1、本學期將選擇與Copy Number Transformation Problem 相關的學術論文。
2、Copy Number Transformation Problem 的意義：
a、在物種進化與癌症的研究裡，基因組重新排列(genome rearrangement)是個核心問題。過去20年，以計算方法對此問題的研究，大部分是在探討物種進化。目前卻有絕佳的機會，以計算方法研究癌症基因組的進化。物種進化以百萬年為單位，
其基因突變，一代傳一代。而一個個體內癌症的基因突變，就只在幾十年內發生。2005年開始的 The Cancer Genome Atlas 計畫，目的即在收集癌症基因突變數據，有利於以計算方法研究癌症的基因突變。
b、癌症是個動態過程，快速的突變，形成複雜的腫瘤基因組。其中，有很多的突變，是整段DNA 的剔除或複製(deletions and amplifications)，使得腫瘤基因組內的基因個數(copy number profile)，不斷改變，且與正常基因組不同。
了解它們的不同，可幫助我們預測疾病的進展與可能的醫療介入。
c、以計算方法了解正常基因組與各階段腫瘤基因組的差異，方法之一為訂出其copy number profile的距離。此概念目前並未有太多探討。本課程選擇的Copy Number Transformation Problem 相關的學術論文，和此有關。

1. This semester, academic papers related to Copy Number Transformation Problem will be selected.
2. The meaning of Copy Number Transformation Problem:
a. In the study of species evolution and cancer, genome rearrangement is a core issue. In the past 20 years, most of the computational research on this issue has been about species evolution. However, there are excellent opportunities to study the evolution of cancer genomes computationally. The evolution of species is measured in millions of years.
Its genetic mutations are passed from generation to generation. Cancer gene mutations in an individual only occur within a few decades. The Cancer Genome Atlas project, started in 2005, aims to collect cancer gene mutation data to facilitate the study of cancer gene mutations using computational methods.
b. Cancer is a dynamic process, with rapid mutations forming complex tumor genomes. Among them, there are many mutations, which are deletions and amplifications of entire sections of DNA, causing the gene number profile (copy number profile) in the tumor genome to constantly change and differ from the normal genome.
Understanding their differences can help us predict disease progression and possible medical intervention.
c. Use calculation methods to understand the differences between the normal genome and the tumor genome at various stages. One method is to determine the distance between their copy number profiles. This concept has not been explored much yet. The academic papers related to Copy Number Transformation Problem selected for this course are related to this.

何謂 “計算生物學” (或稱生物資訊學)? DNA由a,t,c,g 4個字母組合而成，如下例即為一串DNA序列(sequence)： atgcactctt caatagtttt ggccaccgtg ctctttgtag cgattgcttc agcatcaaaa acgcgagagc tatgcatgaa atcgctcgag catgccaagg ttggcaccag caaggaggcg (習慣上，每10個字母寫成一小串，小串間以一“空白”隔開。此例計有120個字母，我們稱其長度為120) 人類DNA總長為30億，這30億個字母決定了一個人。1988年開始的人類基因計劃的主要目的，就是將這30億個字母寫出來。而這些字母是如何運作的，則有待進一步了解。這些隱藏於字母中的生命秘密，我們稱之為生物資訊(Biological information)。 DNA會製造出蛋白質，以營造活生生的生命。蛋白質由20個英文字母 (各代表一種氨基酸)組合而成，長度從數十至數百都有，如下例即為一條蛋白質序列： mhssivlatv lfvaiasask trelcmksle hakvgtskea kqdgidlykh mfehypamkk yfkhrenytp advqkdpffi kqgqnillac hvlcatyddr etfdayvgel marherdhvk 人類約有2萬條不同的蛋白質。這些蛋白質如何營造出生命，有待進一步了解。這些隱藏於字母中的秘密，也是所謂的生物資訊(Biological information)。 研究DNA如何運作及蛋白質如何營造生命, 也就是研究生物資訊(Biological information)，是今日蓬勃發展的“生命科學”之目的。 所謂“生物序列”(Biological sequence)，指的是DNA序列或蛋白質序列。 提出有效的生物序列分析方法(演算法或模型)，以計算機為工具，挖掘隱藏在大量字母裡的生物資訊，我們稱之為“計算生物學”(Computational Biology)，或稱之為“生物資訊學”(Bioinformatics)。

What is "computational biology" (or bioinformatics)? DNA is composed of 4 letters a, t, c, g. The following example is a DNA sequence: atgcactctt caatagtttt ggccaccgtg ctctttgtag cgattgcttc agcatcaaaa acgcgagagc tatgcatgaa atcgctcgag catgccaagg ttggcaccag caaggaggcg (Conventionally, every 10 letters are written in a small string, separated by a "blank". In this example, there are 120 letters, and we call the length 120) The total length of human DNA is 3 billion, and these 3 billion letters determine a person. The main purpose of the Human Genome Project, started in 1988, is to write out these 3 billion letters. How these letters work remains to be understood. These secrets of life hidden in letters are called biological information. DNA makes proteins to create living life. Proteins are composed of 20 English letters (each representing an amino acid), and the length ranges from tens to hundreds. The following example is a protein sequence: mhssivlatv lfvaiasask trelcmksle hakvgtskea kqdgidlykh mfehypamkk yfkhrenytp advqkdpffi kqgqnillac hvlcatyddr etfdayvgel marherdhvk Humans have approximately 20,000 different proteins. How these proteins create life remains to be understood. These secrets hidden in letters are also so-called biological information. Studying how DNA works and how proteins create life, that is, studying biological information, is the purpose of today's booming "life sciences." The so-called "biological sequence" refers to a DNA sequence or a protein sequence. Proposing effective biological sequence analysis methods (algorithms or models), using computers as tools to mine biological information hidden in a large number of letters, we call it "Computational Biology", or "Bioinformatics".

學術論文

academic papers