ALGA (ALgorithm for Genome Assembly) is a genome-scale de novo sequence assembler based on the overlap graph approach. The method accepts at the input reads from the next generation DNA sequencing, paired or not. It can be used without setting any parameter by a user, parameters are adjusted internally by ALGA on the basis of input data. Only one optional parameter is left, the maximum allowed error rate in overlaps of reads, with its default (and suggested) value 0.ALGA incorporates several new ideas resulting in more exact contigs produced in acceptable time. Among these ideas we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland.More information can be found using the URL below and in the article: S. Swat, A. Laskowski, J. Badura, W. Frohmberg, P. Wojciechowski, A. Świercz, M. Kasprzak, J. Błażewicz, "Genome-scale de novo assembly using ALGA", Bioinformatics - 2021, vol. 37, iss. 12, s. 1644-1651.

RNAvista is a webserver to assess RNA secondary structure with non-canonical base pairs.

CLAIM-MS - CLAIM Multi Source, an expanded version of CLAIM.Authors: Marek Blazewicz1,2, Giovanni Felici3, Aleksandra Swiercz1,4, Daniele Santoni3, Marcin Jaroszewski1, Agnieszka Zmienko1,4, Marta Kasprzak1,4CLAIM-MS is a method for finding functionally related genes. The novelty of this proposition is in its flexibility, as the method integrates information from many input data sources of different types. We successfully validated it on gene expression data produced by different technologies (microarray, RNA-seq) and experiment setups (case-control or multi-class, single-time-point or time-series), on protein-protein interaction networks and Gene Ontology annotations. For each dataset, a gene-gene distance metric needs to be derived in accordance with its nature and the experiment setup.  This approach expands our previous work with, among others: the ability to handle more than two data sources at once; a new robustly converging clustering algorithm (a neural gas method); a more efficient clique detection algorithm; deep analysis of underlying distance matrices, which allow tuning up the evaluation of gene clusters with respect to a particular biological dataset; this procedure significantly improves the overall quality of the outcomes. The instruction on how to run the application can be found at: README The research was supported by grant No. 2012/05/B/ST6/03026 from the National Science Centre,  Poland. A publication presenting both the method and the results is in preparation.1 Institute of Computing Science,Poznan University of Technology, Poznan, Poland. 2 Poznan Supercomputing and Networking Center, Poznan, Poland. 3 Institute for Systems Analysis and Computer Science “Antonio Ruberti”, National Research Council of Italy, Rome, Italy. 4 Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland.

The RNApdbee is a webserver to derive secondary structures from pdb files of knotted and unknotted RNAsM. Antczak, T. Zok, M. Popenda, P. Lukasiak, R.W. Adamiak, J. Blazewicz, M. Szachniuk. RNApdbee - a webserver to derive secondary structures from pdb files of knotted and unknotted RNAs, Nucleic Acids Research 42(W1), 2014, W368-W372 (doi:10.1093/nar/gku330).M. Antczak, M. Popenda, T. Zok, M. Zurkowski, R.W. Adamiak, M. Szachniuk. New algorithms to represent complex pseudoknotted RNA structures in dot-bracket notation, Bioinformatics 34(8), 2018, 1304-1312 (doi:10.1093/bioinformatics/btx783).T. Zok, M. Antczak, M. Zurkowski, M. Popenda, J. Blazewicz, R.W. Adamiak, M. Szachniuk. RNApdbee 2.0: multifunctional tool for RNA structure annotation, Nucleic Acids Research 46(W1), 2018 (doi:10.1093/nar/gky314).

RNAComposer is a tool for fully automated prediction of large RNA 3D structures. It is freely available online.M. Popenda, M. Szachniuk, M. Antczak, K.J. Purzycka, P. Lukasiak, N. Bartol, J. Blazewicz, R.W. Adamiak. Automated 3D structure composition for large RNAs. Nucleic Acids Research 40(14), 2012, e112 (doi:10.1093/nar/gks339).M. Antczak, M. Popenda, T. Zok, J. Sarzynska, T. Ratajczak, K. Tomczyk, R.W. Adamiak, M. Szachniuk. New functionality of RNAComposer: an application to shape the axis of miR160 precursor structure, Acta Biochimica Polonica 63(4), 2016, 737-744 (doi:10.18388/abp.2016_1329).

CLAIM - coupling co-expression data and protein-protein interaction networks for functional protein analysisCLAIM (CLusterAnalysis Integration Method) is a new method for integrating co-expression data obtained through microarray experiments (MA) and protein-protein interaction (PPI) network data. Microarray and PPI data are separately clustered; the clusters are then merged in a special graph; cliques of this graph would identify a group of functionally related proteins. The biological insight provided by these groups is analyzed on the basis of co-localization and mRNA developmental expression, pointing out the new information that can be obtained by this method.CLAIM can be also used to assign proteins whose functional role is unknown to pathways using the cliques that are strongly associated with known pathways. The basic assumption is that, if a protein belongs to a clique and the other proteins in that clique are in a known pathway, then that protein is likely to belong to that pathway. Based on this assumption, pathway assignment was performed through a score prediction function, based on the presence of a protein in pathway enriched cliques.The prediction power of the algorithm appears to be sufficiently high to make this method a useful semi-automated tool for protein functional analysis.Method CLAIM has been tested on the model organism Arabidopsis thaliana.For more detailed information please read CLAIM README.Daniele Santoni3, Aleksandra Swiercz1,4, Agnieszka Żmieńko1,4, Marta Kasprzak1,4, Marek Blazewicz1,2, Paola Bertolazzi3, Giovanni Felici3, An Integrated Approach (CLuster Analysis Integration Method) to Combine Expression Data and Protein–Protein Interaction Networks in Agrigenomics: Application on Arabidopsis thaliana, OMICS: A Journal of Integrative Biology. January 2014, 18(2): 155-165. doi:10.1089/omi.2013.0050.1 Institute of Computing Science,Poznan University of Technology, Poznan, Poland. 2 Poznan Supercomputing and Networking Center, Poznan, Poland. 3 Institute for Systems Analysis and Computer Science “Antonio Ruberti”, National Research Council of Italy, Rome, Italy. 4 Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland.

A tabu search algorithm for DNA sequencing by hybridization problem with a partial multiplicity information (a test set included)