Results 61 to 70 of about 11,449,331 (358)

Introducing the FAIR Principles for research software

open access: yesScientific Data, 2022
Research software is a fundamental and vital part of research, yet significant challenges to discoverability, productivity, quality, reproducibility, and sustainability exist.
M. Barker   +10 more
semanticscholar   +1 more source

From omics to AI—mapping the pathogenic pathways in type 2 diabetes

open access: yesFEBS Letters, EarlyView.
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan   +2 more
wiley   +1 more source

ANALYZING THE SOFTWARE QUALITY IN IMAGE PROCESSING SOFTWARE IN INDUSTRY USING MACHINE LEARNING

open access: yesICTACT Journal on Image and Video Processing, 2022
The ability of manufacturing organisations to generate defect-free, high-quality products is critical to their long-term success in the marketplace.
B Gopinathan   +3 more
doaj   +1 more source

Quality Management Software [PDF]

open access: yesLaboratory Medicine, 2005
ity systems management. The motivator may simply be a desire to improve quality or more often a need to comply with accreditation requirements. For some time now, industries have used ISO registration as an indicator of the quality of their product or service provided. Now health care is being expected to demonstrate quality services.
openaire   +2 more sources

The anabolic steroid stanozolol is a potent inhibitor of human MutT homolog 1

open access: yesFEBS Letters, EarlyView.
MutT homolog 1 (MTH1) is a member of the NUDIX superfamily of enzymes and is an anticancer drug target. We show that stanozolol (Stz), an anabolic steroid, is an unexpected nanomolar inhibitor of MTH1. The X‐ray crystal structure of the human MTH1–Stz complex reveals a unique binding scaffold that could be utilized for future inhibitor development ...
Emma Scaletti Hutchinson   +7 more
wiley   +1 more source

A Review of Software Quality Models for the Evaluation of Software Products [PDF]

open access: yesarXiv.org, 2014
Actually, software products are increasing in a fast way and are used in almost all activities of human life. Consequently measuring and evaluating the quality of a software product has become a critical task for many companies.
Jose P. Miguel   +2 more
semanticscholar   +1 more source

ERBIN limits epithelial cell plasticity via suppression of TGF‐β signaling

open access: yesFEBS Letters, EarlyView.
In breast and lung cancer patients, low ERBIN expression correlates with poor clinical outcomes. Here, we show that ERBIN inhibits TGF‐β‐induced epithelial‐to‐mesenchymal transition in NMuMG breast and A549 lung adenocarcinoma cell lines. ERBIN suppresses TGF‐β/SMAD signaling and reduces TGF‐β‐induced ERK phosphorylation.
Chao Li   +3 more
wiley   +1 more source

Considerations for regulation and evaluation of digital mental health technologies

open access: yesDigital Health
Digital mental health technologies (DMHTs) are becoming well established within mental health services and through direct-to-consumer models. Due to their scalable nature, DMHTs may support services to bridge the gap between demand and the available ...
Gareth Hopkin   +6 more
doaj   +1 more source

Software Quality and Quality Management [PDF]

open access: yes, 2018
All engineering disciplines have notions of product quality. Along with these notions come mechanisms and best practices ensuring that, for a given product, each item of the product has a specified quality. Furthermore, we are used to thinking that the most critical of these quality metrics are absolute.
openaire   +2 more sources

Thermostable neutral metalloprotease from Geobacillus sp. EA1 does not share thermolysin's preference for substrates with leucine at the P1′ position

open access: yesFEBS Letters, EarlyView.
Knowing how proteases recognise preferred substrates facilitates matching proteases to applications. The S1′ pocket of protease EA1 directs cleavage to the N‐terminal side of hydrophobic residues, particularly leucine. The S1′ pocket of thermolysin differs from EA's at only one position (leucine in place of phenylalanine), which decreases cleavage ...
Grant R. Broomfield   +3 more
wiley   +1 more source

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