TC_Chu's Point

箱子 秩序的開始 生命的來源

星期一12/26補假一天

沒事去IKEA買了三個大箱子

來整理我的PCB PSOC,STM32,MSP430,CC2540,,,,,,

看到的大箱子裡面還有中箱子

然後裡面還有小盒子

其實如果沒有那些盒子箱子

說不定 一大箱就全裝進去了

不過要找 就會很麻煩了 

這讓我想到細胞 有細胞膜 細胞內的粒線體也有層疊的膜 高爾基體也是膜吧？

基本上生命需要裝在一個個的箱子內

才能不受到 熱力學的破壞

在被保護的環境中生生不息

講完了

 

基因學之父 桑格逝世

• 2013-11-21 01:44
 
• 中國時報
 
• 【蔡鵑如／綜合報導】

    　曾經兩度獲得諾貝爾化學獎的英國生物化學家桑格（Frederick Sanger）19日辭世，享年95歲。桑格被譽為「基因學之父」，是史上4位兩獲諾貝爾的學者之一，也是唯一兩獲化學獎的科學家。

    　桑格在1955年，與同事為胰島素的胺基酸序列完整定序，因此獲頒1958年諾貝爾化學獎；1975年，他和同事研發出快速為DNA定序，也就是解讀DNA的方法，成為繪製人類基因組圖譜的先驅，在1980年再度得到諾貝爾化學獎肯定。

    　桑格經常戲稱自己只會在實驗室亂搞，但在其他學者眼中，也是英國科學界「真正的英雄」。他於1982年退休後，花大把時間照顧花草，並且「在船上鬼混」。

    　英國維康信託基金會和醫學研究理事會，在1993年成立桑格中心，後更名為桑格研究院。信託基金董事法拉爾在聽到桑格的死訊後表示：「我很傷心，他是任何世代最偉大的科學家之一」。

http://news.chinatimes.com/world/110504/112013112100152.html

New chip delivers DNA results within an hour

Panasonic, together with the Belgium-based research institution IMEC, has developed a DNA testing chip that automates all stages of obtaining genetic information, including preprocessing.

http://www.diginfo.tv/v/13-0022-r-en.php

via DangerousPrototype

Supper Cooool! Must See.

Synthetic Biology Open Language

About SBOL

Synthetic Biology Open Language (SBOL) is an open-source standard for in silico representation of genetic designs. SBOL is designed to:

• Allow synthetic biologists and genetic engineers to electronically exchange designs 
• Send and receive genetic designs to and from biofabrication centers
• Facilitate storage of genetic designs in repositories
• Embed genetic designs in publications

SBOL is built around the idea of a core that is used to unambiguously specify the design of a DNA molecule. Around the core are extensions that are used to increase the kind and amount of information transmitted by the language. There are six extensions under development. For example, one extension includes data and information on the performance of DNA components.

The adoption of SBOL offers many benefits, including: (1) enabling the use of multiple tools without rewriting designs for each tool, (2) enabling designs to be shared and published in a form other researchers can use even in a different software environment, and (3) ensuring the survival of design (and the intellectual effort put into them) beyond the lifetime of the software or the reseachers that were used to create them.

https://sites.google.com/a/sbolstandard.org/sbol/

via http://www.biofab.org/software

Store data in DNA

http://www.engadget.com/2013/01/24/scientists-encode-mp3-dna-memory/

Well,DNA is a good storage that is no question. Mother nature has use it for billion years. But right now we still have no techonlogy to read it back as easy as  any E.Coli 

Virterbi Algorithm

最近在上Bioinformatics 的課才知道 Virterbi Algorithm 是在1967年發表的 那是我出生那年 而且Wiki後才知道他也是Qualcomm的Founder .

http://en.wikipedia.org/wiki/Viterbi_algorithm

Embryonic Development Driven By 'Junk DNA'

MicroRNA: one man's junk is another's treasure 

MicroRNAs are small pieces of genetic material similar to the messenger RNA that carries protein-encoding recipes from a cell's genome out to the protein-building machinery in the cytoplasm. Only microRNAs don't encode proteins. So, for many years, scientists dismissed the regions of the genome that encode these small, non-protein coding RNAs as "junk." 

