System and Methods for Disease Module Detection

Patent metadata

Field	Value
Publication number	US-2016232279-A1
Application number	US-201415023582-A
Country	US
Kind code	A1
Filing date	Sep 19, 2014
Priority date	Sep 23, 2013
Publication date	Aug 11, 2016
Grant date	—

Abstract

The present disclosure discusses a system and method for disease module detection. More particularly, a protein network and list of seed proteins are provided to the system. The system iteratively selects one or more candidate proteins for inclusion in the list of seed proteins. The system calculates a connectivity factor for each of the connections of the candidate proteins to proteins listed as seed proteins. Responsive to the calculated connectivity factors the system adds one or more of the candidate proteins to list of seed proteins. At the end of the iterative process the list of seed proteins can be indicative of the disease module.

First claim

We claim:

1 . A method for generating a disease cluster, the method comprising:
receiving, by a connectivity module, an indication of a protein network, the protein network comprising a plurality of interconnected proteins; receiving, by the connectivity module, an indication of a plurality of seed proteins within the protein network that are associated with a disease; repeatedly, until a criterion is satisfied:
selecting, by the connectivity module, one or more candidate proteins;
calculating, by the connectivity module, a connectivity factor for each of the one or more candidate proteins;
updating the plurality of seed proteins to include one of the one or more candidate proteins responsive calculated connectivity factor for each of the one or more candidate proteins; and
providing, responsive to the satisfaction of the criterion, an indication of a portion of the plurality of interconnected proteins associated with the disease based at least in part on the updated plurality of seed proteins.

2 . The method of claim 1 , further comprising ranking, by the connectivity module, the connectivity factor for each of the one or more candidate proteins.

3 . The method of claim 1 , further comprising updating the plurality of seed proteins to include a candidate protein from the one or more candidate proteins with the lowest connectivity factor.

4 . The method of claim 1 , wherein the one or more candidate proteins are connected to at least one of the plurality of seed proteins in the protein network.

5 . The method of claim 4 , wherein the one or more candidate proteins are connected to the at least one of the plurality of seed proteins through an intermediate protein.

6 . The method of claim 1 , wherein the criterion is a predetermined number of iterations.

7 . The method of claim 1 , further comprising calculating a probability for each connection of the one or more candidate proteins that each connection is connected to one of the plurality of seed proteins.

8 . The method of claim 7 , further comprising summing, for each of the one or more candidate proteins, the probabilities that each connection of the one or more candidate proteins is connected to one of the plurality of seed proteins.

9 . The method of claim 1 , wherein the protein network is a human interactome.

10 . The method of claim 1 , further comprising updating the plurality of seed proteins to include two or more of the one or more candidate proteins.

11 . A system for generating a disease cluster, the system comprising:
a storage device configured to store:
an indication of a protein network, the protein network comprising a plurality of interconnected proteins; and
an indication of a plurality of seed proteins within the protein network that are associated with a disease;
a connectivity module configured to retrieve the indication of the protein network and the indication of the plurality of seed proteins from the storage device, the connectivity module further configured to:
select one or more candidate proteins;
calculate a connectivity factor for each of the one or more candidate proteins;
update the plurality of seed proteins to include one of the one or more candidate proteins responsive to the calculated connectivity factor for each of the one or more candidate proteins; and
provide an indication of a portion of the plurality of interconnected proteins associated with the disease based at least in part on the updated plurality of seed proteins.

12 . The system of claim 11 , wherein the connectivity module is further configured to rank the connectivity factor for each of the one or more candidate proteins.

13 . The system of claim 11 , wherein the connectivity module is further configured to update the plurality of seed proteins to include a candidate protein from the one or more candidate proteins with the lowest connectivity factor.

14 . The system of claim 11 , wherein the one or more candidate proteins are connected to at least one of the plurality of seed proteins in the protein network.

15 . The system of claim 14 , wherein the one or more candidate proteins are connected to the at least one of the plurality of seed proteins through an intermediate protein.

16 . The system of claim 11 , wherein the criterion is a predetermined number of iterations.

17 . The system of claim 11 , wherein the connectivity module is further configured to calculate a probability for each connection of the one or more candidate proteins that each connection is connected to one of the plurality of seed proteins.

18 . The system of claim 11 , wherein the connectivity module is further configured to sum, for each of the one or more candidate proteins, the probabilities that each connection of the one or more candidate proteins is connected to one of the plurality of seed proteins.

19 . The system of claim 11 , wherein the protein network is a human interactome.

20 . The system of claim 11 , wherein the connectivity module is further configured to update the plurality of seed proteins to include two or more of the one or more candidate proteins.

Assignees

• Univ Northeastern

Inventors

• Ghiassian Susan
• Menche Jorg
• Sharma Amitabh
• Barabasi Albert-Laszlo

Classifications

• C40B30/02

  Chemistry & Metallurgy · mapped topic

• G06F19/12 Primary

  Physics · mapped topic

• G16B5/20 Primary

  Probabilistic models · CPC title

• G16B35/00

  ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides · CPC title

• G16C20/60

  In silico combinatorial chemistry · CPC title