User-profile-based analytics for detecting cloud security breaches

While the growth of cloud-based technologies has benefited the society tremendously, it has also increased the surface area for cyber attacks. Given that cloud services are prevalent today, it is critical to devise systems that detect intrusions. One form of security breach in the cloud is when cyber-criminals compromise Virtual Machines (VMs) of unwitting users and, then, utilize user resources to run time-consuming, malicious, or illegal applications for their own benefit. This work proposes a method to detect unusual resource usage trends and alert the user and the administrator in real time. We experiment with three categories of methods: simple statistical techniques, unsupervised classification, and regression. So far, our approach successfully detects anomalous resource usage when experimenting with typical trends synthesized from published real-world web server logs and cluster traces. We observe the best results with unsupervised classification, which gives an average F1-score of 0.83 for web server logs and 0.95 for the cluster traces

Aberrant STYK1 expression in ovarian cancer tissues and cell lines

<p>Abstract</p> <p>Background</p> <p>Overexpression of <it>STYK1</it>, a putative serine/threonine and tyrosine receptor protein kinase has been shown to confer tumorigenicity and metastatic potential to normal cells injected into nude mice. Mutation of a tyrosine residue in the catalytic STYK1 domain attenuates the tumorigenic potential of tumor cells <it>in vivo</it>, collectively, suggesting an oncogenic role for STYK1.</p> <p>Methods</p> <p>To investigate the role of STYK1 expression in ovarian cancer, a panel of normal, benign, and ovarian cancer tissues was evaluated for STYK1 immunoreactivity using STYK1 antibodies. In addition, mRNA levels were measured by reverse transcription PCR and real-time PCR of estrogen receptors, GPR30 and STYK1 following treatment of ovarian cell lines with estrogen or G1, a GPR30 agonist, as well as western analysis.</p> <p>Results</p> <p>Our data showed higher expression of STYK1 in cancer tissues versus normal or benign. Only normal or benign, and one cancer tissue were STYK1-negative. Moreover, benign and ovarian cancer cell lines expressed <it>STYK1 </it>as determined by RT-PCR. Estradiol treatment of these cells resulted in up- and down-regulation of <it>STYK1 </it>despite estrogen receptor status; whereas G-1, a GPR30-specific agonist, increased STYK1 mRNA levels higher than that of estradiol.</p> <p>Conclusion</p> <p>We conclude that <it>STYK1 </it>is expressed in ovarian cancer and is regulated by estrogen through a GPR30 hormone-signaling pathway, to the exclusion of estrogen receptor-alpha.</p

Interactive Exploration of Chemical Space with Scaffold Hunter

The supporting information is composed of the following files: I. pyruvatekinasedata.zip The pyruvate kinase data set used for the analysis described in the referenced publication is contained in this file. The analysis is based on the Pyruvate Kinase Screen as published in PubChem under the assay ID 361. It contains all compounds checked in this screen together with the scaffold tree generated from it. Scaffold Hunter can be used to query the database and interactively display the scaffold tree. This file is a dump from a MySQL 5.1 database and was generated with MySQL Administrator 1.2.5. It can be restored with the same program. II. scaffoldhunter_profiles.zip Scaffold Hunter saves the user profiles either on the hard disk or in a database. The corresponding database schema is contained in this zip file. This schema must be contained in the MySQL database before Scaffold Hunter can be run. This file is a dump from a MySQL 5.1 database and was generated with MySQL Administrator 1.2.5. It can be restored with the same program. III. InstallationGuide_Databases.pdf This document describes the installation of a local MySQL database server and the graphical user interface MySQL Administrator. Restoration of the profiles and sample databases are also described. IV. run_ScaffoldHunter.bat Windows batch file to run Scaffold Hunter with 1024 MByte of Memory. V. run_ScaffoldTreeGenerator.bat Windows batch file to run ScaffoldTreeGenerator with 1024 MByte of Memory. VI. ScaffoldHunter_readme.txt Textfile with advice for the installation of Scaffold Hunter. VII. ScaffoldTreeGenerator_readme.txt Textfile with advice for the installation of ScaffoldTree Generator

Drug Repurposing: Far Beyond New Targets for Old Drugs

Repurposing drugs requires finding novel therapeutic indications compared to the ones for which they were already approved. This is an increasingly utilized strategy for finding novel medicines, one that capitalizes on previous investments while derisking clinical activities. This approach is of interest primarily because we continue to face significant gaps in the drug–target interactions matrix and to accumulate safety and efficacy data during clinical studies. Collecting and making publicly available as much data as possible on the target profile of drugs offer opportunities for drug repurposing, but may limit the commercial applications by patent applications. Certain clinical applications may be more feasible for repurposing than others because of marked differences in side effect tolerance. Other factors that ought to be considered when assessing drug repurposing opportunities include relevance to the disease in question and the intellectual property landscape. These activities go far beyond the identification of new targets for old drugs

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博士（文学）神戸大

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

ChemProt: a disease chemical biology database

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical–protein annotation resources, as well as disease-associated protein–protein interactions (PPIs). We assembled more than 700 000 unique chemicals with biological annotation for 30 578 proteins. We gathered over 2-million chemical–protein interactions, which were integrated in a quality scored human PPI network of 428 429 interactions. The PPI network layer allows for studying disease and tissue specificity through each protein complex. ChemProt can assist in the in silico evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram, an antidepressant, with osteogenesis imperfect and leukemia and bisphenol A, an endocrine disruptor, with certain types of cancer, respectively. The server can be accessed at http://www.cbs.dtu.dk/services/ChemProt/

Software for continuous game experiments

ConG is software for conducting economic experiments in continuous and discrete time. It allows experimenters with limited programming experience to create a variety of strategic environments featuring rich visual feedback in continuous time and over continuous action spaces, as well as in discrete time or over discrete action spaces. Simple, easily edited input files give the experimenter considerable flexibility in specifying the strategic environment and visual feedback. Source code is modular and allows researchers with programming skills to create novel strategic environments and displays

Optimality of mutation and selection in germinal centers

The population dynamics theory of B cells in a typical germinal center could play an important role in revealing how affinity maturation is achieved. However, the existing models encountered some conflicts with experiments. To resolve these conflicts, we present a coarse-grained model to calculate the B cell population development in affinity maturation, which allows a comprehensive analysis of its parameter space to look for optimal values of mutation rate, selection strength, and initial antibody-antigen binding level that maximize the affinity improvement. With these optimized parameters, the model is compatible with the experimental observations such as the ~100-fold affinity improvements, the number of mutations, the hypermutation rate, and the "all or none" phenomenon. Moreover, we study the reasons behind the optimal parameters. The optimal mutation rate, in agreement with the hypermutation rate in vivo, results from a tradeoff between accumulating enough beneficial mutations and avoiding too many deleterious or lethal mutations. The optimal selection strength evolves as a balance between the need for affinity improvement and the requirement to pass the population bottleneck. These findings point to the conclusion that germinal centers have been optimized by evolution to generate strong affinity antibodies effectively and rapidly. In addition, we study the enhancement of affinity improvement due to B cell migration between germinal centers. These results could enhance our understandings to the functions of germinal centers.Comment: 5 figures in main text, and 4 figures in Supplementary Informatio