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Project description

BioCommons is a Java library with classes, data structures and embedded static knowledge useful in structural bioinformatics.

If you use BioCommons in your research, please cite:

BioCommons: A Robust Java Library for RNA Structural Bioinformatics. T. Zok. Bioinformatics. 2021. 37(17):2766–2767. doi:10.1093/bioinformatics/btab069

Maven

You can use BioCommons by adding the following to your pom.xml:

<dependency>
  <groupId>pl.poznan.put</groupId>
  <artifactId>BioCommons</artifactId>
  <version>3.1.10</version>
</dependency>

Documentation

You can find the documentation here

Examples

You can find examples and HOWTOs in the wiki

Functionality

  • Full analysis of PDB and mmCIF files, including missing and modified residues, experimental data, etc.
  • An enumeration of atom types, names and aliases used in PDB and mmCIF files
  • Atomic bond lengths’ validation
  • Notations from the literature (Zirbel et al. 2009, Leontis et al. 2001, Saenger 1984)
  • Torsion angle analysis for proteins, including varying number of chi angle types for different amino acids
  • Torsion angle analysis for nucleic acids, including pseudo-torsion angles (Keating et al. 2011) and pseudo-phase pucker of the sugar ring (Saenger 1984)
  • Analysis of circular data (Fisher 1993), including correct averaging of angles
  • Advanced analysis of RNA secondary structure in BPSEQ, CT or dot-bracket formats
  • Handling of pseudoknots of any order (Smit et al. 2008)
  • General-purpose constants and utility classes (e.g. handling of SVG images)

Used in

  • MCQ4Structures (Magnus et al. 2020, Wiedemann et al. 2017, Zok et al. 2014)
  • RNApdbee (Zok et al. 2018, Antczak et al. 2018, Antczak et al. 2014)
  • RNAvista (Antczak et al. 2019, Rybarczyk et al. 2015)
  • RNAfitme (Antczak et al. 2018, Zok et al. 2015)

Bibliography

  1. BioCommons: A Robust Java Library for RNA Structural Bioinformatics. T. Zok. Bioinformatics. 2021. 37(17):2766–2767. doi:10.1093/bioinformatics/btab069

  2. RNA-Puzzles Toolkit: A Computational Resource of RNA 3D Structure Benchmark Datasets, Structure Manipulation and Evaluation Tools. M. Magnus, M. Antczak, T. Zok, J. Wiedemann, P. Lukasiak, Y. Cao, J.M. Bujnicki, E. Westhof, M. Szachniuk, Z. Miao. Nucleic Acids Research. 2020. 48(2):576–588. doi:10.1093/nar/gkz1108

  3. RNAvista: A Webserver to Assess RNA Secondary Structures with Non-Canonical Base Pairs. M. Antczak, M. Zablocki, T. Zok, A. Rybarczyk, J. Blazewicz, M. Szachniuk. Bioinformatics. 2019. 35(1):152–155. doi:10.1093/bioinformatics/bty609

  4. RNAfitme: A Webserver for Modeling Nucleobase and Nucleoside Residue Conformation in Fixed-Backbone RNA Structures. M. Antczak, T. Zok, M. Osowiecki, M. Popenda, R.W. Adamiak, M. Szachniuk. BMC Bioinformatics. 2018. 19(1):304. doi:10.1186/s12859-018-2317-9

  5. RNApdbee 2.0: Multifunctional Tool for RNA Structure Annotation. T. Zok, M. Antczak, M. Zurkowski, M. Popenda, J. Blazewicz, R.W. Adamiak, M. Szachniuk. Nucleic Acids Research. 2018. 46(W1):W30–W35. doi:10.1093/nar/gky314

  6. New Algorithms to Represent Complex Pseudoknotted RNA Structures in Dot-Bracket Notation. M. Antczak, M. Popenda, T. Zok, M. Zurkowski, R.W. Adamiak, M. Szachniuk. Bioinformatics. 2018. 34(8):1304–1312. doi:10.1093/bioinformatics/btx783

  7. LCS-TA to Identify Similar Fragments in RNA 3D Structures. J. Wiedemann, T. Zok, M. Milostan, M. Szachniuk. BMC Bioinformatics. 2017. 18(1):456. doi:10.1186/s12859-017-1867-6

  8. New in Silico Approach to Assess RNA Secondary Structures with Non-Canonical Base Pairs. A. Rybarczyk, N. Szostak, M. Antczak, T. Zok, M. Popenda, R.W. Adamiak, J. Blazewicz, M. Szachniuk. BMC Bioinformatics. 2015. 16(1):276. doi:10.1186/s12859-015-0718-6

  9. Building the Library of RNA 3D Nucleotide Conformations Using Clustering Approach. T. Zok, M. Antczak, M. Riedel, D. Nebel, T. Villmann, P. Lukasiak, J. Blazewicz, M. Szachniuk. International Journal of Applied Mathematics and Computer Science. 2015. 25(3):689–700. doi:10.1515/amcs-2015-0050

  10. MCQ4Structures to Compute Similarity of Molecule Structures. T. Zok, M. Popenda, M. Szachniuk. Central European Journal of Operations Research. 2014. 22(3):457–473. doi:10.1007/s10100-013-0296-5

  11. RNApdbee – a Webserver to Derive Secondary Structures from Pdb Files of Knotted and Unknotted RNAs. M. Antczak, T. Zok, M. Popenda, P. Lukasiak, R.W. Adamiak, J. Blazewicz, M. Szachniuk. Nucleic Acids Research. 2014. 42(W1):W368–W372. doi:10.1093/nar/gku330

  12. A New Way to See RNA. K.S. Keating, E.L. Humphris, A.M. Pyle. Quarterly Reviews of Biophysics. 2011. 44(4):433–466. doi:10.1017/S0033583511000059

  13. Classification and Energetics of the Base-Phosphate Interactions in RNA. C.L. Zirbel, J.E. Šponer, J. Šponer, J. Stombaugh, N.B. Leontis. Nucleic Acids Research. 2009. 37(15):4898–4918. doi:10.1093/nar/gkp468

  14. From Knotted to Nested RNA Structures: A Variety of Computational Methods for Pseudoknot Removal. S. Smit, K. Rother, J. Heringa, R. Knight. RNA. 2008. 14(3):410–416. doi:10.1261/rna.881308

  15. Geometric Nomenclature and Classification of RNA Base Pairs. N.B. Leontis, E. Westhof. RNA. 2001. 7(4):499–512. doi:10.1017/S1355838201002515

  16. Statistical Analysis of Circular Data. N.I. Fisher.

  17. Principles of Nucleic Acid Structure. W. Saenger.