Results 111 to 120 of about 131,766 (331)

OPTIMIZING SOFTWARE DEFECT PREDICTION USING A HYBRID NEURAL NETWORK WITH WEIGHTED MODIFIED CUCKOO SEARCH [PDF]

open access: yesProceedings on Engineering Sciences
Flaws significantly impact the quality, dependability, and maintenance of software. Discovering flaws before they appear in production environments is possible using data mining and classification algorithms.
Devi Priya Gottumukkala   +2 more
doaj   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

open access: yesMolecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova   +25 more
wiley   +1 more source

Feature selection using the zebra optimization algorithm for software fault prediction: a study on the bughunter dataset

open access: yesTạp chí Khoa học và Công nghệ
Software fault prediction focuses on identifying software modules that are most likely to contain faults before the testing stage, helping developers allocate quality assurance resources effectively and improve system reliability.
Ha Thi Minh Phuong   +3 more
doaj   +1 more source

Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra   +6 more
wiley   +1 more source

ATG4B is required for mTORC1‐mediated anabolic activity and is associated with clinical outcomes in non‐small cell lung cancer

open access: yesFEBS Open Bio, EarlyView.
The relationship between anabolic and catabolic processes governing lung cancer cell growth is nuanced. We show that ATG4B, an autophagy regulator, is elevated in lung cancer and that high ATG4B is associated with worse patient outcomes. Targeting ATG4B in cells reduces growth, protein synthesis, and mTORC1 activity, demonstrating a new relationship ...
Patrick J. Ryan   +6 more
wiley   +1 more source

Empirical studies on feature selection for software fault prediction [PDF]

open access: gold, 2013
Jiaqiang Chen   +4 more
openalex   +1 more source

Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction

open access: hybrid, 2023
Sonika Chandrakant Rathi   +5 more
openalex   +1 more source

Diabetes‐induced vascular calcification is associated with low pyrophosphate and its oral supplementation prevents calcification in diabetic mice

open access: yesFEBS Open Bio, EarlyView.
Induction of diabetes in three different mouse strains uniformly resulted in an increase in TNAP activity and a reduction in pyrophosphate (PPi) in the circulation. Inhibition of TNAP restored plasma PPi. Diabetes‐induced calcification in the media layer of the aorta was detected only in the Abcc6−/− strain, which is predisposed to ectopic ...
Krisztina Fülöp   +13 more
wiley   +1 more source

Software fault prediction of unlabeled program modules

open access: yes, 2009
Software metrics and fault data belonging to a previous software version are used to build the software fault prediction model for the next release of the software. Until now, different classification algorithms have been used to build this kind of models. However, there are cases when previous fault data are not present; and hence, supervised learning
Catal, C., Sevim, U., Diri, B.
openaire   +2 more sources

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