Software developed by the Donald Lab

CRANS

Name of program: CRANS (Project Information)

Code authors: Ryan Lilien, Chris Bailey-Kellogg

Copyright: Copyright © 2004, Ryan H. Lilien, Chris Bailey-Kellogg, Amy C. Anderson, and Bruce R. Donald.

Description: A Subgroup Algorithm to Identify Cross-Rotation Peaks Consistent with Non-Crystallographic Symmetry. An efficient quaternion-based algorithm is presented for analyzing peaks from a cross-rotation function to identify model orientations consistent with proper non-crystallographic symmetry (NCS), and to generate proper NCS-consistent orientations missing from the list of cross-rotation peaks. Our algorithm, CRANS, analyzes the rotation differences between each pair of cross-rotation peaks to identify finite subgroups. Sets of rotation differences satisfying the subgroup axioms correspond to orientations compatible with the correct proper NCS.

Distribution Information: The CRANS distribution contains a compiled java .jar file as well as the complete java source. CRANS is written entirely in Java.

References:

1. Ryan H. Lilien, Chris Bailey-Kellogg, Amy C. Anderson, and Bruce R. Donald. "A Subgroup Algorithm to Identify Cross-Rotation Peaks Consistent with Non-Crystallographic Symmetry." Acta Crystallographica D, 2004; 60: 1057-67. [PDF]

Copyright information: Software is made available through the Gnu Public License. If you use or publish any results derived from the use of this program please cite the reference above.

Download Tar file: CRANS_Dist.tar.gz

Exact-2NH

Name of program: Exact-2NH (Project Information)

Code author: Lincong Wang

Copyright: Copyright © 2004, Lincong Wang and Bruce R. Donald.

Release Note: (September 2009). Please note that this code archive represents the software code for our Journal Biomolecular NMR 2004 paper. A significantly improved and enhanced code distribution, called RDC-PANDA for our Journal Biomolecular NMR 2009 paper is now released, open-source, here. For example, RDC-PANDA incorporates significant new functionality and many software improvements.

Description of the (older) Exact-2NH: Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a systematic search algorithm for determining protein backbone structure. The algorithm uses a quartic equation for computing the direction of an internuclear vector from residual dipolar couplings (RDCs) measured in two aligning media, and also uses two simple trigonometric equations for computing the backbone angles from two backbone vectors in consecutive peptide planes. Building upon these exact solutions, the algorithm determines the protein backbone substructure consisting of alpha-helices and beta-sheets. The algorithm employs a systematic search technique to refine the conformation of both alpha-helices and beta-sheets and to determine their orientations using exclusively the angular restraints from RDCs. The backbone substructure is determined with the addition of very sparse distance restraints between pairs of alpha-helices and beta-sheets and is refined by the systematic search. The algorithm has been demonstrated on the protein human ubiquitin using only backboneNH RDCs, plus twelve hydrogen bonds and four NOE distance restraints. The algorithm requires, as its input, backbone resonance assignments, the identification of alpha-helices and beta-sheets as well as sparse NOE distance and hydrogen bond restraints.

Distribution Information:The software distribution contains a compiled java .class files as well as the complete java source. The software is written entirely in Java.

References:

1. Lincong Wang and Bruce R. Donald. "Exact Solutions for Internuclear Vectors and Backbone Dihedral Angles from NH Residual Dipolar Couplings in Two Media, and Their Application in a Systematic Search Algorithm for Determining Protein Backbone Structure." Journal of Biomolecular NMR, 2004; 29: 223-242. [PDF]

Copyright information: Software is made available through the Gnu Public License. If you use or publish any results derived from the use of this program please cite the reference above.

Download Tar file: Please use RDC-PANDA, which has replaced Exact-2NH.

Please see the special Release Note above regarding the availability of a new and improved (2009) version of the software. The TAR file for the old (2004) version is: exact-systematic-2media-NH.tar.gz

MTC

Name of program: MTC

Code author: Chris Langmead

Copyright: Copyright (c) 2004, Chris Langmead and Bruce R. Donald.

