Module Hierarchy

• csb: CSB is a high-level, object-oriented library used to solve problems in the field of Computational Structural Biology.
  • csb.apps: Root package for all executable CSB client programs.
    • csb.apps.bfit: Python application for robust structure superposition of two structures.
    • csb.apps.bfite: Python application for robust structure superposition of an ensemble of structures.
    • csb.apps.buildhmm: Build an HMM from a FASTA sequence.
    • csb.apps.csfrag: CSfrag: build a dynamic library of analogous fragments, given a list of assigned chemical shifts.
    • csb.apps.embd: Sharpening of EM maps by non-negative blind deconvolution.
    • csb.apps.helloworld: This is a CSB HelloWorld dummy application.
    • csb.apps.hhfrag: HHfrag: build a dynamic variable-length fragment library for protein structure prediction with Rosetta AbInitio.
    • csb.apps.hhsearch: Python bindings for the HHsearch program.
    • csb.apps.precision: Measure the precision and coverage of a fragment library stored in Rosetta NNmake format.
    • csb.apps.promix: ProMix: Take a protein structure ensemble and find a mixture of rigid segments or a mixture of conformers.
  • csb.bio: Core bioinformatics abstractions and I/O.
    • csb.bio.fragments: APIs for working with protein structure fragments and libraries.
      • csb.bio.fragments.rosetta: Rosetta fragment libraries.
    • csb.bio.hmm: HHpred and Hidden Markov Model APIs.
      • csb.bio.hmm.pseudocounts
    • csb.bio.io: I/O for various biological file formats.
      • csb.bio.io.clans: Classes for parsing/manipulating/writing CLANS (by Tancred Frickey) files
      • csb.bio.io.cs: Simple NMR STAR chemical shift readers.
      • csb.bio.io.dssp: DSSP Parser
      • csb.bio.io.fasta: FASTA format sequence I/O.
      • csb.bio.io.hhpred: HHpred-related format parsers.
      • csb.bio.io.mrc: Cryo-EM density map I/O
      • csb.bio.io.noe: Simple XEASY and Sparky peak list parsers.
      • csb.bio.io.procheck: Procheck parser
      • csb.bio.io.psipred: PSIPRED Parser
      • csb.bio.io.svg: Build SVG diagrams from various csb objects.
      • csb.bio.io.vasco: VASCO Chemical Shift format parser.
      • csb.bio.io.whatif: Simple WhatIf/WhatCheck Summary parser
      • csb.bio.io.wwpdb: PDB structure parsers, format builders and database providers.
    • csb.bio.nmr: NMR related objects.
    • csb.bio.sequence: Sequence and sequence alignment APIs.
      • csb.bio.sequence.alignment: Collection of sequence alignment algorithms.
    • csb.bio.structure: 3D and secondary structure APIs.
    • csb.bio.utils: Computational utility functions.
  • csb.build: CSB build related tools and programs.
  • csb.core: Generic containers, data structures and language extensions.
  • csb.io: Generic I/O utility objects.
    • csb.io.plots: Plotting facilities, based on Python's MPL library.
    • csb.io.tsv: Read, query and update textual tables via flexible SQL interface.
  • csb.numeric: Low level numeric / math utility functions.
    • csb.numeric.integrators: provides various integration schemes and an abstract gradient class.
  • csb.statistics: Statistics root package.
    • csb.statistics.ars: Adaptive Rejection Sampling (ARS)
    • csb.statistics.maxent: A Maximum-Entropy model for backbone torsion angles.
    • csb.statistics.mixtures: Mixture models for multi-dimensional data.
    • csb.statistics.pdf: Probability density functions.
      • csb.statistics.pdf.parameterized: Probability density functions with support for shared and computed parameters.
    • csb.statistics.rand: Random number generators
    • csb.statistics.samplers: Defines abstract samplers.
      • csb.statistics.samplers.mc: Abstract Monte Carlo samplers.
        • csb.statistics.samplers.mc.multichain: Implements several extended-ensemble Monte Carlo sampling algorithms.
        • csb.statistics.samplers.mc.neqsteppropagator: Propagator class employing stepwise trajectories as used in the NCMC algorithm (Nilmeier et al., "Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation", PNAS 2011)
        • csb.statistics.samplers.mc.propagators: Provides various deterministic and stochastic propagators.
        • csb.statistics.samplers.mc.singlechain: Various Monte Carlo equilibrium sampling algorithms, which simulate only one Markov chain.
    • csb.statistics.scalemixture: Approximation of a distribution as a mixture of gaussians with a zero mean but different sigmas
  • csb.statmech: Methods for statistical mechanics
    • csb.statmech.ensembles: Statistical Ensembles
    • csb.statmech.wham: Estimate the free energy and density of states from tempered ensembles using histogram re-weighting.
  • csb.test: This is a top level package, hosting the entire CSB test framework.
    • csb.test.app: CSB Test Runner app.