Results 151 to 160 of about 14,528 (304)
Advanced Science, EarlyView.SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang +8 more
wiley +1 more source
Hardware Architecture of Tree Structure for Real-time Progressive Sequential Pattern Mining
, 2007 傳統的循序樣式探勘演算法需要龐大的計算時間。當面臨累進式資料庫探勘時所需要的時間更多。在本論文中，我們設計了一種硬體的樹狀結構，用來解決累進式循序樣式探勘的問題。我們的演算法簡稱為HATS，運用樹狀結構代表每一個序列中的循序元素。透過管線設計，HATS可以高效率的產生循序元素。我們透過軟硬體共同設計，在可規劃邏輯閘陣列上，完成實體電路的設計與驗証。我們的實驗結果也顯示HATS不僅在隨機的測試資料中，明顯地比現有的所有循序樣式探勘演算法快速；並且對於一個在無線閘道的實際應用上表現優異 ...
Chen, Bo-Han, 陳伯翰
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Advanced Science, EarlyView.Dual targeting of ANGPTL3 and IL‐33/ST2 attenuates diabetic kidney disease by reprogramming lipid–inflammatory crosstalk. This strategy reduces renal lipotoxicity, suppresses inflammatory activation, and limits fibrotic remodeling, thereby preserving kidney structure and function and highlighting a mechanism‐guided therapeutic approach for metabolic ...
Zhuojin Li +8 more
wiley +1 more source
Advanced Science, EarlyView.ABHD17C‐mediated depalmitoylation of BCL6B at Cys442 blocks its nuclear import and triggers ubiquitin‐dependent degradation, attenuating transcriptional repression of the anti‐phagocytic signal CD24. This mechanism enables pancreatic cancer cells to evade macrophage phagocytosis and fosters an immunosuppressive microenvironment.
Yalu Zhang +9 more
wiley +1 more source
, 2001 Discovering associations is one of the fundamental tasks of data mining. Its aim is to automatically seek for dependencies from vast amounts of data. The task results in socalled association rules, which are of form: If A occurs in the data then B occurs also. Only those rules that occur in the data frequently enough are generated.
openaire +2 more sources
Efficient Sequential Pattern Mining by Breadth-First Approach
, 2007 自從GSP演算法提出之後，許多相關的演算法被提出來且大多專注在找尋所有序列樣式。CloSpan演算法首先提出找尋封閉集合。封閉集合比全集合更精簡有效，且具有相同的表達能力。因此，CloSpan就以PrefixSpan演算法為基礎，加上兩個其稱為backward sub-pattern與backward super-pattern的刪減技巧，有效地找出封閉集合。 因此我們提出一個新的演算法以找尋封閉集合。然而不同於之前演算法多採深度優先的策略，我們的演算法是屬於廣度優先的方法。另外 ...
張耕源, Chang, Keng-Yuan
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Advanced Science, EarlyView.SIRT6‐mediated ATF3 acetylation drives MGARP transcription and mitochondrial dysfunction in macrophages, promoting macrophage senescence and pulmonary fibrosis. Mechanistically, HSP70/Importin α competitively binds to ATF3, modulating its nuclear translocation.
Demin Cheng +18 more
wiley +1 more source
Hiding Fuzzy Sequential Patterns by a Multi-Objective Scheme
International Journal of Information and Communication Technology Research, 2016 Improvements in technology have led to generating and mining huge amounts of data. Sequence mining is a research area of data mining that aims to extract useful knowledge from raw databases.
Olya Sadat Behbahani +2 more
doaj
Advanced Science, EarlyView.This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley +1 more source
Mining fuzzy time sequential patterns
, 2010 碩士 挖掘序列型樣是資料挖掘中一項重要的技術，主要用於找出序列資料庫中的頻繁子序列。一般挖掘序列型樣的演算法大多能正確找出頻繁項目集之間的發生先後順序，但對於其出現前後的間隔時間卻無法加以描述。 為了有效解決此一問題，本研究結合階層式分群法與模糊數的概念，提出一個挖掘模糊時間序列型樣的演算法，不僅可以挖掘出序列資料庫中所有頻繁項目及其出現的順序關係，更可將其出現的間隔時間以合理的方式表示。An important task of sequential patterns mining is to ...
廖珮妤; Liao, Pei-yu
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