最近一期《Molecular Cell》雜志上刊發(fā)了一篇Uri Alon教授撰寫的短文“How To Choose a Good Scientific Problem”。這絕對是一篇值得推薦給所有立志做科研的同學們的好文章。之所以這么說，并非出于Uri Alon教授是位一年能發(fā)好幾篇Nature的大牛，而是因為你能從文字中感覺出Uri Alon教授是一位真正熱愛科學的人，一個以科研為樂趣的人，一個純粹的科學家，一個努力全方位培養(yǎng)學生的好老師。很遺憾，在我們這樣一個中國特色的國度里，這樣純粹的科學家實在是太少了。鑒于我國特殊的國情，文章中建議的一些做法盡管長遠來看對個人發(fā)展有利，但并不適用于我們，所以請各位僅供參考。（日志末尾附Uri Alon教授的實驗室的主頁及原文鏈接）
Choosing good problems is essential for being a good scientist. But what is a good problem, and how do you choose one? The subject is not usually discussed explicitly within our profession. Scientists are expected to be smart enough to figure it out on their own and through the observation of their teachers. This lack of explicit discussion leaves a vacuum that can lead to approaches such as choosing problems that can give results that merit publication in valued journals, resulting in a job and tenure.
以下是我挑出來的一些給我個人留下深刻印象的語句（注意：這些句子不是連貫的，建議感興趣的朋友閱讀原文。）
A good choice means that you can competently discover new knowledge that you find fascinating and that allows self-expression.
What is the goal of starting a lab? It is sometimes easy to pick up a default value, common in current culture, such as “The goal of my lab is to publish the maximum number of papers of the highest quality.”However, in this essay, we will frame the goal differently: “A lab is a nurturing environment that aims to maximize the potential of students as scientists and as human beings.”
From values—even if they are not consciously stated—flow all of the decisions made in the lab, big and small: how the lab looks, when students can take a vacation, and (as we will now discuss) what problems to choose.
The Two Dimensions of Problem Choice
The first is feasibility—that is, whether a problem is hard or easy, in units such as the expected time to complete the project. This axis is a function of the skills of the researchers and of the technology in the lab. It is important to remember that problems that are easy on paper are often hard in reality, and that problems that are hard on paper are nearly impossible in reality.
The second axis is interest: the increase in knowledge expected from the project. We generally value science that ventures deep into unknown waters. Problems can be ranked in terms of the distance from the known shores, by the amount in which they increase verifiable knowledge. We will call this the interest of the problem.
The diagram suggests a way to choose between problems, using the Pareto front principle of optimization theory. If problem A is better on both axes than problem B, one can erase B from the diagram. Applying this criterion to all problems, one is left only with problems for which there are no problems clearly better in both feasibility and interest. These remaining problems are on the Pareto front.
To decide which problem to select along the front depends on how we weigh the two axes. For example, a beginning graduate student needs a problem that is easy; positive feedback can thus be rapidly provided, bolstering confidence. These problems are on the bottom right of the Pareto front. The second problem in graduate school can move up the interest axis. Postdocs need projects in the top-right quadrant, since time is limited. Beginning PIs, who need to select a field on which to spend many years and with which to train students, may seek a grand challenge that can be divided into many good, smaller projects. Thus, the optimal problems move along the Pareto front as a function of the life stages of the scientist.
選題要慎重，磨刀不誤砍柴工，切忌頭腦發(fā)熱。（國情，注意國情）
A common mistake made in choosing problems is taking the first problem that comes to mind. Since a typical project takes years even it if seems doable in months, rapid choice leads to much frustration and bitterness in our profession. It takes time to find a good problem, and every week spent in choosing one can save months or years later on.
In my lab, we have a rule for new students and postdocs: Do not commit to a problem before 3 months have elapsed. In these 3 months the new student or postdoc reads, discusses, and plans. The state of mind is focused on being rather than doing. The temptation to start working arises, but a rule is a rule. After 3 months (or more), a celebration marks the beginning of the research phase—with a well-planned project.
到底該聽誰的？（國情，注意國情）
The confusion is due to the mixing of two voices—one is a loud voice of the interests of those around us, in conferences, in our department, etc. The other is a faint voice in our breast, that says, “This is interesting to me.” Ranking problems with consideration to the inner voice makes you more likely to choose problems that will satisfy you in the long term.
What is the essence of the inner voice? The projects that a particular researcher finds interesting are an expression of a personal filter, a way of perceiving the world. This filter is associated with a set of values: the beliefs of what is good, beautiful, and true versus what is bad, ugly, and false.
we can help students in the late phases of their PhD or in the postdoc stage to strengthen their inner voice. A mentor can help by listening to a student describe what they like in science, in life outside of science, what moment made them decide to become scientists, and what scientific work they admire.
科研行軍路線圖
A common schema is expressed in the way papers are written: one starts at point A, which is the question, and proceeds by the shortest path to point B, the answer. There is a danger, if one accepts this schema, to regard students as a means to an end (an arrow to B).
However, one can adopt a second schema, one that resembles more the course of most projects. As before, one starts at point A and moves toward the goal at point B. Soon enough, things move off course, and the path meanders and loops back. Experiments stop working, all assumptions seem wrong, and nothing makes sense. The researcher has entered a phase linked with negative emotions that may be called “the cloud.”
In this second schema, the meandering of research is seen as an integral part of our craft, rather than a nuisance. The mentors' task is to support students through the cloud that seems to guard the entry into the unknown. And, with this schema, we have more space to see that problem C exists and may be more worthwhile than continuing to plod toward B.
本文的原文鏈接 （Molecular Cell, Volume 35, Issue 6, 726-728, 24 September 2009）
http://www.cell.com/molecular-cell/fulltext/S1097-2765(09)00641-8
Uri Alon教授的課題組主頁
http://www.weizmann.ac.il/mcb/UriAlon/
Youtube上有Uri Alon教授自彈自唱的一段視頻；Uri Alon教授在Facebook上有賬號。可惜，Youtube和Facebook在我國被被和諧掉了。這就是國情。
