To help you get started, we've collected the most common ways that biotite is being used within popular public projects.

biotite-dev / biotite / tests / structure / test_superimpose.py View on Github

Take a structure and rotate and translate a copy of it, so that they
    are not superimposed anymore.
    Then superimpose these structure onto each other and expect an
    almost perfect match.
    """
    fixed = strucio.load_structure(path, model=1)
    
    mobile = fixed.copy()
    mobile = struc.rotate(mobile, (1,2,3))
    mobile = struc.translate(mobile, (1,2,3))
    
    fitted, transformation = struc.superimpose(
        fixed, mobile
    )
    
    assert struc.rmsd(fixed, fitted) == pytest.approx(0, abs=6e-4)
    
    fitted = struc.superimpose_apply(mobile, transformation)
    
    assert struc.rmsd(fixed, fitted) == pytest.approx(0, abs=6e-4)

View more ways to use biotite

Biotite project

Biotite is your Swiss army knife for bioinformatics. Whether you want to identify homologous sequence regions in a protein family or you would like to find disulfide bonds in a protein structure: Biotite has the right tool for you. This package bundles popular tasks in computational molecular biology into a uniform Python library. It can handle a major part of the typical workflow for sequence and biomolecular structure data:

> - Searching and fetching data from biological databases > - Reading and writing popular sequence/structure file formats > - Analyzing and editing sequence/structure data > - Visualizing sequence/structure data > - Interfacing external applications for further analysis

Biotite internally stores most of the data as NumPy ndarray objects, enabling

> - fast C-accelerated analysis, > - intuitive usability through NumPy-like indexing syntax, > - extensibility through direct access of the internal NumPy > arrays.

As a result the user can skip writing code for basic functionality (like file parsers) and can focus on what their code makes unique - from small analysis scripts to entire bioinformatics software packages.

If you use Biotite in a scientific publication, please cite:

Kunzmann, P. & Hamacher, K. BMC Bioinformatics (2018) 19:346.

Installation

Biotite requires the following packages:

> - numpy > - requests > - msgpack > - networkx

Some functions require some extra packages:

> - matplotlib - Required for plotting purposes.

Biotite can be installed via Conda...

$ conda install -c conda-forge biotite

... or pip

$ pip install biotite

Usage

Here is a small example that downloads two protein sequences from the NCBI Entrez database and aligns them:

import biotite.sequence.align as align
import biotite.sequence.io.fasta as fasta
import biotite.database.entrez as entrez

# Download FASTA file for the sequences of avidin and streptavidin
file_name = entrez.fetch_single_file(
    uids=["CAC34569", "ACL82594"], file_name="sequences.fasta",
    db_name="protein", ret_type="fasta"
)

# Parse the downloaded FASTA file
# and create 'ProteinSequence' objects from it
fasta_file = fasta.FastaFile.read(file_name)
avidin_seq, streptavidin_seq = fasta.get_sequences(fasta_file).values()

# Align sequences using the BLOSUM62 matrix with affine gap penalty
matrix = align.SubstitutionMatrix.std_protein_matrix()
alignments = align.align_optimal(
    avidin_seq, streptavidin_seq, matrix,
    gap_penalty=(-10, -1), terminal_penalty=False
)
print(alignments[0])

MVHATSPLLLLLLLSLALVAPGLSAR------KCSLTGKWDNDLGSNMTIGAVNSKGEFTGTYTTAV-TA
-------------------DPSKESKAQAAVAEAGITGTWYNQLGSTFIVTA-NPDGSLTGTYESAVGNA

TSNEIKESPLHGTQNTINKRTQPTFGFTVNWKFS----ESTTVFTGQCFIDRNGKEV-LKTMWLLRSSVN
ESRYVLTGRYDSTPATDGSGT--ALGWTVAWKNNYRNAHSATTWSGQYV---GGAEARINTQWLLTSGTT

DIGDDWKATRVGINIFTRLRTQKE---------------------
-AANAWKSTLVGHDTFTKVKPSAASIDAAKKAGVNNGNPLDAVQQ

More documentation, including a tutorial, an example gallery and the API reference is available at .

Contribution

Interested in improving Biotite? Have a look at the contribution guidelines. Feel free to join our community chat on Discord.