We now know that microRNAs are far from junk. They may not encode their own proteins, but they do bind messenger RNA, preventing their encoded proteins from being constructed. In this way, microRNAs play important roles in determining which proteins are produced (or not produced) at a given time. 

MicroRNAs are increasingly recognized as an important part of both normal cellular function and the development of human disease. 

So, why not embryonic development, too? 

http://www.medicalnewstoday.com/releases/253544.php

Rosalind Problem add 17 new problems

Today, we are beginning a new phase of Rosalind with the publication of 17 new problems. If you have taken a break from the site, we want you back. And… we will be publishing new problems on Friday at 7 PM GMT from now on.

Today's new problems are: “Mendel's First Law”, “Finding a Protein Motif”, “Calculating Expected Offspring”, “Independent Alleles”,“Introduction to Random Strings”, “Partial Permutations”, “Transitions and Transversions”, “Introduction to Alternative Splicing”, “Matching Random Motifs”, “Expected Number of Restriction Sites”, “Independent Segregation of Chromosomes”, “Counting Disease Carriers”,“Counting Quartets”, “Inferring Genotype from a Pedigree”, “The Wright-Fisher Model of Genetic Drift”, “Genome Assembly with Perfect Coverage and Repeats”, “Identifying Reversing Substitutions”. If you have any ideas for new problems, you can create a new problem for Rosalind here and it'll make this project better.

NEC shows 2014-era portable DNA analyzer

From what we're seeing of a next-generation analyzer due in 2014, those expectations are more likely to be met. The new version puts the full DNA extraction, amplification and separation processes on a newer chip that meets NEC's original goal of producing output in 25 minutes -- faster than a short cop drama, if you include the commercial breaks.

http://www.engadget.com/2012/11/26/nec-shows-2014-era-portable-dna-analyzer/

Rosalind Problem(9) Video Course

http://csiflabs.cs.ucdavis.edu/~gusfield/ <--- In the middle of the web page.

正在看！

Rosalind Problem(8) Keep Reading

Who this book is for

The book is intended for Python programmers who need to learn about algorithmic problem-solving, or who need a refresher. Students of computer science, or similar programming-related topics, such as bioinformatics, may also find the book to be quite useful.

Table of Contents

1. Introduction
2. The Basics
3. Counting 101
4. Induction and Recursion ... and Reduction
5. Traversal: The Skeleton Key of Algorithmics
6. Divide, Combine, and Conquer
7. Greed Is Good? Prove It!
8. Tangled Dependencies and Memoization
9. From A to B with Edsger and Friends
10. Matchings, Cuts, and Flows
11. Hard Problems and (Limited) Sloppiness

via Amazon

Rosalind Problem(7) Reading

沒辦法解下去了 要看書了！這本書好像不錯的樣子

Table of Contents

1.   Introduction
2.   NumPy and SciPy
3.   Image Manipulation
4.   Akando and Dancer Modules
5.   Statistics
6.   Parsing DNA Data Files
7.   Sequence Alignment
8.   Dynamic Programming
9.  Tandem Repeats
10. Hidden Markov Models
11. Genetic Algorithms
12. Multiple Sequence Alignment
13. Gapped Alignments
14. Trees
15. Text Mining
16. Complexity
17. Clustering
18. Self-Organizing Maps
19. Principals
20. Species Identification
21. Fourier Transforms and Correlations
22. Correlations
23. Numerical Sequence Alignment
24. Gene Expression Array Files
25. Spot Finding and Measurement
26. Spreadsheet Arrays and Displaying the Data
27. Applications with Expression Arrays

http://www.jblearning.com/catalog/9780763751869/

Rosalind Problem(6) Spectrum Related

今天解決了三題有關Spectrum 與Peptide 辨識相關的題目 但是Reversal Distance還是沒有進展 看來我的Dynamic Programming的思考技巧還要加強ㄚ

Rosalind Problem(5) Reversal Distance

I found a problem on Rosalind Problem : Reversal Distance

I use brut force search for all possible swap . and Get following result of the sample data.

