Results 131 to 140 of about 34,112,328 (298)

Circular RNA expression landscapes in myelodysplastic neoplasms: Associations with mutational signatures and disease progression

Molecular Oncology, EarlyView.
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge, Morten Tulstrup, Gabriele Todisco, Pedro Moura, Christophe Côme, Jakob Werner Hansen, Jakob Schmidt Jespersen, Balthasar Schlotmann, Maria Creignou, Mette Dahl, Claudia Schöllkopf, Klas Raaschou‐Jensen, Krister Wennerberg, Bo Porse, Joachim Weischenfeldt, Eva Hellström‐Lindberg, Lasse Sommer Kristensen, Kirsten Grønbæk   +17 more
wiley   +1 more source

Large-scale data-driven financial risk assessment

, 2019
The state of data in finance makes near real-time and consistent assessment of financial risks almost impossible today. The aggregate measures produced by traditional methods are rigid, infrequent, and not available when needed.
Breymann, Wolfgang, Heitz, Jonas, Stockinger, Kurt, Nils Bundi, Jonas Heitz, Johannes Micheler, Bundi, Nils, Wolfgang Breymann, Micheler, Johannes, Kurt Stockinger   +9 more
core   +1 more source

IMPDH inhibition enhances cytarabine efficacy in SAMHD1‐expressing leukaemia cells via guanine nucleotide depletion

Molecular Oncology, EarlyView.
Cytarabine is a key therapy for acute myeloid leukaemia (AML), but its efficacy is limited by the dNTPase SAMHD1, which hydrolyses its active metabolite. Screening nucleotide biosynthesis inhibitors revealed that IMPDH inhibitors selectively sensitise SAMHD1‐proficient AML cells to cytarabine.
Miriam Yagüe‐Capilla, Christopher Dirks, Caroline Eiden, Sonja K. Fesenmayer, Femke M. Hormann, Yolande Klootsema, Ingrid Lilienthal, Si Min Zhang, Nikolas Herold, Sean G. Rudd   +9 more
wiley   +1 more source

stefdeli/Data-driven-Adaptive-Benders-Decomposition: Data-Driven Adaptive Benders Decomposition

, 2019
Python codes and data from the paper ``Data-driven Adaptive Benders Decomposition for the Stochastic Unit Commitment ...
Stefanos Delikaraoglou
core   +1 more source

Adaptive Droop Gain Control for Optimal Kinetic Energy Extraction From Wind Turbines to Support System Frequency

IEEE Access
Low-inertia power grids would benefit from frequency support from inverter-based generation, given the scarcity of synchronous generators as decarbonisation efforts progress.
Qian Chen, Luis Badesa, Zhongda Chu, Goran Strbac   +3 more
doaj   +1 more source

KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer

Molecular Oncology, EarlyView.
Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan, Veronika M Metzler, Simone de Brot, Corinne L Woodcock, Anna E Harris, Jennifer Lothion‐Roy, Emeli M Nilsson, Atara Ntekim, Michael S Toss, Jenny L Persson, Francesca Khani, Brian D Robinson, Lorraine J Gudas, Emad Rakha, David M Heery, Catrin S Rutland, Nigel P Mongan   +16 more
wiley   +1 more source

Evolution of Lung Function within Individuals: Clinical Insights and Data-driven Methods. [PDF]

Am J Respir Crit Care Med, 2023
Custovic A, Fontanella S.
europepmc   +1 more source

Transcriptional profiling of circulating extracellular vesicles from prebiopsy prostate cancer patients

Molecular Oncology, EarlyView.
RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner, Pierre Tennstedt, Randi C. Pose, Christian Müller, Katharina Besler, Svenja Schneegans, Malik Alawi, Marie C. Roesch, Sven Peine, Desiree Bonci, Joanna Budna‐Tukan, Evi Lianidou, Catherine Alix‐Panabières, Derya Tilki, Klaus Pantel   +14 more
wiley   +1 more source

Data-driven methods to quantify high-dimensional correlated uncertainties

, 2019
1
CHOI, MINSEOK
core  

Addressing Concerns about Single Path Analysis in Business Cycle Turning Points: The Case of Learning Vector Quantization

Mathematics
Data-driven approaches in machine learning are increasingly applied in economic analysis, particularly for identifying business cycle (BC) turning points.
David Enck, Mario Beruvides, Víctor G. Tercero-Gómez, Alvaro E. Cordero-Franco   +3 more
doaj   +1 more source