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Graphical user interfaces

Findaureus: An open-source application for locating Staphylococcus aureus in fluorescence-labelled infected bone tissue slices

Shibarjun Mandal, Astrid Tannert, [ ... ], Luís Bastião Silva

Enabling AI in synthetic biology through Construction File specification

Nassim Ataii, Sanjyot Bakshi, [ ... ], J. Christopher Anderson

ShinyLUTS—A Shiny web application for structured data management and analysis for patients with lower urinary tract symptoms (LUTS)

Christoph-Alexander Joachim von Klot, Cornelius Köpp, Markus Antonius Kuczyk, Mathias Wolters

Development of a graphical user interface for automatic separation of human voice from Doppler ultrasound audio in diving experiments

Arian Azarang, S. Lesley Blogg, [ ... ], Virginie Papadopoulou

A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing

Ammar Malik, Hugo Lhachemi, Robert Shorten

Vizaj—A free online interactive software for visualizing spatial networks

Thibault Rolland, Fabrizio De Vico Fallani

Not getting in too deep: A practical deep learning approach to routine crystallisation image classification

Jamie Milne, Chen Qian, [ ... ], Julie Wilson

Can individual subjective confidence in training questions predict group performance in test questions?

Masaru Shirasuna, Hidehito Honda

FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking

Lara Hauke, Andreas Primeßnig, [ ... ], Florian Rehfeldt

Graphical user interface design to improve understanding of the patient-reported outcome symptom response

Mangyeong Lee, Danbee Kang, [ ... ], Juhee Cho

IMAGE-IN: Interactive web-based multidimensional 3D visualizer for multi-modal microscopy images

Yubraj Gupta, Carlos Costa, [ ... ], Rainer Heintzmann

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation

Tim Scherr, Johannes Seiffarth, [ ... ], Ralf Mikut

NGSpop: A desktop software that supports population studies by identifying sequence variations from next-generation sequencing data

Dong-Jun Lee, Taesoo Kwon, [ ... ], Tae-Ho Lee

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