Accelrys Software, Inc.

Nestec S.a.

Thomas Stockfisch

Sharat Singh

Fred Princen

Steven Lockton

Lisa Croner

Frederick A Fletcher

Lisa J Croner

The present invention provides methods and systems to predict and diagnose inflammatory bowel disease (IBD) and subtypes such as ulcerative colitis (UC) and Crohn's disease (CD) by detecting the presence, absence, level, and/or genotype of one or more sero-genetic-inflammation markers. Advantageously, with the present invention, it is possible to provide a diagnosis of IBD versus non-IBD, to rule out IBD that is inconclusive for CD and UC, and to differentiate between CD and UC with increased accuracy.

Methods for improving inflammatory bowel disease diagnosis

Systems and methods are described for forming a decision tree by considering multiple possible alternative tests or thresholds as well as the possible alternative branches from each test or threshold. This method of making decision trees may be referred to as 'look-ahead' or 'chart-ahead' recursive partitioning because tests or thresholds can be selected not only for their own ability to divide items into different classes, but also for the ability of future tests or thresholds, enabled by the present tests or thresholds, to further divide items into classes. In preferred embodiments, the method of making the decision tree includes generating clusters of items having similar descriptors and properties, and then evaluating various tests or thresholds for their ability to isolate clusters. Also disclosed are methods of using such decision trees, particularly for the purpose of predicting the unknown properties of molecules.

Chart-ahead method for decision tree construction

This application describes systems and methods of forming a decision tree that simultaneously classifies multiple properties of items, and systems and methods of using the decision tree to simultaneously predicting multiple unknown properties of an item. In one embodiment, the decision tree has a top generic layer of nodes that are generic to all properties, a middle K layer of nodes that split on a property type descriptor K, and a bottom specific layer of nodes that are specific to some properties. In addition to simultaneously predicting multiple properties of new items, the decision tree may also aid users in uncovering relationships between properties and in determining what descriptors may represent a generic quality, and what descriptors may represent property-specific activity.

Methods and systems of classifying multiple properties simultaneously using a decision tree

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Escondido, CA, United States of America

Thomas Stockfisch