Description: Mean Tensor Consistency (MTC)
The difference between experimentally-observed and back-computed RDCs, as measured by the similarity and consistency of alignment tensors, can be useful to assess the overall correctness of an ensemble of resonance assignments. One can, in principle, distinguish between a correct set of assignments and an incorrect one using mean tensor consistency. See pages 125-127 in reference 1 below.

Mean tensor consistency U is correlated with the number of correct assignments. The correlation between tensor consistency and correctness of assignments suggests a new strategy for performing resonance assignment wherein the goal is to maximize U.

Pairwise tensor consistency is measured using the technique of Yan et al. (reference 2 below).

Distribution Information: The MTC distribution contains a set of Matlab (Mathworks Inc, Natick, MA) functions. MTC is written entirely in Matlab.

References:

1. C. Langmead, and B. R. Donald. An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments (with C. Langmead). Journal of Biomolecular NMR, 2004; 29(2): 111-138. [PDF]
2. A Probability-Based Similarity Measure for Saupe Alignment Tensors with Applications to Residual Dipolar Couplings in NMR Structural Biology (with A. Yan and C. Langmead). The International Journal of Robotics Research Special Issue on Robotics Techniques Applied to Computational Biology, 2005; 29(2-3): 165-182. [PDF]

Copyright information: Software is made available through the Gnu Public License.
If you use or publish any results derived from the use of these programs please cite the reference above.

Download Tar file: MTC.tar.gz

NVR/HD/GD

Name of program: NVR/HD/GD

Code author: Chris Langmead

Copyright: Copyright (c) 2004, Chris Langmead & Bruce R. Donald.

Description: Nuclear Vector Replacement and Homology Detection.
NVR: NVR (Nuclear Vector Replacement) is an algorithm for high-throughput NMR resonance assignment for a protein of known structure, or of an homologous structure. Our algorithm performs Nuclear Vector Replacement by Expectation/Maximization (EM) to compute assignments. NVR correlates experimentally-measured NH residual dipolar couplings (RDCs) and chemical shifts to a given a priori whole-protein 3D structural model. The algorithm requires only uniform 15N-labelling of the protein, and processes unassigned H/D exchange HSQC spectra, RDCs, and sparse HN-HN NOEs.

GD: GD is an algorithm for detecting 3D structural homologies from sparse, unassigned protein NMR data. GD correlates experimentally-measured backbone HN-15N bond orientations with the backbone HN-15N bonds in a putative homologous structure using Kullback-Leibler distance, as well as other available information about the target protein.

HD: HD is also an algorithm for detecting 3D structural homologies from sparse, unassigned protein NMR data. In contrast to GD, HD identifies 3D models in a protein structural database whose geometries best fit the unassigned experimental NMR data using an Expectation/Maximization (EM) framework. The HD method can also be used to confirm or refute structural predictions made by other techniques such as protein threading or homology modelling.

Distribution Information: The NVR/GD/HD distribution contains a set of Matlab (Mathworks Inc, Natick, MA) functions. NVR/GD/HD is written entirely in Matlab.

References:

1. C. Langmead, and B. R. Donald. An Expectation/Maximization Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments (with C. Langmead). Journal of Biomolecular NMR, 2004; 29(2): 111-138. [PDF]
2. C. Langmead, R. H. Lilien, T. Yan, L. Wang, and B. R. Donald. A Polynomial-Time Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments," (with C. Langmead, A. Yan, R. Lilien, and L. Wang), Proc. The Seventh Annual International Conference on Research in Computational Molecular Biology (RECOMB), Berlin (2003) pp. 176-187. [PDF]
3. C. Langmead, R. H. Lilien, T. Yan, L. Wang, and B. R. Donald. A Polynomial-Time Nuclear Vector Replacement Algorithm for Automated NMR Resonance Assignments, Journal of Computational Biology, 2004; 11(2-3): 277-298. [PDF]
4. C. Langmead, and B. R. Donald. 3D Structural Homology Detection via Unassigned Residual Dipolar Couplings," (with C. Langmead) Proc. IEEE Computational Systems Bioinformatics Conference (CSB), Stanford University, Palo Alto (August 10, 2003) pp. 209-217. ISBN 0-7695-2000-6. [PDF]
5. C. Langmead, and B. R. Donald. High-Throughput 3D Structural Homology Detection via NMR Resonance Assignment (with C. Langmead). The IEEE Computational Systems Bioinformatics Conference (CSB), Stanford CA, (August, 2004) pp. 278-289. [PDF]

Copyright information: Software is made available through the Gnu Public License.
If you use or publish any results derived from the use of these programs please cite the references (NVR: refs. 1,2; GD: ref. 4, HD: ref. 5) above.

