Results 111 to 120 of about 6,217,824 (300)
Software evolution through intentional classifications
, 2002 Maintaining and evolving large software systems is hard. One of the main underlying causes is that existing modularisation mechanisms are inadequate to handle cross-cutting concerns.
Annual meeting of the FWO research network on Formal Foundations of Software Evolution +2 more
core
Molecular Oncology, EarlyView.Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park +6 more
wiley +1 more source
Modeling History to Understand Software Evolution [PDF]
, 2005 Over the past three decades, more and more research has been spent on understanding software evolution. The development and spread of versioning systems made valuable data available for study.
Tudor Gîrba, Gîrba, Tudor
core +1 more source
Molecular Oncology, EarlyView.Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach +9 more
wiley +1 more source
Molecular Oncology, EarlyView.LUNAR is a liver‐specific long noncoding RNA (lncRNA) that is highly expressed in normal liver but becomes epigenetically silenced in hepatocellular carcinoma through promoter hypermethylation. Loss of LUNAR is associated with NOTCH activation, epithelial–mesenchymal transition, and metastasis, whereas restoring LUNAR restrains metastatic progression ...
Se Ha Jang +9 more
wiley +1 more source
Molecular Oncology, EarlyView.This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi +6 more
wiley +1 more source
Supporting Compositional Styles for Software Evolution
, 2000 Software is not just difficult to develop, but it is even more difficult to maintain in the face of changing requirements. The complexity of software evolution can, however, be significantly reduced if we manage to separate the stable artifacts (the ...
Achermann, Franz, Nierstrasz, Oscar
core +1 more source
Molecular Oncology, EarlyView.Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou +4 more
wiley +1 more source
The Evolution of Software Effort Estimation Models
JISR on Computing– Software effort estimation is the process of estimating the amount of time, effort, and money required to develop and manage software. It has an important role in software project planning and management.
Adeen Iftikhar +5 more
doaj +1 more source
Towards a Taxonomy of Software Evolution [PDF]
Previous taxonomies of software evolution have focused on the purpose of the change rather than the underlying mechanisms. This paper proposes a taxonomy of software evolution based on the characterizing mechanisms of change and the factors that ...
Mens, Tom +3 more
core +1 more source