      ['3', '1', '5', '2', '7', '4', '9', '6', '10', '8']
      ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10']
0 1 1 ['2', '1', '3', '4', '5', '6', '7', '8', '9', '10'] 1
0 2 1 ['3', '1', '2', '4', '5', '6', '7', '8', '9', '10'] 2
2 3 1 ['3', '1', '4', '2', '5', '6', '7', '8', '9', '10'] 3
2 4 1 ['3', '1', '5', '2', '4', '6', '7', '8', '9', '10'] 4
4 5 1 ['3', '1', '5', '2', '6', '4', '7', '8', '9', '10'] 5
4 6 1 ['3', '1', '5', '2', '7', '4', '6', '8', '9', '10'] 6
6 7 1 ['3', '1', '5', '2', '7', '4', '8', '6', '9', '10'] 7
6 8 1 ['3', '1', '5', '2', '7', '4', '9', '6', '8', '10'] 8
8 9 1 ['3', '1', '5', '2', '7', '4', '9', '6', '10', '8'] 9
--------------------------------------------------------------------------------
      ['5', '2', '3', '1', '7', '4', '10', '8', '6', '9']
      ['3', '10', '8', '2', '5', '4', '7', '1', '6', '9']
0 3 2 ['5', '2', '8', '10', '3', '4', '7', '1', '6', '9'] 1
2 6 2 ['5', '2', '1', '7', '3', '4', '10', '8', '6', '9'] 2
2 3 1 ['5', '2', '7', '1', '3', '4', '10', '8', '6', '9'] 3
2 4 1 ['5', '2', '3', '1', '7', '4', '10', '8', '6', '9'] 4
--------------------------------------------------------------------------------
      ['8', '2', '7', '6', '9', '1', '5', '3', '10', '4']
      ['8', '6', '7', '9', '4', '1', '3', '10', '2', '5']
6 8 2 ['8', '6', '7', '9', '4', '1', '5', '2', '10', '3'] 1
1 3 1 ['8', '9', '7', '6', '4', '1', '5', '2', '10', '3'] 2
1 4 1 ['8', '4', '7', '6', '9', '1', '5', '2', '10', '3'] 3
1 7 1 ['8', '2', '7', '6', '9', '1', '5', '4', '10', '3'] 4
7 9 1 ['8', '2', '7', '6', '9', '1', '5', '3', '10', '4'] 5
--------------------------------------------------------------------------------
      ['2', '9', '8', '5', '1', '7', '3', '4', '6', '10']
      ['3', '9', '10', '4', '1', '8', '6', '7', '5', '2']
2 8 2 ['3', '9', '2', '5', '1', '8', '6', '7', '4', '10'] 1
0 2 1 ['2', '9', '3', '5', '1', '8', '6', '7', '4', '10'] 2
2 5 1 ['2', '9', '8', '5', '1', '3', '6', '7', '4', '10'] 3
5 6 1 ['2', '9', '8', '5', '1', '6', '3', '7', '4', '10'] 4
5 7 1 ['2', '9', '8', '5', '1', '7', '3', '6', '4', '10'] 5
7 8 1 ['2', '9', '8', '5', '1', '7', '3', '4', '6', '10'] 6
--------------------------------------------------------------------------------
      ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10']
      ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10']

The problem is my answer of data 3 is 6 not 7 !

Due to my bad formating, you can do the swap by the 3 number.

0 3 2 : swap at 0 to 3 with length 2

PS.I know why. 

