Network shape intelligence outperforms AlphaFold2 intelligence in vanilla protein interaction prediction. bioRxiv, August 2023. [PUMA: AlphaFold2 protein xack prediction interaction intelligence vanilla]
Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J. Pathol., (256)3:269--281, Wiley, March 2022. [PUMA: metastasis; bowel predictive adipose intelligence digital biomarker artificial prediction zno tissue; pathology inflamed deep cancer learning LNM pT2 pT1 AI; colorectal and topic_lifescience new early]
Destination Prediction Based on Partial Trajectory Data. 2020. [PUMA: Destination Partial Prediction data Trajectory zno Based on] URL
Accuracy of RNA Structure Prediction Depends on the Pseudoknot Grammar. Advances in Bioinformatics and Computational Biology, 20–31, Springer Nature Switzerland, 2022. [PUMA: DependsPseudoknot nopdf RNA Prediction Grammar Structure] URL
Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network. J. Med. Imaging (Bellingham), (10)4:044502, SPIE-Intl Soc Optical Eng, July 2023. [PUMA: imaging stroke medical neural machine prediction learning multi-modal topic_visualcomputing networks graph yaff]
Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection. Worldwide Congress on “Genetics, Geriatrics and Neurodegenerative Diseases Research", 223--230, 2022. [PUMA: Neuroimaging Investigating Selection Impact Disease Graph-Based Prediction topic_neuroinspired learning Feature yaff]
Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: models modeling Theory Consciousness algorithms Prediction data learning Information Modeling Complexity Processing Syndrome Training Neuroscience Measures Predictive and machine Locked-In processing zno Signal Computational]
RosettaCM for antibodies with very long HCDR3s and low template availability. Proteins, (89)11:1458--1472, Wiley, November 2021. [PUMA: homology loop modeling antibody topic_lifescience prediction zno Rosetta benchmark structure]
Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction. J. Biomol. NMR, (77)3:69--82, June 2023. [PUMA: membrane (PCSs) Click chemistry proteins (ncAAs) acids (IMPs) Non-canonical amino topic_lifescience shifts prediction zno Rosetta Structure Integral Pseudocontact]
Sequence models for continuous cell cycle stage prediction from brightfield images. Medical Imaging with Deep Learning, 2025. [PUMA: brightfield_images prediction Sequence_models yaff] URL
RNA secondary structures with limited base pair span: Exact backtracking and an application. Genes (Basel), (12)1:14, MDPI AG, December 2020. [PUMA: RNA elements secondary scanning prediction hyper-stable algorithm yaff structure]
PredicTF: prediction of bacterial transcription factors in complex microbial communities using deep learning. Environmental Microbiome, (17)December 2022. [PUMA: microbialdeep bacterial PredicTF: transcription complex prediction learning zno]
Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network. Am. J. Hum. Genet., (108)10:1946--1963, Elsevier BV, October 2021. [PUMA: disease Network rare Undiagnosed_clinical_digenic machine topic_lifescience prediction learning zno oligogenic Diseases UDN]
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: a imaging or disease liver multivariable TACE non-alcoholic multimodal artificial prediction support integration NAFLD TRIPOD deep neural Digital network transarterial fatty topic_lifescience Diagnosis DICOM ML steatohepatitis microvascular convolutional NASH in HCC AI Communications images intelligence hepatocellular Reporting chemoembolisation system Medicine carcinoma invasion Transparent Individual slide machine zno MVI Prognosis CNN data for learning whole WSIs of and Imaging diagnostic model]
Utilizing transformers on OCT imagery and metadata for treatment response prediction in macular edema patients. Lecture Notes in Computer Science, 3--15, Springer Nature Switzerland, Cham, 2023. [PUMA: macular transformers edema response topic_lifescience xack prediction OCT treatment]