Results 121 to 130 of about 325,444 (301)
Dimension reduction for path signatures
CoRRThis paper focuses on the mathematical framework for reducing the complexity of models using path signatures. The structure of these signatures, which can be interpreted as collections of iterated integrals along paths, is discussed and their applications in areas such as stochastic differential equations (SDEs) and financial modeling are pointed out ...
Christian Bayer 0001, Martin Redmann
openaire +2 more sources
Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
JSDRlib : a java library for sufficient dimension reduction
, 2013 碩士充分維度縮減法 (sufficient dimension reduction, SDR) 可以找出有效的維度縮減方向來探索高維度資料的內在結構。本論文以 Java 程式語言開發一個充分維度縮減法的函式庫，稱做jSDRlib，實作了SIR、SAVE、pHd、及 IRE 等等估計中央子空間 (central subspace) 的方法；同時提供了相關的卡方檢定來判定維度縮減個數。我們的目的在利用 Java 語言跨平台的特性，提供使用者一個具擴充性的維度縮減資料分析工具。應用所開發的函式庫 ...
胡肇元; Hu, Jhao-Yuan
core
Research on manufacturing text classification based on improved genetic algorithm
Brazilian Archives of Biology and TechnologyAccording to the features of texts, a text classification model is proposed. Base on this model, an optimized objective function is designed by utilizing the occurrence frequency of each feature in each category.
Zhou Kaijun, Tong Yifei
doaj +1 more source
Parsimonious Tensor Dimension Reduction
Journal of Computational and Graphical StatisticsTensor data is emerging in many scientific applications, such as multi-tissue transcriptomics. In such cases, the covariates for each individual are no longer a vector. To apply traditional vector-based methods to this type of data, we need to either do the vectorization or analyze data marginally, which suffers a significant information loss.
Xin Xing +3 more
openaire +1 more source
COMP–PMEPA1 axis promotes epithelial‐to‐mesenchymal transition in breast cancer cells
Molecular Oncology, EarlyView.This study reveals that cartilage oligomeric matrix protein (COMP) promotes epithelial‐to‐mesenchymal transition (EMT) in breast cancer. We identify PMEPA1 (protein TMEPAI) as a novel COMP‐binding partner that mediates EMT via binding to the TSP domains of COMP, establishing the COMP–PMEPA1 axis as a key EMT driver in breast cancer.
Konstantinos S. Papadakos +6 more
wiley +1 more source
Molecular Oncology, EarlyView.Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
wiley +1 more source
Review of sparse sufficient dimension reduction: comment
Statistical Theory and Related Fields, 2020 Liping Zhu
doaj +1 more source
Molecular Oncology, EarlyView.Targeted therapy was evaluated in SHH medulloblastoma using neuroepithelial stem cell (NES) and tumor‐derived NES‐like (tNES) models in 2D monolayers and 3D spheroids. PI3K, AKT, and CDK4/6 inhibitors had minimal effects in NES but markedly reduced viability and growth and induced apoptosis in tNES cells, revealing distinct therapeutic vulnerabilities.
Monika Lukoseviciute +4 more
wiley +1 more source
Effective feature extraction and data reduction with hyperspectral imaging in remote sensing
, 2014 Although PCA has been widely used for feature extraction and data reduction, it suffers from three main drawbacks: high computational cost, large memory requirement and low efficacy in processing large datasets such as HSI.
Zabalza, Jaime +3 more
core +1 more source