The problem description refers to reversing an entire interval of the set, not swapping various parts of it. 

Check it in Problem's Question.

 

Rosalind Problem(4) Reversal Distance

這題我想了好久 也寫了三格版本 星期二時想到了如何找出 一次Swap多個資料的方法 找到為何 Sample Data 2 只需要4次 但是Sample Data 3我卻還是認為要6次 今天又搞了一個下午 還是沒搞出來 不過有想到一個更笨的方法了 就是“慢慢找“ Brute Force Search!! 

Rosalind Problem (4) Solve 3 more problem by the help of friend

今天又解了三題 不過都是朋友幫忙的 因為他是念Computer Science科班出身 一下子就找到答案了！

Yahoo Japan Sale Genetic Test

 

http://www.technologyreview.com/view/506811/yahoo-japan-to-sell-genetic-test/

Rosalind Problemset (4) So hard! Cannot Continue

這幾天都沒有進度 被 Reversal Distance  Error Correction in Reads 搞死了 更慘的是原本以為很簡單的Introduction to Set Operations 居然也沒過 玩不下去了! 哪邊有討論區啊

Rosalind Problemset (3) Interesting continue

This is my Rosalind problem set running platform. A Raspberry Pi 256M . Today I solve two problem. One is n-1 another is n-2 . I have spend a whole day to figure it out. There problem are all well document in the Computer Algorithm Book. Hope you can find the solution in the book or by yourself.

Rosalind Problemset (2) Getting harder and harder

The problem set is getting harder and harder. The major issue is sample dataset is too small to verify the program. And download dataset has no answer just told you Correct or not. Make the debug very hard.

Trying to solve the Shortest Superstring problem .

Rosalind Problemset

http://rosalind.info/problems/as-table/

這星期都在忙這個Problem set 基本上是有關bioinformatics 的東西 今天已經做到"Open Reading Frame"那一題了 （我不是上班偷懶喔 我是因為在做初號機的馬拉松測試 因此很無聊 用Raspberry Pi來玩）這些問題集還蠻好玩的

Encode and the Human Genome Project

Most of what you read was wrong: how press releases rewrote scientific history

This week, the ENCODE project released the results of its latest attempt to catalog all the activities associated with the human genome. Although we've had the sequence of bases that comprise the genome for over a decade, there were still many questions about what a lot of those bases do when inside a cell. ENCODE is a large consortium of labs dedicated to helping sort that out by identifying everything they can about the genome: what proteins stick to it and where, which pieces interact, what bases pick up chemical modifications, and so on. What the studies can't generally do, however, is figure out the biological consequences of these activities, which will require additional work.

Yet the third sentence of the lead ENCODE paper contains an eye-catching figure that ended up being reported widely: "These data enabled us to assign biochemical functions for 80 percent of the genome." Unfortunately, the significance of that statement hinged on a much less widely reported item: the definition of "biochemical function" used by the authors.

This was more than a matter of semantics. Many press reports that resulted painted an entirely fictitious history of biology's past, along with a misleading picture of its present. As a result, the public that relied on those press reports now has a completely mistaken view of our current state of knowledge (this happens to be the exact opposite of what journalism is intended to accomplish). But you can't entirely blame the press in this case. They were egged on by the journals and university press offices that promoted the work—and, in some cases, the scientists themselves.

via arstechnica

ENCODE: The Encyclopedia of DNA Elements

Nature ENCODE iOS App

http://www.nature.com/encode/

ENCODE: The human encyclopaedia

...

