CIBB 2021: the 17th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics (online)

List of accepted short papers

EasyChair ID number, short paper title, authors (in bold the author who presented the article at the conference). Articles that have been released as preprints or have been published as journal articles or as proceedings chapters have an link to their corresponding URL:

1 "A collaborative training approach for stress detection", Eleonora Ciceri, Marco Mosconi, Boris Rozenberg, and Ron Shmelkin

3 "Interpretability methods for differential gene analysis of scRNA-seq clustering models", Madalina Ciortan, and Matthieu Defrance; bioRxiv, 2021.

4 "Non-linear clustering of smell clinic data reliably differs Parkinson’s disease patients and healthy people", Vladislav Abramov, Maria Tunik, Tatiana Anuchina, Natalia Malchik, Ksenia Tutsenko, Alina Horoshavina, Dmitry Pokhabov, Denis Pokhabov, and Michael Sadovsky

5 "High-dimensional multi-trait GWAS by reverse prediction of genotypes using machine learning methods", Muhammad Ammar Malik, Adriaan-Alexander Ludl, and Tom Michoel

7 "Identifying SNP associations and predicting disease risk from genome-wide association studies using LassoNet", Hussain M Sajwani, and Samuel Feng

8 "Convolution and fast Fourier transform to compare symbol sequences", Anna Molyavko, Eugenia Karepova, Michael Sadovsky, and Igor Borovikov

9 "Deep transfer learning for DTI- and MRI- based early diagnosis of cognitive decline and dementia", Nitsa J. Herzog, and George D. Magoulas; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

10 "Genetic algorithms for the identification of marker panels in single-cell RNA data", Andrea Tangherloni, Simone G. Riva, Simone Spolaor, Marco S. Nobile, and Paolo Cazzaniga

11 "Chemical language transformer for drug-target binding affinity", Vincenzo Marco De Luca, Alessio Ferone, and Antonino Staiano

12 "Peeking inside the box: transfer learning vs 3D convolutional neural networks applied in neurodegenerative diseases", Kobra Etminani, Amira Soliman, Stefan Byttner, Anette Davidsson, and Miguel Ochoa-Figueroa; BMC Medical Informatics and Decision Making, 2022.

14 "Topology-aware optimisation of vaccination strategy for minimising virus spreading", Pietro Hiram Guzzi, Francesco Petrizzelli, and Tommaso Mazza

15 "End-to-end facial landmark detection to characterise oro-facial impairments in neurological patients: towards innovative techniques for the assessment of dysarthria", Lucia Migliorelli, Francesco Alborino, Michela Coccia, Laura Villani, Emanuele Frontoni, and Sara Moccia

16 "Knowledge graph-based neurodegenerative diseases and diet relationship discovery", Yi Nian, Xinyue Hu, Rui Zhang, Jingna Feng, Jingcheng Du, Fang Li, Larry Bu, Yuji Zhang, Yong Chen, and Cui Tao; BMC Bioinformatics, 2022.

18 "Cancer-lncRNA: a database of lncRNAs exploring chromosomal linkages in human cancers", Gaurav Kumar Bhagat

19 "Summarizing global SARS–CoV–2 geographical spread by phylogenetic multitype branching models", Hao Chi Kiang, Krzysztof Bartoszek, Sebastian Sakowski, Stefano Maria Iacus, and Michele Vespe; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

20 "Deep recurrent neural networks for generating synthetic coronavirus spike protein sequences", Lisa Crossman; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

21 "A machine learning-based efficient sepsis detection using electronic health records", Ya-Lun Wu, Ding-Hong Xu, Ting-An Chang, Yueh-Tang Weng, Ying-Hsien Wu, and Kai-Cheng Hsu

22 "Automatic plankton detection and classification on raw hologram with a single deep learning architecture", Romane Scherrer, Rodrigue Govan, Thomas Quiniou, Thierry Jauffrais, Hugues Lemonnier, Sophie Bonnet, and Nazha Selmaoui-Folcher; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

23 "Batch effect detection in RNA-Seq data using machine-learning-based automated assessment of quality", Maximilian Sprang, Miguel Andrade-Navarro, and Jean-Fred Fontaine; BMC Bioinformatics, 2022.

