PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium

Protein Analysis THrough Evolutionary Relationships (PANTHER) is a comprehensive software system for inferring the functions of genes based on their evolutionary relationships. Phylogenetic trees of gene families form the basis for PANTHER and these trees are annotated with ontology terms describing the evolution of gene function from ancestral to modern day genes. One of the main applications of PANTHER is in accurate prediction of the functions of uncharacterized genes, based on their evolutionary relationships to genes with functions known from experiment. The PANTHER website, freely available at http://www.pantherdb.org, also includes software tools for analyzing genomic data relative to known and inferred gene functions. Since 2007, there have been several new developments to PANTHER: (i) improved phylogenetic trees, explicitly representing speciation and gene duplication events, (ii) identification of gene orthologs, including least diverged orthologs (best one-to-one pairs), (iii) coverage of more genomes (48 genomes, up to 87% of genes in each genome; see http://www.pantherdb.org/panther/summaryStats.jsp), (iv) improved support for alternative database identifiers for genes, proteins and microarray probes and (v) adoption of the SBGN standard for display of biological pathways. In addition, PANTHER trees are being annotated with gene function as part of the Gene Ontology Reference Genome project, resulting in an increasing number of curated functional annotations

Framework for a Protein Ontology

Biomedical ontologies are emerging as critical tools in genomic and proteomic research, where complex data in disparate resources need to be integrated. A number of ontologies describe properties that can be attributed to proteins. For example, protein functions are described by the Gene Ontology (GO) and human diseases by SNOMED CT or ICD10. There is, however, a gap in the current set of ontologies – one that describes the protein entities themselves and their relationships. We have designed the PRotein Ontology (PRO) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modifications). PRO will allow the specification of relationships between PRO, GO and other ontologies in the OBO Foundry. Here we describe the initial development of PRO, illustrated using human and mouse proteins involved in the transforming growth factor-beta and bone morphogenetic protein signaling pathways

On the Bit Security of Elliptic Curve Diffie--Hellman

This paper gives the first bit security result for the elliptic curve Diffie--Hellman key exchange protocol for elliptic curves defined over prime fields. About $5/6$ of the most significant bits of the $x$-coordinate of the Diffie--Hellman key are as hard to compute as the entire key. A similar result can be derived for the $5/6$ lower bits. The paper also generalizes and improves the result for elliptic curves over extension fields, that shows that computing one component (in the ground field) of the Diffie--Hellman key is as hard to compute as the entire key

Draft genome sequence of the Tremellomycetes yeast Papiliotrema laurentii 5307AH, isolated from aircraft.

Papiliotrema laurentii 5307AH was isolated from an aircraft polymer-coated surface. The genome size is 19,510,785 bp with a G + C content of 56%. The genome harbors genes encoding oxygenases, cutinases, lipases, and enzymes for styrene degradation, all of which could play a critical role in survival on xenobiotic surfaces

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Antimetastatic Potential of PAI-1 Specific RNA Aptamers

The serine protease inhibitor plasminogen activator inhibitor-1 (PAI-1) is increased in several cancers, including breast, where it is associated with a poor outcome. Metastatic breast cancer has a dismal prognosis, as evidenced by treatment goals that are no longer curative but are largely palliative in nature. PAI-1 competes with integrins and the urokinase plasminogen activator receptor on the surface of breast cancer cells for binding to vitronectin. This results in the detachment of tumor cells from the extracellular matrix, which is critical to the metastatic process. For this reason, we sought to isolate RNA aptamers that disrupt the interaction between PAI-1 and vitronectin. Through utilization of combinatorial chemistry techniques, aptamers have been selected that bind to PAI-1 with high affinity and specificity. We identified two aptamers, WT-15 and SM-20, that disrupt the interactions between PAI-1 and heparin, as well as PAI-1 and vitronectin, without affecting the antiprotease activity of PAI-1. Furthermore, SM-20 prevented the detachment of breast cancer cells (MDA-MB-231) from vitronectin in the presence of PAI-1, resulting in an increase in cellular adhesion. Therefore, the PAI-1 aptamer SM-20 demonstrates therapeutic potential as an antimetastatic agent and could possibly be used as an adjuvant to traditional chemotherapy for breast cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78126/1/oli.2008.0177.pd

The role of rapid diagnostics in managing Ebola epidemics

Ebola emerged in West Africa around December 2013 and swept through Guinea, Sierra Leone and Liberia, giving rise to 27,748 confirmed, probable and suspected cases reported by 29 July 2015. Case diagnoses during the epidemic have relied on polymerase chain reaction-based tests. Owing to limited laboratory capacity and local transport infrastructure, the delays from sample collection to test results being available have often been 2 days or more. Point-of-care rapid diagnostic tests offer the potential to substantially reduce these delays. We review Ebola rapid diagnostic tests approved by the World Health Organization and those currently in development. Such rapid diagnostic tests could allow early triaging of patients, thereby reducing the potential for nosocomial transmission. In addition, despite the lower test accuracy, rapid diagnostic test-based diagnosis may be beneficial in some contexts because of the reduced time spent by uninfected individuals in health-care settings where they may be at increased risk of infection; this also frees up hospital beds. We use mathematical modelling to explore the potential benefits of diagnostic testing strategies involving rapid diagnostic tests alone and in combination with polymerase chain reaction testing. Our analysis indicates that the use of rapid diagnostic tests with sensitivity and specificity comparable with those currently under development always enhances control, whether evaluated at a health-care-unit or population level. If such tests had been available throughout the recent epidemic, we estimate, for Sierra Leone, that their use in combination with confirmatory polymerase chain-reaction testing might have reduced the scale of the epidemic by over a third