A5066840452- Model Reduction and Neural Networks
- Chronic Lymphocytic Leukemia Research
- Multiple Myeloma Research and Treatments
- Numerical methods in engineering
- Lymphoma Diagnosis and Treatment
- Advanced Numerical Methods in Computational Mathematics
- Elasticity and Material Modeling
- Probabilistic and Robust Engineering Design
- Monoclonal and Polyclonal Antibodies Research
- Fluid Dynamics Simulations and Interactions
- Modeling and Simulation Systems
- Fluid Dynamics and Vibration Analysis
- Solid-state spectroscopy and crystallography
- Protein Degradation and Inhibitors
- Real-time simulation and control systems
- Glycosylation and Glycoproteins Research
- Inorganic Fluorides and Related Compounds
- Lattice Boltzmann Simulation Studies
- Particle physics theoretical and experimental studies
- Dark Matter and Cosmic Phenomena
- Structural Analysis and Optimization
- Numerical methods for differential equations
- Control Systems and Identification
- Advanced Condensed Matter Physics
- Chronic Myeloid Leukemia Treatments
Universidad de Zaragoza
2015-2024
Queen's University Belfast
2019-2024
Christian Medical College, Vellore
2024
Instituto Tecnológico de Aragón
2008-2023
University of Puerto Rico-Mayaguez
1964-2023
Universidad San Pablo CEU
2023
United States Department of Transportation
2023
Institute of Engineering
2006-2021
ESI Group (France)
2021
Arts et Métiers
2021
Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue these is not yet available their characteristic localizations also poorly understood. Because RNA represents direct output genetic information encoded by genomes a significant proportion cell's regulatory capabilities focused on its synthesis, processing, transport, modification translation, generation such crucial for...
We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete components with high success rates but assembly complete isoform structures poses a major challenge even when all constituent elements identified. Expression-level estimates also varied widely across methods, based on similar models. Consequently,...
The International Germanium Experiment (IGEX) has analyzed 117 mol yr of 76Ge data from its isotopically enriched (86% 76Ge) germanium detectors. Applying pulse-shape discrimination to the more recent data, lower bound on half-life for neutrinoless double-beta decay is T1/2(0ν)>1.57×1025yr (90% C.L.). This corresponds an upper in Majorana neutrino mass parameter, ⟨mν⟩, between 0.33 and 1.35 eV, depending choice theoretical nuclear matrix elements used analysis.Received 29 October...
Purpose The prognostic significance of ATM mutations in chronic lymphocytic leukemia (CLL) is unclear. We assessed their impact the context a prospective randomized trial. Patients and Methods analyzed gene 224 patients treated on Leukemia Research Fund Chronic Lymphocytic 4 (LRF-CLL4) trial with chlorambucil or fludarabine without cyclophosphamide. status was by denaturing high-performance liquid chromatography related to treatment response, survival, TP53 alterations for same patient...
We present an algorithm to learn the relevant latent variables of a large-scale discretized physical system and predict its time evolution using thermodynamically-consistent deep neural networks. Our method relies on sparse autoencoders, which reduce dimensionality full order model set with no prior knowledge coded space dimensionality. Then, second network is trained metriplectic structure those reduced so-called structure-preserving network. This data-based integrator guaranteed conserve...
Myeloma is a clonal malignancy of plasma cells. Poor-prognosis risk currently identified by clinical and cytogenetic features. However, these indicators do not capture all prognostic information. Gene expression analysis can be used to identify poor-prognosis patients this improved combination with information about DNA-level changes.Using single nucleotide polymorphism-based gene mapping in global analysis, we have homozygous deletions genes networks that are relevant myeloma pathogenesis...
Abstract Separated representations based on finite sum decompositions constitute an appealing strategy for reducing the computer resources and calculation costs by drastically number of degrees freedom that functional approximations involve (the scale linearly with dimension space in which model is defined instead exponential growing characteristic mesh‐based discretization strategies). In our knowledge use separated only possibility circumventing terrific curse dimensionality related to...
SUMMARY We introduce here a novel approach for the numerical simulation of nonlinear, hyperelastic soft tissues at kilohertz feedback rates necessary haptic rendering. This is based upon use proper generalized decomposition techniques, generalization PODs. Proper techniques can be considered as means priori model order reduction and provides physics‐based meta‐model without need prior computer experiments. The suggested strategy thus composed an offline phase, in which general computed,...
Sparse model identification by means of data is especially cumbersome if the sought dynamics live in a high dimensional space. This usually involves need for large amount data, unfeasible such settings. well‐known phenomenon, coined as curse dimensionality, here overcome use separate representations. We present technique based on same principles Proper Generalized Decomposition that enables complex laws low‐data limit. provide examples performance up to ten dimensions.