ENCODE was designed to pick up where the Human Genome Project left off. Although that massive effort revealed the blueprint of human biology, it quickly became clear that the instruction manual for reading the blueprint was sketchy at best. Researchers could identify in its 3 billion letters many of the regions that code for proteins, but those make up little more than 1% of the genome, contained in around 20,000 genes — a few familiar objects in an otherwise stark and unrecognizable landscape. Many biologists suspected that the information responsible for the wondrous complexity of humans lay somewhere in the ‘deserts’ between the genes. ENCODE, which started in 2003, is a massive data-collection effort designed to populate this terrain. The aim is to catalogue the ‘functional’ DNA sequences that lurk there, learn when and in which cells they are active and trace their effects on how the genome is packaged, regulated and read.

...

via Nature

Low-cost water tests - mWater

Our Android App currently supports several other inexpensive water tests, including thePortable Microbiology Laboratory, which is available from Professor Robert Metcalf. One of the components in this kit, 3M Petrifilms, can detect E. coli and other bacteria in water. The tests can be incubated at room temperature in many locations or they can be worn in a pouch to make use of body heat for incubation. The mWater Android app can use the onboard camera to automatically count the bacteria on a Petrifilm and calculate the risk to the user.

In the near future, we will add simple test strips for Free Chlorine (important in piped water systems), Nitrate (commonly found in contaminated wells), and pH. We envision a complete low-cost laboratory suite for communities, health workers, utilities and emergency workers, that is connected to our cloud-based reporting system for instant sharing and mapping of data.

via mWater

SnapGene

www.snapgene.com

Knome

www.knome.com

The elements of bioinformatics

http://elements.eaglegenomics.com/

A Startup Uses the Cloud to Unravel DNA

"The more and more data you produce faster and cheaper, the more the bottleneck—which used to be the DNA sequencing itself—is actually now the data management," he says.

Sundquist sees his company as an instant online genomics center, offering clients immediate access to vast stores of DNA data and to analysis tools so they can make sense of it all—and potentially come up with better treatments for cancer and genetic diseases, as well as identify genetic links to diseases like autism and alcoholism.

via MIT Technology Review

 

Fun and intuitive way of doing genetic engineering : Genome Compiler

What is Bioinformatics?

Let’s assume we have a species of bacteria that is part of the normal millions of ‘good’ bacteria living on and inside healthy human beings; we’ll call this Bacteria X.0. One day Bacteria X started making people very ill. What happened to Bacteria X.0 to make it become the harmful Bacteria X.1? Let’s see how we could answer this question using bioinformatics, along the way gaining insight into the wonderful world of bioinformatics.

Using traditional molecular biology techniques, we isolate Bacteria X and extract its DNA. Then we “sequence” this DNA. Cue the first link in the bioinformatics chain: acquiring data! Acquiring data is the process of generating useable data from a biological sample. In our case, deriving and determining the DNA sequence of the Bacteria X genome.

The next link in the chain is storing this sequence data. While bacterial genomes are typically small, other genomes, such as those of human beings, can produce terabytes (1000 gigabytes) of data.

Now we analyze this sequence data. There are people who specialize in developing computational tools to analyze and visualize data, versus people who actually analyze the information. A typical analysis for our sample case might be to first graphically visualize and compare the genome of the original, harmless Bacteria X.0 with the genome of the new, harmful Bacteria X.1. A scientist might observe a segment of DNA in Bacteria X.1 which is not present in the original Bacteria X.0. This new region of DNA may be responsible for the harmful effects, so the next analysis steps might be to drill down deeper into this region and see what genes lie there, what the function of those genes are, where they may have come from, etc.

[Remember: all assumptions made and conclusions drawn in this example are hypothetical and for illustrative purposes only.]

In this example, we encountered at least 4 different specialized areas within the field of bioinformatics:

1)      Acquiring of data (working with machines and equipment, sequencing DNA)
2)      Storing data (typically working with databases)
3)      Developing tools to analyze and visualize data (programming)
4)      Analyzing data (statistics, analysis)

Typically, individuals will specialize in one particular area rather than working simultaneously across all these fields. That, combined with all the different applications of bioinformatics, means you could ask 100 different “bioinformaticians” what they do and get 100 very different answers!

