Results 31 to 40 of about 19,735 (267)

Finding novel vulnerabilities of hypomorphic BRCA1 alleles

Molecular Oncology, EarlyView.
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder, Klaas de Lint, Hồ Mỹ Phúc Võ, Mariana M. Góis, Rosalie A. Kampen, Marta San Martin Alonso, Ilse Nootenboom, Veronica Garzero, Tiemen J. Wendel, Rob M. F. Wolthuis, Sylvie M. Noordermeer   +10 more
wiley   +1 more source

Data sanitization in association rule mining based on impact factor [PDF]

Journal of Artificial Intelligence and Data Mining, 2015
Data sanitization is a process that is used to promote the sharing of transactional databases among organizations and businesses, it alleviates concerns for individuals and organizations regarding the disclosure of sensitive patterns.
A. Telikani, A. Shahbahrami, R. Tavoli
doaj   +1 more source

MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis

FEBS Open Bio, EarlyView.
MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss, Ao Li, Eduardo H. Gilglioni, Mayank Bansal, Sumeet Pal Singh, Latifa Bakiri, Alessandra K. Cardozo, Esteban N. Gurzov   +7 more
wiley   +1 more source

Adaptive-Miner: an efficient distributed association rule mining algorithm on Spark

Journal of Big Data, 2018
Extraction of valuable data from extensive datasets is a standout amongst the most vital exploration issues. Association rule mining is one of the highly used methods for this purpose.
Sanjay Rathee, Arti Kashyap
doaj   +1 more source

Identification and characterisation of calcitonin receptor isoforms expressed in glioblastoma derived glioma stem and U‐87 MG cells

FEBS Open Bio, EarlyView.
Glioblastoma cells express calcitonin receptor variants (CT receptor isoforms) that may help them survive stress. Using qPCR, transcript‐specific long‐read nanopore sequencing, immunofluorescence co‐localisation and comparative sequence analysis, this study identifies a novel alternatively spliced CALCR transcript that encodes the CTb receptor isoform ...
Pragya Gupta, Sebastian GB Furness, Tahereh Gharbi, Ric De Paoli‐Iseppi, Shweta S. Joshi, Michael Clark, David L. Hare, Peter Wookey   +7 more
wiley   +1 more source

Association rules recommendation algorithm supporting recommendation nonempty

Tongxin xuebao, 2017
Existing association rule recommendation technologies were focus on extraction efficiency of association rule in data mining.However,it lacked consideration of recommendation balance between popular and unusual data and efficient processing.In order to ...
Ming HE, Wei-shi LIU, Jiang ZHANG
doaj   +2 more sources

Particle Swarm Optimization-Based Association Rule Mining in Big Data Environment

IEEE Access, 2019
With the explosive growth of information data in today's society, the continuous accumulation and increase of data in recent years make it difficult to extract useful information from it, so data mining comes into being.
Tong Su, Haitao Xu, Xianwei Zhou
doaj   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

niarules: Advancing interpretable machine learning through numerical association rule mining and 3D coral plot visualization

SoftwareX
Numerical association rule mining remains comparatively underexplored in interpretable machine learning, largely due to the challenges of handling continuous variables and the limited availability of effective visualization techniques.
Iztok Fister Jr, Gerlinde Emsenhuber, Jan Hendrik Plümer, Iztok Fister, Andreas Holzinger   +4 more
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source