Developing artificial intelligence tools for solving bionformatical problems  Page description

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Details of project

  
Identifier
127909
Type K
Principal investigator Grolmusz, Vince
Title in Hungarian Mesterséges intelligenciai eszközök fejlesztése bioinformatikai problémák megoldására
Title in English Developing artificial intelligence tools for solving bionformatical problems
Keywords in Hungarian bioinformatika, hálózatok, neurális hálók
Keywords in English bioinformatics, networks, neural nets
Discipline
Information Technology (Council of Physical Sciences)90 %
Ortelius classification: Applied informatics
Mathematics (Council of Physical Sciences)5 %
Ortelius classification: Computational mathematics
Bioinformatics (Council of Medical and Biological Sciences)5 %
Panel Informatics and Electrical Engineering
Department or equivalent Department of Computer Science (Eötvös Loránd University)
Participants Fellner, Máté
Rec, Tamás
Takács, Kristóf
Varga, Bálint
Starting date 2018-09-01
Closing date 2022-11-30
Funding (in million HUF) 48.000
FTE (full time equivalent) 4.30
state running project





 

Final report

  
Results in Hungarian
Rendkívül sikeres projektet zárunk: 19 referált, angol nyelvű folyóirat-publikációból 5 D1 lapban, 9 Q1 lapban jelent meg, a kumulatív impact factor 59.989 . Két webszervert hoztunk létre: A Budapest Amyloid Predictort: https://pitgroup.org/bap A PDB_Amyloid listát: https://pitgroup.org/amyloid/ Illetve, a már létező https://braingraph.org webszerverüket több százezer új, augmentált konnektommal bővítettük. Sok alapjában új módszert dolgoztunk ki, így a konnektomok írányítására, a implkátor élek megtalálására, és robusztus, hibatűrő egzakt vizsgálatokat vezettünk be.
Results in English
We have concluded a very successful project: Number of referred, international journal publications in the course of the project: 19, from these: Number of D1 journal publications: 5 Number of Q1 journal publications: 9 Cumulative impact factor of our journal publications in project K 127909: 59.989 We have introduced the Budapest Amyloid Predictort: https://pitgroup.org/bap webserver, and the PDB_Amyloid list: https://pitgroup.org/amyloid/ The already existent webserver of ours, https://braingraph.org was refreshed by several hundred thousand new augmented connectomes.
Full text https://www.otka-palyazat.hu/download.php?type=zarobeszamolo&projektid=127909
Decision
Yes





 