 

Breaking the Genome Bottleneck

The group plans to sell its so-called "Bina Box" preloaded with software that can reduce the 300 gigabytes or so of raw data from a human genome into a few hundred megabytes of genetic information. The box will upload the compressed dataset to Bina's cloud service for storage, sharing, and further analysis. The Bina Box can do the initial heavy lifting and make the data small enough to send to the cloud, the company says.

Bina Technologies says its system does this initial processing of genomic data at speeds that are orders of magnitude faster than tools made available by the Broad Institute, the MIT-Harvard joint genome center. What takes about a week using the Broad's genome variation analysis pipeline on a high-end eight-core machine on Amazon's cloud can be done in about two hours on a Bina Box, says Bani Asadi. The company expects to publish a full description of its comparison to other analysis pipelines in the coming months.

via MIT Technology Review

 

Bases to Bytes Cheap sequencing technology is flooding the world with genomic data. Can we handle the deluge?

The cost of sequencing human genomes is plunging—in the most advanced genomics centers, it's falling five times faster than the cost of computing. Increasingly, people are getting their DNA sequenced by companies and research labs in a search for clues about genetic variation and disease.

But the industry must figure out how to cheaply store all the resulting data. Each of the 3.2 billion DNA base pairs in a human genome can be encoded by two bits—800 megabytes for the entire genome. But considerable data about each base is usually collected, and genes are often sequenced many times to ensure accuracy, so it's common to save around 100 gigabytes when sequencing a human genome with a machine made by industry leader Illumina. Keeping this much data about every person on the planet would require about as much digital storage as was available in the whole world in 2010.

The trick, then, will be to save less. Harvard geneticist George Church says that eventually only the differences between a newly sequenced genome and a reference genome will need to be stored. That information could be encoded in as little as four megabytes. Then your genome might be just another e-mail attachment.

via MIT Technology Review

 

DNA: The Secret of Life

via Amazon

前半段關於基因改造食物的部份差點看不下去 就算那是James D. Watson說的 後面有關基因治療的部份 我也是不是很同意 （我支持體細胞（Somatic Cell)基因治療 而不支持性細胞（Germline Cell)基因治療）因為如果你知道目前把好的基因植入你的細胞是使用反轉錄病毒而且你完全不知道會把基因植到哪邊 光是這一點就讓人不放心（對於重大的基因疾病這是兩難的選擇）Watson對基因工程的看法太過天真了 但是我同意我門應該對基因做更多的研究 甚至於找出與行為相關的基因 不是要逃避責任而是知道有這樣的缺陷才能用適當的教育或是環境來改善

關於基因改造食物 (1)

如果孟山都(Monsanto)公司覺得自己的產品是那麼的值得驕傲 請在每一件使用貴公司的種子而生產的食物與沿生食品上打打上 ”Monsnto Indside" 不是很棒的一件事嗎？ 學學人家Intel and Windows 在每一臺電腦上都貼上亮晶晶的貼紙 不是很光榮的事嗎？

讀完“欺騙的種子”有感

Why a Portable DNA Device Could Yield Better Data

The technology relies on the fact that a DNA base, or a combination of bases on a DNA strand creates a characteristic disruption in a current as it passes through the nanopore. Electrodes measure the change in current flow as DNA molecules are fed through protein nanopores; an electrical gradient drives the DNA through the pore, while molecular "controllers" attached to the molecules mechanically slow them down so that their electrical signals may be recorded.

This approach has two important advantages.

First, the system is compact and doesn't require a supply of expensive reagents. That means sequencing can come out of the lab, making it useful for personalized medicine or for use in resource-poor clinics. Indeed, the disposable sequencer the company is about to introduce is the size of a USB memory stick.

