV treatment. The time of induction of mdm-2 in cells treated with UV light correlates with recovery of normal rates of DNA synthesis, presumably after DNA repair. These data indicate a possible role for mdm-2 in cell cycle progression.

https://www.pnas.org/content/pnas/90/24/11623.full.pdf

The mdm-2 gene is induced in response to UV light in a p53-dependent manner

A quantitative algorithm was developed and applied to predict target genes of microRNAs encoded by herpesviruses. Although there is almost no conservation among microRNAs of different herpesvirus subfamilies, a common pattern of regulation emerged. The algorithm predicts that herpes simplex virus 1, human cytomegalovirus, Epstein–Barr virus, and Kaposi's sarcoma-associated herpesvirus all employ microRNAs to suppress expression of their own genes, including their immediate-early genes. In the case of human cytomegalovirus, a virus-coded microRNA, miR-112-1, was predicted to target the viral immediate-early protein 1 mRNA. To test this prediction, mutant viruses were generated that were unable to express the microRNA, or encoded an immediate-early 1 mRNA lacking its target site. Analysis of RNA and protein within infected cells demonstrated that miR-UL112-1 inhibits expression of the major immediate-early protein. We propose that herpesviruses use microRNA-mediated suppression of immediate-early genes as part of their strategy to enter and maintain latency.

Arnold J. Levine

Papers

Induced α Helix in the VP16 Activation Domain upon Binding to a Human TAF

Allele Specific p53 Mutant Reactivation

The Origins and Evolution of the p53 Family of Genes

The mdm-2 gene is induced in response to UV light in a p53-dependent manner

Suppression of immediate-early viral gene expression by herpesvirus-coded microRNAs: Implications for latency