科学与数学ds9a.nl编辑精选
用程序员的眼光看 DNA
DNA seen through the eyes of a coder (2017)
2013 — 2018，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
这篇文章用程序员熟悉的语言和类比（代码、编译、程序、垃圾代码等）来讲解 DNA 与基因组，帮助没有生物学背景的读者建立直觉。它适合作为跨学科入门，但评论也提醒：这些类比只是启发工具，不能替代真实的分子生物学。
为什么经久不衰：它把 DNA 用程序员能秒懂的框架串起来，而评论区又提供了必要的专业纠偏，使这篇跨学科入门至今仍有阅读价值。
HN 评论精选
类比不错但只是类比，真正执行工作的是蛋白质。
作为正在开发基因工具设计软件的人，我觉得这实际上是个相当不错的概览。它的类比很扎实，尽管只是类比。它很好地描绘了早期教育阶段的快照，有助于建立宏观直觉和学科间联系。但要小心记住它们只是类比，通常不能依赖它们去真正发现、发明、设计或下结论。有趣的是，科学发展太快，现在我们已经开始能够改进、实现并兑现那些编码式能力——可以用智能而理性的方式编写、修补、更新和影响那段代码，而不是上世纪设下的屏幕。我接下来会加的一节是真正开始谈论编译后的程序——蛋白质本身。所有那些代码、规则、启发式都是要通过原子 3D 打印机运行来生产蛋白质。作为集合，这些蛋白质在细胞内形成封闭社区，在组织中形成社区，在生物体中形成社区。编译后的蛋白质在最低层做实际工作，却常被忽视，而我们都惊叹于源码。源码优雅，但程序更惊人。
jfarlow查看英文原文
As someone building software to design genetic tools, this is actually a pretty good overview. It's analogies are pretty solid, even if they are just analogies. It's a well-described snapshot of the early phase of education where this helps build a grand intuition and relations between disciplines. Just be careful to remember that they're just analogies, and in general can't be relied on to actually discover, invent, design or conclude. The fun part for everyone here is that the science has improved so far so quickly that at this point that we are starting to be able to improve, implement and otherwise make good on those coding-style capabilities. We can start to write, patch, update, and affect that code - and do so in intelligent and rational ways, rather than the screens set up in the past century. The next section I would add would be one that actually started to talk about the compiled programs - the protein's themselves. All that code, all those rules, all those heuristics are there to be run through an atomic 3D-printer to produce proteins. And in an ensemble, those proteins form a closed community within a cell, which then form communities in a tissue, which form in communities called an organism. Those compiled proteins actually do the work at the lowest levels but often get a bit of short shrift while we all stare at their source-code in amazement. The source is elegant, but the programs are even more amazing, in my humble opinion. Here are some 'profiles' of the kinds of economically and socially interesting programs we've started to make based on the above source-code. An 'app-store' of compiled apps if you will: https://serotiny.bio/notes/proteins/
基因调控网络像可自我复制的神经网络，能进行计算。
你知道 DNA 让我震撼的是什么吗？基因调控网络。它们的工作方式类似神经网络，基因在复杂依赖图中作为其他基因的信号。每个细胞都有一个“基于基因的大脑”（一个 RNN），能进行计算，把状态映射为行动。大脑中的每个神经元实际上都是一整个神经网络。GRN 可能是宇宙中最节能的神经网络，而且它们还能自我复制。
visarga查看英文原文
You know what blew my mind about DNA? The "Gene Regulatory Networks". https://en.wikipedia.org/wiki/Gene_regulatory_network They work analogically like neural networks, where genes act as signals to other genes in a complex graph of dependency. Isn't that amazing? Each cell has a "gene based brain" (an RNN) which can do computation - it can map states to actions. Each neuron in the brain is actually a whole neural network. GRN's are probably the most energy efficient neural nets that exist in the universe, and they're also self replicators.
反对 DNA/程序类比，建议系统学习真实的分子生物学。
生物学与计算机科学完全不同，领域间的隐喻不建立理解，只会误导；每次听到有人把 DNA 比作计算机程序我都崩溃。我推荐《Molecular Biology for Computer Scientists》给愿意学点真正生物学的人。我曾考虑进入生物信息学，进行了三周密集学习，最后给其他人做研讨会讲解基础。学习需要先复习相关化学，理解生物学家使用的化学和生物学术语，然后生物学内容才清晰。一旦理解，非常美丽，是值得学的最美的东西之一。
stiff查看英文原文
Biology is completely different from Computer Science and metaphors between the fields build no understanding and can only be misleading, every time I hear someone comparing DNA to a computer program I fall into pieces. I recommend "Molecular Biology for Computer Scientists" instead for those willing to learn some actual biology: http://www.biostat.wisc.edu/~craven/hunter.pdf I think it's the first chapter of this book: http://mitpress.mit.edu/books/processes-life I once considered going into bioinformatics, and did an intense three weeks sprint trying to learn some molecular biology, ending in a seminar presentation to other people explaining the basics. I used this book back then which I also recommend strongly to those interested: http://www.amazon.com/Bioinformatics-Molecular-Evolution-Paul-Higgs/dp/1405106832/ref=sr_1_1?ie=UTF8&qid=1387141666&sr=8-1&keywords=bioinformatics+and+molecular+evolution It covers all the basics of molecular biology very understandably and at the same time the scientific/computational content is interesting even for a computer scientist. Still, learning this stuff takes hard work, you have to rehash some relevant chemistry first or you get nowhere, than biologists use a lot of both chemical and biological lingo which you have to understand, and only then the actual biological content becomes clear. Once you do understand it, however, it's beautiful, beautiful stuff, one of the most beautiful things one can learn in general I think, of which you unfortunately won't get a sense from reading this article, or in general from trying to understand it by sloppy metaphors. Do yourself a favour and try to understand this for real.
非编码 DNA 常有结构和调控功能，“垃圾 DNA”说法有害。
要警惕“垃圾 DNA”这个词：染色体片段非编码，并不意味着它在基因组功能中没有作用。组装功能性结构（如复制体）需要形成复杂的二级和三级 3D 构象，这由拓扑异构酶、结合蛋白、各种 RNA 以及“垃圾”片段来支持。另一些情况下，“垃圾”可以隔离高度保守的基因。“垃圾”是很糟糕的定性。媒体/科普可能落后，几年前的一些生物化学教材已经过时。DNA-DNA 相互作用、表观遗传、差异 RNA 剪接和 DNA-DNA 反馈之间的交互层令人难以置信。
atratus查看英文原文
It's important to be wary of the term 'junk DNA'...just because a segment of a chromosome is noncoding does not mean it has no role in the genome's function. Assembly of functional structure ie a Replisome requires formation of elaborate secondary and tertiary 3-D conformations that support the primary replication machinery. This is facilated by topoisomerases, binding proteins, a whole soup of RNAs, and spans of "junk" which allow the necessary conformations. In other cases, the 'junk' can serve to insulate highly conserved genes. "Junk" is a terrible characterization. This is one of those instances where the press/pop media can be a bit behind. Some bchem textbooks from even a few years ago are obsolete. Research into DNA-DNA interaction really has become hotter in only the last few years as we've begun pinning down protein roles. There is a whole layer of interaction between epigenetics, differential RNA splicing, and DNA-DNA feedback that is just mind-boggling.
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