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Documents authored by Ciach, Michał Aleksander


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DiscrimAlign

Authors: Michał Aleksander Ciach, Elissavet Zacharopoulou, Michał Piotr Startek, Błażej Miasojedow, and Panagiotis Alexiou


Abstract

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Michał Aleksander Ciach, Elissavet Zacharopoulou, Michał Piotr Startek, Błażej Miasojedow, Panagiotis Alexiou. DiscrimAlign (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@misc{dagstuhl-artifact-27630,
   title = {{DiscrimAlign}}, 
   author = {Ciach, Micha{\l} Aleksander and Zacharopoulou, Elissavet and Startek, Micha{\l} Piotr and Miasojedow, B{\l}a\.{z}ej and Alexiou, Panagiotis},
   note = {Software, version 1.0., swhId: \href{https://archive.softwareheritage.org/swh:1:dir:e70ee75187e06eb93adc1da6022502a80230d4b0;origin=https://github.com/BioGeMT/DiscrimAlign;visit=swh:1:snp:099e310c351ec557fd10ce0904c01902f0385dd5;anchor=swh:1:rev:2f69b6664e86039919793e651f89602063d5433d}{\texttt{swh:1:dir:e70ee75187e06eb93adc1da6022502a80230d4b0}} (visited on 2026-08-27)},
   url = {https://github.com/BioGeMT/DiscrimAlign},
   doi = {10.4230/artifacts.27630},
}
Document
Discriminative Learning of Substitution Matrices and Gap Penalties for Pairwise Alignment of Biological Sequences

Authors: Michał Aleksander Ciach, Elissavet Zacharopoulou, Michał Piotr Startek, Błażej Miasojedow, and Panagiotis Alexiou

Published in: LIPIcs, Volume 390, 26th International Conference on Algorithms for Bioinformatics (WABI 2026)


Abstract
Pairwise alignment scores are used to classify pairs of sequences in many areas of bioinformatics, including homology search, predicting interactions, or read mapping. The relative scores of different pairs strongly depend on the choice of a substitution matrix and gap penalties. However, current approaches for the estimation of these parameters typically describe patterns observed in a collection of ground-truth alignments instead of optimizing specifically for the task of classification. In this work, we present DiscrimAlign, a statistical model for discriminative learning of substitution matrices and gap penalties from a dataset of positive and negative pairs of unaligned DNA or amino acid sequences. The model links the alignment score of a sequence pair with the associated binary label through a logistic function and learns the parameters by likelihood maximization. We analyze theoretical properties of the model, derive and implement a learning procedure, study its performance in simulated experiments, and apply it to predict microRNA-target interactions. We show that sequence alignment with discriminative substitution matrices and gap penalties predicts the interactions comparably to black-box neural network classifiers while being more interpretable. An implementation of the model and reproducibility workflows are available at https://github.com/BioGeMT/DiscrimAlign.

Cite as

Michał Aleksander Ciach, Elissavet Zacharopoulou, Michał Piotr Startek, Błażej Miasojedow, and Panagiotis Alexiou. Discriminative Learning of Substitution Matrices and Gap Penalties for Pairwise Alignment of Biological Sequences. In 26th International Conference on Algorithms for Bioinformatics (WABI 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 390, pp. 17:1-17:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{ciach_et_al:LIPIcs.WABI.2026.17,
  author =	{Ciach, Micha{\l} Aleksander and Zacharopoulou, Elissavet and Startek, Micha{\l} Piotr and Miasojedow, B{\l}a\.{z}ej and Alexiou, Panagiotis},
  title =	{{Discriminative Learning of Substitution Matrices and Gap Penalties for Pairwise Alignment of Biological Sequences}},
  booktitle =	{26th International Conference on Algorithms for Bioinformatics (WABI 2026)},
  pages =	{17:1--17:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-446-8},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{390},
  editor =	{El-Mabrouk, Nadia and Vandin, Fabio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2026.17},
  URN =		{urn:nbn:de:0030-drops-275218},
  doi =		{10.4230/LIPIcs.WABI.2026.17},
  annote =	{Keywords: Sequence alignment, Substitution matrix, Logistic regression}
}

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