List of publications

  
Szalkai B, Grolmusz V: MetaHMM: A webserver for identifying novel genes with specified functions in metagenomic samples, GENOMICS 111: (4) pp. 883-885., 2019
Szalkai B, Varga B, Grolmusz V: Mapping correlations of psychological and structural connectome properties of the dataset of the human connectome project with the maximum spanning tree method, BRAIN IMAGING AND BEHAVIOR 13: (5) pp. 1185-1192., 2019
Takács K., Varga B., Grolmusz V.: PDB_Amyloid: an extended live amyloid structure list from the PDB, FEBS OPEN BIO 9: (1) pp. 185-190., 2019
László Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel, Vince Grolmusz: Succinct Amyloid and Non-Amyloid Patterns in Hexapeptides, ACS Omega Vol. 7, No. 40, 35532-35537, 2022
Laszlo Keresztes, Evelin Szogi, Balint Varga, Vince Grolmusz: Identifying Super-Feminine, Super-Masculine and Sex-Defining Connections in the Human Braingraph, Cognitive Neurodynamics, Vol. 15. No. 6. pp. 949-959, 2021
Kristof Takacs, Vince Grolmusz: The multiple alignments of very short sequences, FASEB BioAdvances 2021;3:523-530, 2021
Balint Varga, Vince Grolmusz: The braingraph.org Database with more than 1000 Robust HumanStructural Connectomes in Five Resolutions, Cognitive Neurodynamics Vol. 15 No. 5, pp. 915-919,, 2021
Balázs Szalkai, Bálint Varga, Vince Grolmusz: The Graph of our Mind, Brain Sciences Vol. 11, No. 3. 342, 2021
Lászlo Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel, Vince Grolmusz: The Budapest Amyloid Predictor and its Applications, Biomolecules, 11(4) 500,, 2021
Kristóf Takács, Vince Grolmusz: On the Border of the Amyloidogenic Sequences: Prefix Analysis of the Parallel Beta Sheets in the PDB_Amyloid Collection, Journal of Integrative Bioinformatics, 2021
Szalkai B, Varga B, Grolmusz V: Mapping correlations of psychological and structural connectome properties of the dataset of the human connectome project with the maximum spanning tree method, BRAIN IMAGING AND BEHAVIOR 13: (5) pp. 1185-1192., 2019
Takács K., Varga B., Grolmusz V.: PDB_Amyloid: an extended live amyloid structure list from the PDB, FEBS OPEN BIO 9: (1) pp. 185-190., 2019
Fellner Máté, Varga Bálint, Grolmusz Vince: The Frequent Network Neighborhood Mapping of the human hippocampus shows much more frequent neighbor sets in males than in females, PLOS ONE 15: (1) e0227910, 2020
Fellner Máté, Varga Bálint, Grolmusz Vince: Good neighbors, bad neighbors: the frequent network neighborhood mapping of the hippocampus enlightens several structural factors of the human intelligence, SCIENTIFIC REPORTS 10: (1) 11967, 2020
Balázs Szalkai, Vince Grolmusz: SCARF: A Biomedical Association Rule Finding Webserver,, Journal of Integrative Bioinformatics, Vol. 19, No. 1. pp. 20210035, 2022
László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Introducing and Applying Newtonian Blurring: An Augmented Dataset of 126,000 Human Connectomes at braingraph.org, Scientific Reports, 12:3102, 2022
László Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel, Vince Grolmusz: Succinct Amyloid and Non-Amyloid Patterns in Hexapeptides, ACS Omega, 2022
László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Discovering Sex and Age Implicator Edges in the Human Connectome, Neuroscience Letters Vol. 791, 136913, 2022
Muntasir Kamal, Levon Tokmakjian, Jessica Knox, Peter Mastrangelo, Jingxiu Ji, Hao Cai, Jakub Wojciechowski, Micael P. Hughes, Kristof Takacs, Xiaoquan Chu, Jianfeng Pei, Vince Grolmusz, Malgorzata Kotulska, Julie Deborah Forman-Kay, Peter J. Roy: A Spatiotemporal Reconstruction of the C. elegans Pharyngeal Cuticle Reveals a Structure Rich in Phase-Separating Proteins, eLife, 2022
Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Subgraphs of the Connectome of the Human Brain, Cognitive Neurodynamics Vol. 13, No. 5, pp. 453-460 (2019) https://doi.org/10.1007 /s11571-019-09535-y https://rdcu.be/bAHoe, 2019
Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: High-Resolution Directed Human Connectomes and the Consensus Connectome Dynamics, PLOS ONE, Vol. 14 No. 4,: e0215473 (2019) https://doi.org/10.1371/journal.pone.0215473, 2019
Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Complete Subgraphs in the Human Connectome, In: Rojas I., Joya G., Catala A. (eds) Advances in Computational Intelligence. IWANN 2019. Lecture Notes in Computer Science, Vol 11507. pp. 908-920, Springer, 2019
Balint Varga, Vince Grolmusz: The braingraph.org Database with more than 1000 Robust HumanStructural Connectomes in Five Resolutions, arXiv preprint arXiv:2008.13273, 2020
Fellner Máté, Varga Bálint, Grolmusz Vince: The Frequent Complete Subgraphs in the Human Connectome, PLOS ONE 15(8): e0236883 (2020), 2020
Fellner Máté, Varga Bálint, Grolmusz Vince: The Frequent Network Neighborhood Mapping of the human hippocampus shows much more frequent neighbor sets in males than in females, PLOS ONE 15: (1) e0227910, 2020
Fellner Máté, Varga Bálint, Grolmusz Vince: Good neighbors, bad neighbors: the frequent network neighborhood mapping of the hippocampus enlightens several structural factors of the human intelligence on a 414-subject cohort, SCIENTIFIC REPORTS 10: (1) 11967, 2020
Kristof Takacs, Vince Grolmusz: On the Border of the Amyloidogenic Sequences: Prefix Analysis of the Parallel Beta Sheets in the PDB Amyloid Collection, arXiv preprint arXiv:2003:02942, 2020
László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Introducing and Applying Newtonian Blurring: An Augmented Dataset of 126,000 Human Connectomes at braingraph.org, arXiv preprint arXiv:2010.09568 (2020), 2020
Fellner Mate, Varga Balint, Grolmusz Vince: The frequent subgraphs of the connectome of the human brain, COGNITIVE NEURODYNAMICS 13: (5) pp. 453-460., 2019
Fellner Mate, Varga Balint, Grolmusz Vince: The Frequent Complete Subgraphs in the Human Connectome, In: Catala, A; Joya, G; Rojas (szerk.) ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2019, PT II, SPRINGER INTERNATIONAL PUBLISHING AG (2019) pp. 908-920., 2019
Laszlo Keresztes, Evelin Szogi, Balint Varga, Vince Grolmusz: Identifying Super-Feminine, Super-Masculine and Sex-Defining Connections in the Human Braingraph, arXiv preprint arXiv:1912:02291, 2019
Szalkai B, Grolmusz V: MetaHMM: A webserver for identifying novel genes with specified functions in metagenomic samples, GENOMICS 111: (4) pp. 883-885., 2019
Szalkai B, Kerepesi Cs, Varga B, Grolmusz V: High-Resolution Directed Human Connectomes and the Consensus Connectome Dynamics, PLOS ONE 14: (4) e0215473, 2019




 

Events of the project

  
2022-01-04 16:52:32
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