Procognia, Ltd.

Trading Systems Associates (ts-a) (israel) Limited

Einat Or

Ofer Markman

Eyal Klingbell

Amir Knipel

Assaf Peretz Oron

Shawn Melamed

Leonid Shvartser

Nava Zaarur

The invention provides a method for learning and identification of message types in a network in which the learning and identification is based solely upon information contained in messages in the network. In one embodiment, the method includes comparing a current message with one or more previously defined message structures and applying a comparison method in order to infer whether the structure of the current message conforms to any one of the previously defined message structures. The invention also provides a method for classifying a collection of messages input or output from a computational node in which the set of messages is portioned into subsets of similar messages, and a structure of the messages of each subset is characterized. The invention further provides a method for inferring causal relations between a message type input to a computational node in a network and message type output from the computational node in the network using one or more statistical tests. The invention further provides a system for monitoring transactions within a distributed information network. The system includes collection servers that execute a classification module and a correlation module. A management server analyzes data from the collection servers in order to determine a performance of the transactions in the system.

Method and system for transaction monitoring in a communication network

A system and method for characterizing carbohydrate polymers according to maps obtained from experimental data. Preferably, the data is obtained from a plurality of different types of experimental assays for characterizing the carbohydrate polymer. More preferably, at least one such assay involves binding a saccharide-binding agent to the carbohydrate polymer. One or more features of the carbohydrate polymer are then preferably characterized. These features are preferably derived from maps of the data obtained from assays involving the sample carbohydrate polymer. These maps are more preferably analyzed at a plurality of levels, with each level providing more abstract biological information. Most preferably, new types of experimental data are introduced to the process of analysis at each level, in order to support more complex analyses of the data. Optionally and most preferably, maps are eliminated at each level as being inconsistent with the experimental data. New maps are most preferably added at a higher level only if they are derived from the new experimental data which has been introduced at that level, in order to prevent a combinatorial explosion at successive levels of data analysis.

System and method for integrated analysis of data for characterizing carbohydrate polymers

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Tel Aviv, Israel

Einat Or