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How to measure the topological quality of protein parse trees?

Title: How to measure the topological quality of protein parse trees?
Authors: Pyzik, Mateusz; Coste, François; Dyrka, Witold
Contributors: Wrocław University of Science and Technology = Politechnika Wroclawska Wrocław; Dynamics, Logics and Inference for biological Systems and Sequences (Dyliss); Inria Rennes – Bretagne Atlantique; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7); Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)
Source: ICGI 2018 - 14th International Conference on Grammatical Inference ; https://inria.hal.science/hal-01938608 ; ICGI 2018 - 14th International Conference on Grammatical Inference, Sep 2018, Wroclaw, Poland. pp.118 - 138
Publisher Information: HAL CCSD
Publication Year: 2018
Collection: Université de Rennes 1: Publications scientifiques (HAL)
Subject Terms: context-free grammar; parse tree; contact map; molecular language; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Subject Geographic: Wroclaw; Poland
Description: International audience ; Human readability and, consequently, interpretability is often considered a key advantage of grammatical descriptors. Beyond the natural language, this is also true in analyzing biological sequences of RNA, typically modeled by grammars of at least context-free level of expressiveness. However, in protein sequence analysis, the explanatory power of grammatical descriptors beyond regular has never been thoroughly assessed. Since the biological meaning of a protein molecule is directly related to its spatial structure, it is justified to expect that the parse tree of a protein sequence reflects the spatial structure of the protein. In this piece of research, we propose and assess quantitative measures for comparing topology of the parse tree of a context-free grammar with topology of the protein structure succinctly represented by a contact map. Our results are potentially interesting beyond its bioinformatic context wherever a reference matrix of dependencies between sequence constituents is available.
Document Type: conference object
Language: English
Availability: https://inria.hal.science/hal-01938608; https://inria.hal.science/hal-01938608v1/document; https://inria.hal.science/hal-01938608v1/file/pyzik18.pdf
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.13748493
Database: BASE