{BiQ} Analyzer {HiMod}: An Interactive Software Tool for High-throughput Locus-specific Analysis of 5-Methylcytosine and its Oxidized Derivatives

Recent data suggest important biological roles for oxidative modifications of methylated cytosines, specifically hydroxymethylation, formylation and carboxylation. Several assays are now available for profiling these DNA modifications genome-wide as well as in targeted, locus-specific settings. Here we present BiQ Analyzer HiMod, a user-friendly software tool for sequence alignment, quality control and initial analysis of locus-specific DNA modification data. The software supports four different assay types, and it leads the user from raw sequence reads to DNA modification statistics and publication-quality plots. BiQ Analyzer HiMod combines well-established graphical user interface of its predecessor tool, BiQ Analyzer HT, with new and extended analysis modes. BiQ Analyzer HiMod also includes updates of the analysis workspace, an intuitive interface, a custom vector graphics engine and support of additional input and output data formats. The tool is freely available as a stand-alone installation package from http://biq-analyzer-himod.bioinf.mpi-inf.mpg.de/

RPP: Automatic Proof of Relational Properties by Self-Composition

Self-composition provides a powerful theoretical approach to prove relational properties, i.e. properties relating several program executions, that has been applied to compare two runs of one or similar programs (in secure dataflow properties, code transformations, etc.). This tool demo paper presents RPP, an original implementation of self-composition for specification and verification of relational properties in C programs in the FRAMA-C platform. We consider a very general notion of relational properties invoking any finite number of function calls of possibly dissimilar functions with possible nested calls. The new tool allows the user to specify a relational property, to prove it in a completely automatic way using classic deductive verification, and to use it as a hypothesis in the proof of other properties that may rely on it

ARPA Whitepaper

We propose a secure computation solution for blockchain networks. The correctness of computation is verifiable even under malicious majority condition using information-theoretic Message Authentication Code (MAC), and the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty computation protocol and a layer2 solution, our privacy-preserving computation guarantees data security on blockchain, cryptographically, while reducing the heavy-lifting computation job to a few nodes. This breakthrough has several implications on the future of decentralized networks. First, secure computation can be used to support Private Smart Contracts, where consensus is reached without exposing the information in the public contract. Second, it enables data to be shared and used in trustless network, without disclosing the raw data during data-at-use, where data ownership and data usage is safely separated. Last but not least, computation and verification processes are separated, which can be perceived as computational sharding, this effectively makes the transaction processing speed linear to the number of participating nodes. Our objective is to deploy our secure computation network as an layer2 solution to any blockchain system. Smart Contracts\cite{smartcontract} will be used as bridge to link the blockchain and computation networks. Additionally, they will be used as verifier to ensure that outsourced computation is completed correctly. In order to achieve this, we first develop a general MPC network with advanced features, such as: 1) Secure Computation, 2) Off-chain Computation, 3) Verifiable Computation, and 4)Support dApps' needs like privacy-preserving data exchange

Secure Integration of Desktop Grids and Compute Clusters Based on Virtualization and Meta-Scheduling

Reducing the cost for business or scientific computations, is a commonly expressed goal in today’s companies. Using the available computers of local employees or the outsourcing of such computations are two obvious solutions to save money for additional hardware. Both possibilities exhibit security related disadvantages, since the deployed software and data can be copied or tampered if appropriate countermeasures are not taken. In this paper, an approach is presented to let a local desktop machines and remote cluster resources be securely combined into a singel Grid environment. Solutions to several problems in the areas of secure virtual networks, meta-scheduling and accessing cluster schedulers from desktop Grids are proposed

Network of the Day: Aggregating and Visualizing Entity Networks from Online Sources

This software demonstration paper presents a project on the interactive visualization of social media data. The data presentation fuses German Twitter data and a social relation network extracted from German online news. Such fusion allows for comparative analysis of the two types of media. Our system will additionally enable users to explore relationships between named entities, and to investigate events as they develop over time. Cooperative tagging of relationships is enabled through the active involvement of users. The system is available online for a broad user audience