Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflows

G Bayarri, P Andrio, JL Gelpí, A Hospital… - PLOS Computational …, 2024 - journals.plos.org
… An exhaustive list of available workflows and where they can be found is given in Table A in
… The notebook reproduces the workflow integrated into the FlexServ web-based tool for the …

Sentinel-2 satellite-based analysis of bark beetle damage in Sopron Mountains, Hungary

T Molnár, G Király - Acta Geographica Debrecina Landscape & …, 2023 - ojs.lib.unideb.hu
Sopron mountains were affected by bark beetle (Ips typographus) damage between 2017
and 2020, which was surveyed on high-resolution ESA Sentinel-2 satellite images for the …

Planutils: Bringing planning to the masses

C Muise, F Pommerening, J Seipp… - … Conference on Automated …, 2022 - edoc.unibas.ch
… is, however, currently hosted on personal or lab spaces online, with tools often requiring a
non-… Anaconda Software Distribution. https://docs.anaconda.com/. Benton, J.; Coles, A.; and …

Artifact: Codesign of Edge Intelligence and Automated Guided Vehicle Control

M Gallage, R Scaciota, S Samarakoon… - … Workshops and other …, 2023 - ieeexplore.ieee.org
This is the replication package for the paper, Code-sign of Edge Intelligence and autonomous
guided vehicle (AGV) Control, which is published at the International Conference on …

Restoring execution environments of Jupyter notebooks

J Wang, L Li, A Zeller - 2021 IEEE/ACM 43rd International …, 2021 - ieeexplore.ieee.org
More than ninety percent of published Jupyternotebooks do not state dependencies on external
packages. This makes them non-executable and thus hinders reproducibility of scientific …

MLHCBugs: A Framework to Reproduce Real Faults in Healthcare Machine Learning Applications

GS Jaganathan, N Kazi, I Kahanda… - 2024 IEEE Conference …, 2024 - ieeexplore.ieee.org
Machine Learning (ML) is the field of study that allows computers to learn from experiences
without being explicitly programmed [1]. ML models are currently used in many safety-critical …

Learned embeddings from deep learning to visualize and predict protein sets

C Dallago, K Schütze, M Heinzinger, T Olenyi… - Current …, 2021 - Wiley Online Library
Abstract Models from machine learning (ML) or artificial intelligence (AI) increasingly assist
in guiding experimental design and decision making in molecular biology and medicine. …

A brief survey of tools for genomic regions enrichment analysis

D Chicco, G Jurman - Frontiers in bioinformatics, 2022 - frontiersin.org
Functional enrichment analysis or pathway enrichment analysis (PEA) is a bioinformatics
technique which identifies the most over-represented biological pathways in a list of genes …

Ten quick tips for building FAIR workflows

C de Visser, LF Johansson, P Kulkarni… - PLoS Computational …, 2023 - journals.plos.org
Research data is accumulating rapidly and with it the challenge of fully reproducible science.
As a consequence, implementation of high-quality management of scientific data has …

MEGARes and AMR++, v3. 0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using …

N Bonin, E Doster, H Worley, LJ Pinnell… - Nucleic acids …, 2023 - academic.oup.com
Antimicrobial resistance (AMR) is considered a critical threat to public health, and genomic/metagenomic
investigations featuring high-throughput analysis of sequence data are …