24 "RF-isolation: a novel representation of structural connectivity networks for multiple sclerosis classification", Antonella Mensi, Simona Schiavi, Maria Petracca, Nicole Graziano, Alessandro Daducci, Matilde Inglese, and Manuele Bicego; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

25 "A statistical analysis of multiple sclerosis risk factor interaction with Bayesian networks", Morghan Hartmann, Norman Fenton, and Ruth Dobson; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

26 "Stratification of Parkinson's disease patients from the Fox Insight study", Melanija Kraljevska, Marko Robnik-Sikonja, and Anita Valmarska

27 "Structural classification of RNA molecules using ASPRA distance", Michela Quadrini, Luca Tesei, Riccardo Piergallini, and Emanuela Merelli; BMC Bioinformatics, 2023.

28 "Using machine learning to predict reading strategies from fNIRS data", Matthew Campbell, and Indika Kahanda

30 "A non-negative matrix tri-factorization based method for predicting antitumor drug sensitivity", Sara Pidò, Carolina Testa, and Pietro Pinoli; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

31 "The first in-silico model of leg movement activity during sleep", Matteo Italia, Andrea Danani, Fabio Dercole, Raffaele Ferri, and Mauro Manconi; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

32 "Towards generating synthetic pathways for object detection", Joshua Thompson, Fei He, Mihail Popescu, and Dong Xu; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

33 "Toward a standard formal semantic representation of the model card report", Muhammad Amith, Licong Cui, Degui Zhi, Kirk Roberts, Xiaoqian Jiang, and Cui Tao; BMC Bioinformatics, 2022.

35 "Boolean network inference at different levels of logical complexity", Eline S. van Mantgem, and Gunnar W. Klau

36 "Text mining enhancements for image recognitions of gene names and gene relations", Yijie Ren, Fei He, Joshua Thompson, Mark Hannink, Mihail Popescu, and Dong Xu; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

37 "Specialized prognostic models based on disease progression patterns: predicting non-invasive ventilation in ALS patients stratified by progression rate", Andreia S. Martins, Helena Aidos, Marta Gromicho, Mamede de Carvalho, and Sara C. Madeira

38 "Improving bacterial sRNA identification by combining genomic context and sequence-derived features", Mohammad Sorkhian, Megha Nagari, Moustafa Elsisy, and Lourdes Pena-Castillo; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

39 "Predictive modeling for inflammatory bowel disease detection from endoscopic imaging", Nicolae Puica, Marco Chierici, Antonello Capistrano, Marcello Donzella, Antonio Colangelo, Venet Osmani, and Giuseppe Jurman; BMC Medical Informatics and Decision Making, 2022.

40 "Linear regression modelling to assess the impact of socio-economic, demographic and health-related variables on wellbeing in the elderly population", Isotta Trescato, Chiara Roversi, Martina Vettoretti, Barbara Di Camillo, and Andrea Facchinetti

41 "Synthetic cell biotechnology as a useful platform for chemical AI", Pasquale Stano; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

42 "A statistical network method to identify relevant genes for pathway enrichment analysis", Giuseppe Agapito, Mario Cannataro, and Marianna Milano; BMC Bioinformatics, 2022.

43 "Identifying prototype model patients in Amyotrophic Lateral Sclerosis patients at diagnosis through Archetypal Analysis", Isotta Trescato, Erica Tavazzi, Martina Vettoretti, Rosario Vasta, Adriano Chiò, and Barbara Di Camillo

44 "Improved prediction of H3K27ac histone marks in time-series experiments at one time-point using deep learning and novel DNA sequence features extracted from a reference time-point.", Mohammad Hallal, Mariette Awad, and Pierre Khoueiry

45 "In silico clinical trials for relapsing-rermitting multiple sclerosis with MS TreatSim", Fianne Sips, Francesco Pappalardo, Giulia Russo, and Roberta Bursi; BMC Medical Informatics and Decision Making, 2022.

46 "A multi-objective optimisation approach for the linear modelling of cerebral autoregulation system", Felipe-Andres Bello Robles, Manuel Villalobos-Cid, Ronney Panerai, and Mario Inostroza-Ponta

47 "Table detection in text documents for extracting regulatory interaction from literature of regulation in bacteria", Dante Sepulveda, Joel R. Herrera, Axel Zagal Norman, and Carlos-Francisco Méndez-Cruz; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

48 "An alternative learning algorithm for tree augmented naive Bayes: an application to facial biotype classification", Gonzalo A. Ruz, Pamela Araya-Díaz, and Pablo A. Henríquez

49 "Combining denoising and flux balance analysis for single-cell cluster analysis", Bruno Galuzzi, and Chiara Damiani; BMC Bioinformatics, 2022.

