Methods, systems, and software for identifying functional...

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Biological or biochemical

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C702S020000

Reexamination Certificate

active

07747391

ABSTRACT:
The present invention generally relates to methods of rapidly and efficiently searching biologically-related data space. More specifically, the invention includes methods of identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The invention also provides methods of modeling sequence-activity relationships. As many of the methods are computer-implemented, the invention additionally provides digital systems and software for performing these methods.

REFERENCES:
patent: 6537776 (2003-03-01), Short
patent: 6605449 (2003-08-01), Short
patent: 7315786 (2008-01-01), Dahiyat et al.
patent: 2001/0051855 (2001-12-01), Wang et al.
patent: 2002/0045175 (2002-04-01), Wang et al.
patent: 2002/0048772 (2002-04-01), Dahiyat et al.
patent: 2002/0155460 (2002-10-01), Schellenberger et al.
patent: 2003/0032059 (2003-02-01), Wang et al.
patent: 2004/0072245 (2004-04-01), Gustafsson et al.
patent: 2004/0161796 (2004-08-01), Gustafsson et al.
patent: 2005/0084907 (2005-04-01), Fox
patent: 2006/0205003 (2006-09-01), Gustafsson et al.
patent: 2007/0239364 (2007-10-01), Fox
patent: 2008/0132416 (2008-06-01), Fox
patent: 2008/0133143 (2008-06-01), Gustafsson et al.
patent: 2008/0147369 (2008-06-01), Fox
patent: 2008/0220990 (2008-09-01), Fox
patent: WO01/59066 (2001-08-01), None
patent: WO01/61344 (2001-08-01), None
patent: WO03/055978 (2003-07-01), None
patent: WO03/075129 (2003-08-01), None
patent: WO2006/002267 (2006-01-01), None
Moore et al., “Computational Challenges in Combinatorial Library Design in Protein Engineering,” AIChE Journal, vol. 50, No. 2, Feb. 2004, pp. 262-272.
Hu et al., “Developing Optimal Non-Linear Scoring Function for Protein Design,” Bioinformatics, vol. 20, Issue 17, 2004, pp. 3080-3098.
Richard Fox, “Directed Molecular Evolution by Machine Learning and the Influence of Nonlinear Interactions,” Journal of Theoretical Biology 234, 2005, pp. 187-199.
Zhang et al., “Genome Shuffling Leads to Rapid Phenotypic Improvement in Bacteria,” Nature, vol. 415, Feb. 2002, pp. 644-646.
PCT Search Report for Int'l Application No. PCT/US2005/022119, dated Nov. 24, 2005.
PCT Written Opinion for Int'l Application No. PCT/US2005/022119, dated Nov. 24, 2005.
Voigt et al., “Rational Evolutionary Design: The Theory of In Vitro Protein Evolution,” Advances in Protein Chemistry, Academic Press, vol. 55, pp. 79-160, 2001.
Dahiyat et al., “De Novo Protein Design: Fully Automated Sequence Selection,” Science, American Assoc fro the Advancement of Science, vol. 278, No. 5335, p. 82-87, 1997.
Fox et al., “Optimizing the Search Algorithm for Protein Engineering by Directed Evolution,” Protein Engineering, Oxford Univ Press, vol. 16, No. 8, pp. 589-597, 2003.
Supplemental Partial EPO Search Report for Int'l Application No. PCT/US03/06551, dated Nov. 28, 2005, 6 pages.
International Search Report for Int'l Application No. PCT/US03/06551, Completed Sep. 5, 2003, 4 pages.
Ness et al., “Synthetic Shuffling Expands Functional Protein Diversity by Allowing Amino Acids to Recombine Independently,” Nature Biotechnology, vol. 20, 1251-1255 (2002).
Kolkman et al., “Directed Evolution of Proteins by Exon Shuffling,” Nature Biotechnology, vol. 19, 423-428 (2001).
Voigt et al., “Computationally Focusing the Directed Evolution of Proteins,” Journal of Cellular Biochemistry Supplement 37:58-63 (2001).
Goodacre et al., “Detection of the Dipicolinic Acid Biomarker inBacillusSpores Using Curie-Point Pyrolysis Mass Spectrometry and Fourier Transform Infrared Spectroscopy,”Anal. Chem. (2000), 72, 119-127.
Geladi et al., “Partial Least-Squares Regression: A Tutorial,”Analytica Chimica Acta, 185 (1986) 1-17.
The GMAX: printed from website http://www.abergc.com, prior to Jul. 21, 2003, 3 pages.
Steve R. Gunn, “Support Vector Machines for Classification and Regression,” Technical Report, Department of Electronics and Computer Science, University of Southampton, 1998, 57 Pages.