Second, the technology reads much longer stretches of DNA than other rapid sequencing approaches, which means it has the potential to be better at spotting important "structural variants" related to disease. These variants occur when a whole segment of chromosome is moved, inverted, duplicated, or otherwise changed. When DNA is chopped into shorter stretches to be sequenced and then put back together on a computer, it is easier to miss, or misinterpret, such variants.

via Technology Review

synthesis.cc 

Device Brings $1,000 Genome Within Reach

At $149,000, the new machine is about three times the price of the Personal Genome Machine, the sequencer that the company debuted about a year ago. But the DNA-reading chip inside it is 1,000 times more powerful, according to Rothberg, allowing the device to sequence an entire human genome in a day for $1,000—a price the biotech industry has been working toward for years because it would bring the cost down to the level of a medical test.

via MIT Technology Review

 

Find Your Inner Neanderthal

In the last few years, scientists have uncovered clues not just to what the lives of Neanderthals may have been like, but also clues that tell us more about what it means to be a modern human.

Most interesting of all is that, although Neanderthals disappeared long ago, their DNA lives on in all non-African people.

http://spittoon.23andme.com/2011/12/15/find-your-inner-neanderthal/

PS.我在網路上的看過那個分析資料 蠻有趣的 因為收集到的尼安德塔人的基因量真的很少 如何分析這些資料和方法很有趣 (沒記錯的話是MIT Bioinformatics的課　一個很cool的年輕教授）

 

 

Is Autoimmunity a Result of Genetic Adaptation to Pathogens?

Although about 95% of the observed human genetic diversity appeared to be due to non-selective processes, a finding that was not surprising, adaptation to local environments—and specifically to pathogens—also accounted for a significant amount of genetic diversity. Viruses, bacteria, protozoan organisms that cause malaria and leishmaniasis, and parasitic worms are all examples of pathogens.

The study’s findings suggest that about 100 human genes have been strongly influenced by pathogenic organisms. Parasitic worms seem to have posed the most pressure on human genes. Because worms are complex organisms with longer lifespans than more simple pathogens, they may have co-evolved with people and exerted more pressure on the human genome.

...

This study offers new evidence for the hygiene hypothesis, a currently unproven theory suggesting that ramped up immune systems originally evolved to protect people from infectious organisms. As societies devised ways to keep pathogens at bay, however, their immune systems failed to adjust and they began to suffer from immune diseases characterized by too much inflammation.

http://spittoon.23andme.com/2011/11/30/is-autoimmunity-a-result-of-genetic-adaptation-to-pathogens/

 

Epigentics

If Gene is the program,regulation is condition block and epigentic is condition compilation . A programmer's point of view.

I think the early development enviroment has more impact on after birth enviroment impact on epigenitics and regulation control. Also the stem cell to normal cell creation enviroment is a key. I think these microenviroment has a lot more impact on living enviroment .

And I also think , we are still living in RNA world. I belived there are a lot to discovery inside the nucleous. There are must some kind of DNA house keeping job maintain by RNA. Like chaperone protien help protien folding.

Some though after read "The dynamic genome, A general introduction"

Last Update – 18 August 2011 (Biopython 1.58)

http://biopython.org/DIST/docs/tutorial/Tutorial.html

http://news.open-bio.org/news/2011/10/chromosome-diagrams-in-biopython/

Transcriptome

The transcriptome is the set of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA produced in one or a population of cells.

http://en.wikipedia.org/wiki/Transcriptome

'Junk DNA' defines differences between humans and chimps

The research team lead by Georgia Tech Professor of Biology John McDonald has verified that while the DNA sequence of genes between humans and chimpanzees is nearly identical, there are large genomic "gaps" in areas adjacent to genes that can affect the extent to which genes are "turned on" and "turned off." The research shows that these genomic "gaps" between the two species are predominantly due to the insertion or deletion (INDEL) of viral-like sequences called retrotransposons that are known to comprise about half of the genomes of both species. The findings are reported in the most recent issue of the online, open-access journal Mobile DNA.