50 "BRANET: Graph-based integration of multi-omics data with biological a priori for regulatory network inference", Surabhi Jagtap, Aurélie Pirayre, Frederique Bidard, Laurent Duval, and Fragkiskos D. Malliaros; BMC Bioinformatics, 2022.

51 "Inspecting progression trajectories in amyotrophic lateral sclerosis using process mining", Erica Tavazzi, Roberto Gatta, Mauro Vallati, Stefano Cotti Piccinelli, Massimiliano Filosto, Maurizio Castellano, and Barbara Di Camillo; BMC Medical Informatics and Decision Making, 2023

52 "OG-SPACE: Optimized stochastic simulation of spatial models of cancer evolution", Fabrizio Angaroni, Marco Antoniotti, and Alex Graudenzi

53 "Integrating decision tree learning on the graph database Neo4j to analyze clinical data", Rahul Mondal, Minh Dung Do, Nasim Uddin Ahmed, David Broneske, Gunter Saake, and Robert Heyer; BMC Medical Informatics and Decision Making, 2023.

54 "Impaired core networks and time-distant reconfiguration patterns in Alzheimer's disease", Kai Du, Pindong Chen, Yida Qu, Xiaopeng Kang, and Yong Liu; BMC Bioinformatics, 2022.

56 "Feature relevance in lncRNA microarray data", Emanuel Di Nardo, Marco Sautto, Angelo Ciaramella, Ferdinando Febbraio, and Amelia Cimmino; BMC Bioinformatics, 2023.

57 "Camera-assisted motor state assessment of patients with Parkinson’s disease", Steve Stavropoulos, Spiros Georgakopoulos, Sotiris Tasoulis, and Vassilis Plagianakos

58 "RNA secondary structure factorization in prime tangles", Daniele Marchei, and Emanuela Merelli; BMC Bioinformatics, 2022.

59 "Recent dimensionality reduction techniques for high-dimensional COVID-19 data", Ioannis Dallas, Aristidis Vrahatis, Vassilis Plagianakos, and Sotiris Tasoulis; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

60 "Interlead conversion of single-lead blindly-segmented electrocardiogram signals", Sofia C. Beco, João Ribeiro Pinto, and Jaime S. Cardoso; BMC Medical Informatics and Decision Making, 2022.

61 "The need of standardised metadata to encode causal relationships: towards safer data-driven machine learning biological solutions", Beatriz García Santa Cruz, Carlos Vega Moreno, and Frank Hertel; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

62 "X-AI-Covid-19 diagnosis system based multi-datasets", Aicha Boutorh, Hala Rahim, and Yasmine Bendoumia; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

63 "Environment perception in biochemical reactions", Stefano Maestri, and Emanuela Merelli

64 "Percolation-based stability analysis of functional connectivity in mild cognitive impairment and Alzheimer's disease", Angela Lombardi, Domenico Diacono, Sabina Tangaro, and Roberto Bellotti

65 "Computer-aided diagnosis system for Alzheimer’s disease using principal component analysis and machine learning-based approaches", Lilia Lazli; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

66 "Soft brain ageing indicators based on light-weight LeNet-like neural networks and localized 2D brain age biomarkers", Francesco Bardozzo, Mattia Delli Priscoli, Andrea Gerardo Russo, Davide Crescenzi, Ugo Maria De Benedetto, Fabrizio Esposito, and Roberto Tagliaferri; Springer Lecture Notes in Bioinformatics (LNBI), volume 13483, 2022.

67 "Deep learning based deblocking of Fourier ptycographic images", Mattia Delli Priscoli, Francesco Bardozzo, Vittorio Bianco, Daniele Pirone, Gennaro Zanfardino, Pasquale Memmolo, Lisa Miccio, Gioele Ciaparrone, Pietro Ferraro, and Roberto Tagliaferri

68 "What architectures could lead next generation single cell analysis pipelines?", Zhengyu Chen, Andrea Tangherloni, and Pietro Liò