Fernando Martin Maroto

US Patent:

8200593, Jun 12, 2012

Filed:

Jul 20, 2009

Appl. No.:

12/460542

Inventors:

Marcos E. Guillen - Washington esq con Juan de Salazar, PY
Fernando M. Maroto - El Cerrito CA, US

Assignee:

Corticaldb Inc - San Francisco CA

International Classification:

G06E 1/00
G06E 3/00
G06F 15/18
G06G 7/00
G06N 3/04

US Classification:

706 27

Abstract:

A neural network simulation represents components of neurons by finite state machines, called sectors, implemented using look-up tables. Each sector has an internal state represented by a compressed history of data input to the sector and is factorized into distinct historical time intervals of the data input. The compressed history of data input to the sector may be computed by compressing the data input to the sector during a time interval, storing the compressed history of data input to the sector in memory, and computing from the stored compressed history of data input to the sector the data output from the sector.

US Patent:

20050131647, Jun 16, 2005

Filed:

Dec 16, 2003

Appl. No.:

10/738667

Inventors:

Fernando Maroto - Palo Alto CA, US

International Classification:

G06F019/00
G01N033/48
G01N033/50

US Classification:

702019000

Abstract:

Computer programs and methods for defining a misidentification probability for an experimental protein divisible into experimental peptides. The invention receives data representing a set of matches of experimental peptides to reference peptides that can be derived from a protein in a database of proteins; calculates a probability of observing by chance, in a search of the database of proteins, a set of matches equivalent to or better than the represented set of matches; and defines the misidentification probability using the probability of observing by chance a set of matches equivalent to or better than the represented set of matches.

US Patent:

20060089807, Apr 27, 2006

Filed:

Mar 11, 2003

Appl. No.:

10/512606

Inventors:

Fernando Maroto - Santa Clara CA, US

Assignee:

Thermo Finnigan, LLC - San Jose CA

International Classification:

G06F 19/00

US Classification:

702019000

Abstract:

Methods, systems and apparatus implement techniques for identifying modifications in polypeptides. A set of candidate sequences is identified that includes sequence information potentially corresponding to an unmodified variant of the polypeptide. Peptides derived from the polypeptide are sequenced to identify sequence tags. The sequence tags are compared with sequence information for the set of candidate sequences to identify a candidate sequence containing the sequence tags. For each such sequence tag, the difference between at least one subsequence mass of the corresponding peptide and at least one subsequence mass of the identified candidate sequence is calculated. The candidate sequences containing the sequence tags can be identified by searching a reduced database constructed based on the identified set of candidate sequences.