U.S. Office Action mailed Mar. 13, 2006, from U.S. Appl. No. 10/379,378.
U.S. Office Action mailed Jan. 27, 2006, from U.S. Appl. No. 10/386,903.
Skibinsky, “Office Action for U.S. Appl. No. 10/379,378” mailed Sep. 28, 2006.
Eroshkin et al., “PROANAL version 2: Multifunctional Program for Analysis of Multiple Protein Sequence Alignments and for Studying the Structure-Activity Relationships in Protein Families,” Comput. Appl. Biosci., vol. 11, No. 1, pp. 39-44, 1995.
Eroshkin et al., “Algortihm and Computer Program Pro—Anal for Analysis of Relationship Between Structure and Activity in a Family of Proteins or Peptides,” Comput. Appl. Biosci., vol. 9, No. 5, pp. 491-497, 1993.
Ivanisenko,V.A. and Eroshkin,A.M, “Search for Sites With Functionally Important Substitutions in Sets of Related or Mutant Protein,” Mol. Biol. (Moskow), 31, pp. 749-755, 1997.
Berglund et al. (1997) “INLR, Implicit Non-Linear Latent Variable Regression,”Journal of Chemometrics, 11:141-156.
Cho et al., (1998) “Rational Combinatorial Library Design. 2. Rational Design of Targeted Combinatorial Peptide Libraries Using Chemical Similarity Probe and the Inverse QSAR Approachcs,”J. Chem. Inf. Comput. Sci. 38(2):259-268.
Dahiyat et al., (1996) “Protein Design Automation,”Protein Science5:895-903.
Ginalski et al., (2005)“Practical Lessons From Protein Structure Prediction,”Nucleic Acids Research, 33( 6):1874-1891.
Gribskov, et al. (Jul. 1987) “Profile analysis: Detection of distantly related proteins”Proc. Natl. Acad. Sci. USA, Biochemistry84:4355-4358.
Hellberg et al., (1987) “Peptide Quantitative Structure-Activity Relationships, a Multivariate Approach,” Research Group for Chemometrics, Umca University, S-901 87 Umca, Sweden. Received Mar. 3, 1986,Journal of Medicinal Chemistry, 30(7):1126-1135.
Krogh, Anders (1998) “An Introduction to Hidden Markov Models for Biological Sequences,”Computational Methods in Molecular Biology, edited by S.L. Salzberg, D.B. Searls and S. Kasif, pp. 45-63.
International Preliminary Report on Patentability dated Jun. 25, 2007 issued in PCT/US03/06551.
US Office Action dated Apr. 18, 2007 issued in U.S. Appl. No. 10/379,378.
US Office Action dated Feb. 21, 2008 issued in U.S. Appl. No. 10/379,378..
US Final Office Action dated Sep. 17, 2008 issued in U.S. Appl. No. 10/379,378.
US Final Office Action (Supplementary) dated Oct. 15, 2008 issued in U.S. Appl. No. 10/379,378.
US Office Action (Advisory Action) dated Mar. 2, 2009 issued in U.S. Appl. No. 10/379,378.
US Office Action dated Mar. 13, 2007 issued in U.S. Appl. No. 10/874,802.
Hellberg et al., “The Prediction of Bradykinin Potentiating Potency of Pentapeptides. An Example of a Peptide Quantitative Structure-Activity Relationship,” Acia Chemica Scandinaviea B 40, pp. 135-140, 1988.
Bucht et al., “Optimising the Signal Peptide for Glycosyl Phosphatidylinositol Modification of Human Acetylcholinesterase Using Mutational Analysis and Peptide-Quantitative Structure-Activity Relationships,” Biochimica et Biophysica Acta 1431, pp. 471-482, 1999.
Sandberg et al., “Engineering Multiple Properties of a Protein by Combinatorial Mutagenesis,” Proc. Natl. Acad. Sci. USA, vol. 90, pp. 8367-8371, Sep. 1993.
Wrede et al., “Peptide Design Aided by Neural Networks: Biological Activity of Artificial Signal Peptidase I Cleavage Sites,” Biochemistry, 37, pp. 3588-3593, 1998.
Jill Damborsky, “Quantitative Structure-Function and Structure-Stability Relationships of Purposely Modified Proteins,” Protein Engineering, vol. 11, No. 1, pp. 21-30, 1998.
Hellberg, et al., “Peptide Quantitative Structure—Activity Relationships, a Multivariate Approach,” J. Med Chem, 30: pp. 1126-1195, 1987.
Sa

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Methods, systems, and software for identifying functional... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Methods, systems, and software for identifying functional..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Methods, systems, and software for identifying functional... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-4245397

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.