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Unclassified software tools | Protein interaction data analysis

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Aims at facilitating the use of BioCyc, a collection of Pathway/Genome Databases (PGDBs). Cyclone can read and write PGDBs, and can write its own data in the CycloneML format. It interfaces easily with Java software including the Eclipse IDE for Hibernate Query Language (HQL) edition, the Jung API for graph algorithms or Cytoscape for graph visualization. The Cyclone API allows the extraction of data from BioCyc in order to build biological networks. The resulting networks can be manipulated as graphs using the Jung graph library, bundled with the Cyclone installation package.
OCSANA / Optimal Combinations of Interventions from Network Analysis
Identifies and prioritizes optimal and minimal combinations of interventions to disrupt the paths between source nodes and target nodes. OCSANA seeks to additionally minimize the side effects that a combination of interventions can cause on specified off-target nodes. With the crucial ability to cope with very large networks, OCSANA includes an exact solution and a novel selective enumeration approach for the combinatorial interventions’ problem.
GEB052 model / Glucocorticoid receptor model by Emyr Bakker
Provides a Boolean model for the glucocorticoid receptor (GR) interaction network similar to the p53 interactomes. The GEB052 model consists of 52 nodes connected by 241 logical interactions, and has 64 two-step feedback loops within the model. In this process, nodes represent genes/proteins or inputs (glucocorticoid)/outputs (cell death and inflammation). It provides accurate predictions and indicates potential routes through which glucocorticoid resistance may arise.
Creates PyMOL hydrogen bonds (H-bonds) interaction views from Hbind tables. HbindViz is a program that permits users to visualize hydrogen bond interactions detected by Hbind, a tool that defines intermolecular H-bonds by donor/acceptor chemistry and geometric constraints. The software consists of three steps: (1) generation of an Hbind interaction table, (2) creation of the PyMOL visualization commands, and (3) execution of the generated PyMOL commands to visualize hydrogen-bonds.
openBEB / open Biological Experiment Browser
Allows data acquisition, coordination, synchronization and annotation with database solutions. openBEB is organized in two parts: first a static core program that handles data and metadata, and second a plug-in manager for the experiment-specific functionalities. It contains also a local repository to organize raw-data, metadata and cache files. This software can be used as a bridge between biological experiments, annotation and synchronization with databases.
A technique for reducing overfitting in large neural nets. Dropout provides a way of approximately combining exponentially many different neural network architectures efficiently. The term “dropout” refers to dropping out units (hidden and visible) in a neural network. By dropping a unit out, this unit is temporarily removing it from the network, along with all its incoming and outgoing connections. This technique was found to improve the performance of neural nets in a wide variety of application domains including object classification, digit recognition, speech recognition, document classification and analysis of computational biology data. This suggests that dropout is a general technique and is not specific to any domain. Methods that use dropout achieve state-of-the-art results on SVHN, ImageNet, CIFAR-100 and MNIST.
iENA / individual-specific ENA
Identifies the pre-disease state or the tipping point during disease progression. iENA extracts the high-order statistics and dynamical information from biological data. This tool utilizes individual samples for the prediction of disease states by exploring differential edge-network based on differential expression, variance and covariance analysis. It can be used for clinical panel assay and it is able to predict the tipping points or critical transitions of diseases including cancer.
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