Download Tar file: nvr.tgz

Q5

Name of program: Q5 (Project Information)

Code authors: Ryan Lilien, Hany Farid

Copyright:Copyright (c) 2002, Ryan H. Lilien, Hany Farid, and Bruce R. Donald.

Description: Probabilistic Disease Classification of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum. The algorithm employs Principal Components Analysis (PCA) followed by Linear Discriminant Analysis (LDA) on whole spectrum Surface-Enhanced Laser Desorption/Ionization Time of Flight (SELDI-TOF) Mass Spectrometry (MS) data. Q5 is a closed-form, exact solution to the problem of classification of complete mass spectra of a complex protein mixture. Q5 employs a probabilistic classification algorithm built upon a dimension-reduced linear discriminant analysis.

Distribution Information: The Q5 distribution contains a set of Matlab (Mathworks Inc, Natick, MA) functions. Q5 is written entirely in Matlab.

References:

1. Ryan H. Lilien, Hany Farid, and Bruce R. Donald. "Probabilistic Disease Classification of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum." Journal of Computational Biology, 2003; 10(6): 925-946. [PDF]

Copyright information: Software is made available through the Gnu Public License.
If you use or publish any results derived from the use of this program please cite the reference above.

Download Tar file: Q5_Dist.tar.gz

Rage/Enrage

Name of program: RAGE/ENRAGE

Code author: Chris Langmead

Copyright: Copyright (c) 2002, Chris Langmead and Bruce R. Donald.

Description: Analysis of Genome-Wide Expression Patterns from Microarray Hybridization Data.
RAGE: A model-based analysis technique for extracting and characterizing rhythmic expression profiles from genome-wide DNA microarray hybridization data. The algorithm, implemented in a program called RAGE (Rhythmic Analysis of Gene Expression), decouples the problems of estimating a pattern's periodicity and phase. Our algorithm is linear-time in frequency and phase resolution, an improvement over previous quadratic-time approaches. Unlike previous approaches, RAGE uses a true distance metric for measuring expression profile similarity, based on the Hausdorff distance.

ENRAGE: A maximum entropy-based analysis technique for extracting and characterizing rhythmic expression profiles from DNA microarray hybridization data. The algorithm, implemented in a program called ENRAGE (Entropy-based Rhythmic Analysis of Gene Expression), treats the task of estimating an expression profile's periodicity and phase as a simultaneous bicriterion optimization problem. Specifically, a frequency domain spectrum is reconstructed from a time-series of gene expression data, subject to two constraints: (a) the likelihood of the spectrum and (b) the Shannon entropy of the reconstructed spectrum. Our algorithm is optimal, running in linear time in the number of expression profiles.

Distribution Information: The RAGE/ENRAGE distribution contains a set of Matlab (Mathworks Inc, Natick, MA) functions. RAGE/ENRAGE is written entirely in Matlab.

References:

1. C. Langmead, T. Yan, C. R. McClung, and B. R. Donald "Phase-Independent Rhythmic Analysis of Genome-Wide Expression Patterns", Journal of Computational Biology, 2003; 10(3-4): 521-536. [PDF]
2. C. Langmead, T. Yan, C. R. McClung, and B. R. Donald Proc. The Sixth Annual International Conference on Research in Computational Molecular Biology (RECOMB), Washington DC (April18-21, 2002). pp. 205-215. [PDF]
3. "A Maximum Entropy Algorithm for Rhythmic Analysis of Genome-Wide Expression Patterns," C. J. Langmead, C.R. McClung and B. R. Donald, Proc. IEEE Computer Society Bioinformatics Conference (CSB 2002), Stanford University, CA (August, 2002) pp. 237-245. [PDF]

Copyright information: Software is made available through the Gnu Public License.
If you use or publish any results derived from the use of these programs please cite the three references above.

Download Tar file: ENRAGEandRAGE.tar.gz