Uniform manifold approximation and projection
J Healy, L McInnes - Nature Reviews Methods Primers, 2024 - nature.com
Uniform manifold approximation and projection is a nonlinear dimension reduction method
often used for visualizing data and as pre-processing for further machine-learning tasks …
often used for visualizing data and as pre-processing for further machine-learning tasks …
ARC–MOF: a diverse database of metal-organic frameworks with DFT-derived partial atomic charges and descriptors for machine learning
Metal–organic frameworks (MOFs) are a class of crystalline materials composed of metal
nodes or clusters connected via semi-rigid organic linkers. Owing to their high-surface area …
nodes or clusters connected via semi-rigid organic linkers. Owing to their high-surface area …
The oncogenic fusion protein DNAJB1-PRKACA can be specifically targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma
The DNAJB1-PRKACA fusion transcript is the oncogenic driver in fibrolamellar
hepatocellular carcinoma, a lethal disease lacking specific therapies. This study reports on …
hepatocellular carcinoma, a lethal disease lacking specific therapies. This study reports on …
Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex
Cortical circuits are thought to contain a large number of cell types that coordinate to
produce behavior. Current in vivo methods rely on clustering of specified features of …
produce behavior. Current in vivo methods rely on clustering of specified features of …
Cagra: Highly parallel graph construction and approximate nearest neighbor search for gpus
Approximate Nearest Neighbor Search (ANNS) plays a critical role in various disciplines
spanning data mining and artificial intelligence, from information retrieval and computer …
spanning data mining and artificial intelligence, from information retrieval and computer …
Global and local structure preserving GPU t-SNE methods for large-scale applications
Currently, the use of dimensionality reduction techniques such as t-distributed stochastic
neighbor embedding (t-SNE) to visualize data has become essential in dealing with large …
neighbor embedding (t-SNE) to visualize data has become essential in dealing with large …
Immune surveillance of acute myeloid leukemia is mediated by HLA-presented antigens on leukemia progenitor cells
A Nelde, H Schuster, JS Heitmann, J Bauer… - Blood Cancer …, 2023 - AACR
Therapy-resistant leukemia stem and progenitor cells (LSC) are a main cause of acute
myeloid leukemia (AML) relapse. LSC-targeting therapies may thus improve outcome of …
myeloid leukemia (AML) relapse. LSC-targeting therapies may thus improve outcome of …
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection
Malware detection is an interesting and valuable domain to work in because it has
significant real-world impact and unique machine-learning challenges. We investigate …
significant real-world impact and unique machine-learning challenges. We investigate …
Intraoperative assessment of tumor margins in tissue sections with hyperspectral imaging and machine learning
D Pertzborn, HN Nguyen, K Hüttmann, J Prengel… - Cancers, 2022 - mdpi.com
Simple Summary The complete resection of the malignant tumor during surgery is crucial for
the patient's survival. To date, surgeons have been intraoperatively supported by information …
the patient's survival. To date, surgeons have been intraoperatively supported by information …
Building interpretable predictive models with context-aware evolutionary learning
Building prediction models with the right balance between performance and interpretability
is currently a great challenge in machine learning. A large number of recent studies have …
is currently a great challenge in machine learning. A large number of recent studies have …