scadsfct > disease

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2Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease
V. Friedrich, P. Pennitz, E. Wyler, J. Adler, D. Postmus, K. Müller, L. Teixeira Alves, J. Prigann, F. Pott, D. Vladimirova and 10 other author(s). eBioMedicine, (2024)
9 days ago by @scadsfct
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Disease
Cross-species
model,
learning
Deep
matching,
Single-cell
RNA-seq,
COVID-19,
analysis,
state
Hamster
DiseaseCross-speciesmodel,learningDeepmatching,Single-cellRNA-seq,COVID-19,analysis,stateHamster
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2Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs
A. Hannemann, J. Ewald, L. Seeger, and E. Buchmann. Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV, page 279–293. Berlin, Heidelberg, Springer-Verlag, (2024)
9 days ago by @scadsfct
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Prognosis
Learning,
Type
Disease
Classification,
Federated
Cell
PrognosisLearning,TypeDiseaseClassification,FederatedCell
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1Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants
S. Mukherjee, T. Cassini, N. Hu, T. Yang, B. Li, W. Shen, C. Moth, D. Rinker, J. Sheehan, J. Cogan and 8 other author(s). Human Genetics and Genomics Advances, 3 (4): 100131 (2022)
2 months ago by @scadsfct
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developmental
variant,
disease
molecular
encephalopathy,
electrophysiology,
Diseases
simulations,
personalized
structural
rare
dynamics
interpretation,
epileptic
KCNC2,
and
DEE,
variant
Network,
Undiagnosed
biology,
developmentalvariant,diseasemolecularencephalopathy,electrophysiology,Diseasessimulations,personalizedstructuralraredynamicsinterpretation,epilepticKCNC2,andDEE,variantNetwork,Undiagnosedbiology,
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2Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection
D. Kiakou, A. Adamopoulos, and N. Scherf. Worldwide Congress on “Genetics, Geriatrics and Neurodegenerative Diseases Research", page 223--230. Springer, (2022)
7 days ago by @scadsfct
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Neuroimaging
Investigating
Selection
Impact
Disease
Graph-Based
Prediction
learning
Feature
NeuroimagingInvestigatingSelectionImpactDiseaseGraph-BasedPredictionlearningFeature
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1Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network
S. Mukherjee, J. Cogan, J. Newman, J. Phillips, 3rd, R. Hamid, Undiagnosed Diseases Network, J. Meiler, and J. Capra. Am. J. Hum. Genet., 108 (10): 1946--1963 (October 2021)
2 months ago by @scadsfct
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disease;
prediction;
disease
learning;
Network;
oligogenic
Diseases
clinical
digenic
rare
machine
topic_lifescience
Undiagnosed
UDN;
disease;prediction;diseaselearning;Network;oligogenicDiseasesclinicaldigenicraremachinetopic_lifescienceUndiagnosedUDN;
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2Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease

2Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs

1Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants

2Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection

1Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network

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publications (hide)5 displayallpublications onlypublications per page5102050100 sort byadded attitleauthorpublication dateentry typehelp for advanced sorting... RSSBibTeXRDFmore...

2Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease

2Federated Learning on&nbsp;Transcriptomic Data: Model Quality and&nbsp;Performance Trade-Offs

1Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants

2Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection

1Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network

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2Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs