Lani Fang Wu

US Patent:

6556983, Apr 29, 2003

Filed:

Jan 12, 2000

Appl. No.:

09/481615

Inventors:

Steven Altschuler - Redmond WA
David V. Ingerman - Princeton NJ
Lani Wu - Redmond WA
Lei Zhao - Bellevue WA

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G06F 1700

US Classification:

706 55, 706 11, 706 20, 706 21

Abstract:

A pattern lattice data space as a framework for analyzing data, in which both schema-based and statistical analysis are accommodated, is defined. Ways to manage the size of the lattice structures in the pattern lattice data space are described. Utilities to classify or cluster, search (find similar data), or relate data using lattice fragments in the pattern lattice data space are also described. Superpattern cone or lattice generation function, which may be used by the classification and clustering functions, is also described. In addition, a subpattern cone or lattice generation process, which may be used by the search (find similar data) and data relating functions, is also described. Finally, a function to label, in readily understandable âpidginâ, categories which classify information, is also described.

US Patent:

6606613, Aug 12, 2003

Filed:

Jun 3, 1999

Appl. No.:

09/325168

Inventors:

Steven J. Altschuler - Redmond WA
David Ingerman - New York NY
Edward K. Jung - Bellevue WA
Greg Ridgeway - Bellevue WA
Lani F. Wu - Redmond WA

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G06N 302

US Classification:

706 21, 707 3, 707 6

Abstract:

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by âclusteringâ similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

US Patent:

6713257, Mar 30, 2004

Filed:

Feb 12, 2001

Appl. No.:

09/781814

Inventors:

Daniel D. Shoemaker - Bothell WA
Stewart Scherer - Moraga CA
Steven J. Altschuler - Redmond WA
Lani F. Wu - Redmond WA
Christopher D. Armour - Kirkland WA

Assignee:

Rosetta Inpharmatics LLC - Kirkland WA

International Classification:

C12Q 168

US Classification:

435 6, 536 231, 536 243, 702 19, 702 20

Abstract:

The invention relates to methods and systems (e. g. , computer systems and computer program products) for identifying and characterizing genes using microarrays. In particular, the invention provides for improved, robust methods for detecting genes through the use of microarrays to analyze the expression state of the genome. Genes which are expressed can be mapped to their respective positions in the genome, and the structure of such genes can be determined.

US Patent:

6778971, Aug 17, 2004

Filed:

Jun 3, 1999

Appl. No.:

09/325169

Inventors:

Steven J. Altschuler - Redmond WA
David Ingerman - New York NY
Edward K. Jung - Bellevue WA
Greg Ridgeway - Bellevue WA
Lani F. Wu - Redmond WA

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G06N 502

US Classification:

706 55, 700 29

Abstract:

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by âclusteringâ similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

US Patent:

6879952, Apr 12, 2005

Filed:

Apr 25, 2001

Appl. No.:

09/842416

Inventors:

Alejandro Acero - Bellevue WA, US
Steven J. Altschuler - Redmond WA, US
Lani Fang Wu - Redmond WA, US

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G10L019/12

US Classification:

704222, 704223, 381 941, 381 942, 381 66, 381 711

Abstract:

Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.

US Patent:

7047189, May 16, 2006

Filed:

Nov 18, 2004

Appl. No.:

10/992051

Inventors:

Alejandro Acero - Bellevue WA, US
Steven J. Altschuler - Redmond WA, US
Lani Fang Wu - Redmond WA, US

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G10L 19/12

US Classification:

704222, 704223, 381 941, 381 942, 381 66

Abstract:

Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.

US Patent:

20040161791, Aug 19, 2004

Filed:

Mar 29, 2004

Appl. No.:

10/813506

Inventors:

Daniel Shoemaker - Bothell WA, US
Stewart Scherer - Moraga CA, US
Steven Altschuler - Redmond WA, US
Lani Wu - Redmond WA, US
Christopher Armour - Kirkland WA, US

Assignee:

Rosetta Inpharmatics LLC.

International Classification:

C12Q001/68
C12M001/34

US Classification:

435/006000, 435/287200

Abstract:

The invention relates to methods and systems (e.g., computer systems and computer program products) for identifying and characterizing genes using microarrays. In particular, the invention provides for improved, robust methods for detecting genes through the use of microarrays to analyze the expression state of the genome. Genes which are expressed can be mapped to their respective positions in the genome, and the structure of such genes can be determined.

US Patent:

20060050946, Mar 9, 2006

Filed:

May 12, 2003

Appl. No.:

10/435827

Inventors:

Timothy Mitchison - Brookline MA, US
Steven Altschuler - Cambridge MA, US
Yan Feng - Andover MA, US
Thomas Mayer - Munchen, DE
Zachary Perlman - Boston MA, US
Michael Slack - La Mesa CA, US
Lani Wu - Cambridge MA, US

International Classification:

G06K 9/00

US Classification:

382133000

Abstract:

The present invention provides methods and systems for automated morphological analysis of cells. The inventive methods are particularly useful in the rapid analysis of cells required in a biological screen. Agents which cause a particular phenotype in the cells can be identified using the inventive quantitative morphometric analysis of cells. The data gathered using the inventive method can also be quantified and analyzed later for various trends and classifications. Characteristics of cells which can be determined using this method include number of nuclei, size of cell, size of nuclei, number of the centrosomes, shape of cells, size of centrosomes, perimeter of nucleus, shape of nucleus, pattern of staining, and degree of staining.