# US 2014/0156235 A1 · Modeling multiple interactions between multiple loci

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- Number: US 2014/0156235 A1
- Document ID: US20140156235A1
- Status: Published application
- Kind: A1
- Application number: 13/705,738
- Filed: 2012-12-05
- Published: 2014-06-05
- Earliest claimed: 2012-12-05
- Assignees: International Business Machines Corporation
- Applicants: International Business Machines Corp
- Inventors: David C. Haws; Dan He; Laxmi P. Parida
- Web page: https://patentgrep.com/patent/US20140156235A1

## CPC

- G16B 5/00: ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
- G16B 20/20: Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
- G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY

## Abstract

Various embodiments generate a quantitative model of genetic effect. In one embodiment, a processor receives a set of loci of an entity. Each locus is associated with a contribution value to a given physical trait. A first set of interacting loci associated with a first interaction and at least a second set of interacting loci associated with at least a second interaction are identified. The first interaction type is associated with a first interaction model. The at least the second interaction is associated at least a second interaction model. A model of a quantitative value of the entity is generated based on at least the contribution value associated with each locus in the set of loci, a contribution value of the first interaction as defined by the first interaction model, and a contribution value of the second interaction as defined by the at least the second interaction model.

## Claims

### Claim 1

A computer implemented method for generating a quantitative model of genetic effect, the computer implemented method comprising:
receiving, by a processor, a set of loci of an entity, wherein each locus in the set of loci is associated with a contribution value to a given physical trait;
identifying, from the set of loci, a first set of interacting loci associated with a first interaction and at least a second set of interacting loci associated with at least a second interaction, wherein the first interaction is associated with a first interaction model, and wherein the at least the second interaction is associated at least a second interaction model;
generating a model of a quantitative value of the entity based on at least
the contribution value associated with each locus in the set of loci,
a contribution value of the first interaction as defined by the first interaction model, and
a contribution value of the at least the second interaction as defined by the at least the second interaction model.

### Claim 2 (depends on 1)

The computer implemented method of claim 1, wherein the model of the quantitative value is defined as a
V
j
:=
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β
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+
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{
i
1
,
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i
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}
=
A
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ℐ
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f
i
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(
x
i
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j
,
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,
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i
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where Vj is the model of the quantitative value, j is an entity, Variable j is the individual, i is a locus, N is a real number, βi is an impact scaling factor for locus i, xij is a contribution encoding of locus i, k is an integer identifying a number of interacting loci, I is a set of interacting loci, f is an interaction model, and iA is a set of loci A using the interaction model f.

### Claim 3 (depends on 1)

The computer implemented method of claim 1, further comprising:
identifying at least one of the first set of interacting loci and the at least the second set of interacting loci are from real data.

### Claim 4 (depends on 1)

The computer implemented method of claim 1, wherein the first set of interacting loci and the at least the second set of interacting loci are identified based on input received from a user.

### Claim 5 (depends on 1)

The computer implemented method of claim 1, further comprising:
determining that at least one of the first interaction model and the at least the second interaction model are associated with the first interaction and the at least the second interaction, respectively, based on real data.

### Claim 6 (depends on 1)

The computer implemented method of claim 1, further comprising:
receiving, from a user, at least one of
an association of the first interaction model with the first interaction, and
an association of the at least the second interaction model with the at least the second interaction.

### Claim at position 7

7-18. (canceled)