"These genetic gaps have primarily been caused by the activity of retroviral-like transposable element sequences," said McDonald. "Transposable elements were once considered 'junk DNA' with little or no function. Now it appears that they may be one of the major reasons why we are so different from chimpanzees."

via http://kevin-gattaca.blogspot.com

What European DNA Can Say About Ancestry, Disease Risk, and Cultural Traits

All the drama in the European Union right now — the debt crisis, the North-South divide and the kvetching over the wisdom of a common currency — has reignited talk about the cultural divide between people on the continent.

But is the divide more than a political and cultural one? Is there a deeper difference among the people of Europe or those of European ancestry than whether Germans have a firmer handshake or are more punctual, or which nationality prefers a kielbasa to köttbulla?

There may be, and those differences can be seen in people’s DNA.

Although all humans are over 99 percent identical genetically, even in the tight geographic confines of Europe there is enough genetic variation that 23andMe researchers can use it to determine from where in Europe a person, or a person’s ancestors, came.

http://spittoon.23andme.com/2011/10/21/genes-and-geography/

Genetic Variation Influences How We Respond to Reinforcement

A study published this month suggests that rs1799971 also influences learning through positive reinforcement. The researchers behind this study tested if individuals with different versions of rs1799971 were more or less likely to continue choosing the right answer in a video game if they received reinforcement (in the form of a small cash prize) for correct answers.

The authors found that positive reinforcement prompted individuals with the AA genotype at rs1799971 to continue to choose the right answer over time. That is, positive reinforcement motivated these individuals to learn. In contrast, individuals with at least one copy of the G version at rs1799971 (AG or GG) were less motivated by positive feedback—these participants did not continue to choose the right answer over time.

http://spittoon.23andme.com/2011/09/20/snpwatch-genetic-variation-influences-how-we-respond-to-reinforcement/

看來吃軟不吃硬或是軟硬都不吃是一種遺傳!

Gamers solve decade-long simian AIDS protein conundrum

For over a decade, researchers have been arduously attempting to reconstruct the folded shape of M-PMV with the aid of the task-specific Rosetta software, but to no avail. Now, in what they're calling a possible first, gamers were able to do what scientific brains and algorithms could not, creating a sufficient model for molecular replacement -- all in just three weeks. Feel like dedicating your leisure hours to this worthwhile cause? Then be sure to hit up the source link below, and transform yourself from couch potato to couch crusader.

via Engadget

把蛋白質折疊當成Game來玩 請Game玩家來解決科學家一直找不出來的方法 (玩家們只花了3星期 兒科學家花了10年)

http://fold.it/portal/

An RNA Switch for Stem Cells

Mitchell Guttman, first author of the study and a graduate student at MIT and the Broad Institute, says that when the Broad team discovered more than 3,500 unique lincRNAs in the human and mouse genomes in 2009, "the potential was enormous, and we wanted to know what they could be doing."

To answer that question, the researchers focused on understanding lincRNAs' role in embryonic stem cells. Using a technique called RNA interference, they systematically shut down the function of each of more than 200 lincRNAs previously identified as playing a role in embryonic stem cells. They then profiled the genes expressed in the cells and studied their functions. They found that most lincRNAs have widespread effects on cells, and that they help control the fate of stem cells. The team identified about two dozen lincRNAs that help maintain the cell's pluripotency—its ability to beget all other kinds of cells—and a similar number of lincRNAs that repress genes involved in differentiating into other cell types.

via MIT Technology Review

Learn R Quickly !

If you currently use another statistical package, why learn R?

1. It's free! If you are a teacher or a student, the benefits are obvious.
2. It runs on a variety of platforms including Windows, Unix and MacOS.
3. It provides an unparalleled platform for programming new statistical methods in an easy and straightforward manner.
4. It contains advanced statistical routines not yet available in other packages.
5. It has state-of-the-art graphics capabilities.

http://www.statmethods.net/

不錯的R學習網站 書也不錯 很實用