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Application of Bootstrap Method in Cell Migration Analysis

Application of Bootstrap Method in Cell Migration Analysis. 第八組 R02548059 曹舜皓 R03548003 陳吉麟. Cell Mirgration. Wound healing / Morphogenesis Stimulation Directionality & Speed. Galvanotaxis. a phenomenon where electric fields (EFs) direct cell migration

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Application of Bootstrap Method in Cell Migration Analysis

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  1. Application ofBootstrap Method in Cell Migration Analysis 第八組 R02548059 曹舜皓 R03548003 陳吉麟

  2. Cell Mirgration • Wound healing / Morphogenesis • Stimulation • Directionality & Speed

  3. Galvanotaxis • a phenomenon where electric fields (EFs) direct cell migration • involved in wound healing and development • the mechanisms are still not fully understood • Electrophoretic and electro-osmotic forces • redistribute cell surface molecules • direct cell migration

  4. Difficulties • Only a few cells can be observed by microscope during the experiment • Not a normal distribution • Data is insufficient

  5. Bootstrap Method 優點: • 在使用上對原始的樣本分佈沒有特別限制 • 利用多次取樣可以將原始的小樣本集合增加 • 經過多次的取樣，Bootstrap樣本的分佈會接近常態分佈 (CLT) 方法: 將原始的樣本集合進行再抽樣，任意抽取1個樣本記錄數值後再放回 重複步驟1. n次 得到第一組樣本集合，算出統計數值 重複前兩個步驟B次，故總共有B個統計數值 ….. 利用新的Bootstrap樣本(B個)做統計計算

  6. Bootstrap Method 3 6 …. 4 1 6 6 …. 5 1 5 56 …. 4 6 4 2 3 1 6 4 6 …. 1 1 Mean

  7. Application i j i + j i + j ….. ….. Cell 1 ….. ….. i + j Cell 2 ….. ….. Cell 3 i + j i + j ….. ….. Cell 4 Cell 5 求出平均角度與標準差

  8. Application H0: 無特別方向偏好(其機率在各方向機率平均兩倍標準差內) H1: 有方向偏好(其機率大於或小於各方向機率平均兩倍標準差)

  9. Accuracy 在一次的抽取中，每一筆原始樣本被抽到的機率為沒抽到機率為1 因此n次的抽取都沒抽到某個樣本的機率為 當抽取數n->∞ = a =ln(a) x=1/n = ln(a) L'Hôpital'srule = ln(a) a= = 0.3678 => 一直沒觀察到某樣本的機率 =>Bootstrap沒觀察到的樣本佔原始樣本的比例

  10. Accuracy 被抽到 沒被觀察到但 也符合預測模 型的資料 未抽到 正確 該次抽取未抽取到的資料且符 合該次抽取所得模型的數量 / 未抽取到資料的數量 權重分配: 沒觀察到的資料: 佔原始資料36.8% 0.632* 沒觀察到的資料但也符合模型的正確性 => 模型預測能力高，故權重高 0.368 * 原始資料符合模型的正確性 => 模型在原始資料預測能力 原始資料且符合該次抽取所得 模型的數量 / 原始資料的數量 註:模型 -> 例如細胞的平均方向及標準差 Data mining concepts and techniques / Jiawei Han, MichelineKamber

  11. References • http://en.wikipedia.org/wiki/Bootstrapping • http://sjchen.im.nuu.edu.tw/DataMining/final/Classification.pdf • Data mining concepts and techniques / Jiawei Han, MichelineKamber

  12. Thanks for your listening

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