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HOW TO EVALUATE A PAPER 已有1人参与
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HOW TO EVALUATE A PAPER A thorough understanding and evaluation of a paper involves answering several questions: a. What questions does the paper address? b. What are the main conclusions of the paper? c. What evidence supports those conclusions? d. Do the data actually support the conclusions? e. What is the quality of the evidence? f. Why are the conclusions important? 全面理解和评价一篇论文需要回答以下几个问题： a.该论文提出了什么问题？ b.该论文的主要结论是什么？ c.这些结论有什么证据支持？ d.这些资料是否确实支持该结论？ e.这些证据的质量如何？ f.这些结论为何重要？ a. What questions does the paper address? Before addressing this question, we need to be aware that research in biochemistry and molecular biology can be of several different types: Type of research Question asked: Descriptive What is there? What do we see? Comparative How does it compare to other organisms? Are our findings general? Analytical How does it work? What is the mechanism? a.该论文提出了什么问题？ 在提出这个问题前，我们需要知道在生物化学和分子生物学领域的研究有几种不同的类型： 描述型 回答：存在什么？我们看到什么？ 比较型 回答：它如何与其它微生物比较？我们的发现普遍存在吗？ 分析型 回答：它如何发挥作用？它的机制是什么？ Descriptive research often takes place in the early stages of our understanding of a system. We can't formulate hypotheses about how a system works, or what its interconnections are, until we know what is there. Typical descriptive approaches in molecular biology are DNA sequencing and DNA microarray approaches. In biochemistry, one could regard x-ray crystallography as a descriptive endeavor. 描述的研究通常处于我们对一个系统理解的早期阶段。只有知道存在何物，我们才能关于系统如何发挥作用，或者它的互相联系是什么提出假说。在分子生物学中典型的描述性方法是DNA测序和DNA芯片途径。在生化中，X线晶体衍射可视作一种种描述。 Comparative research often takes place when we are asking how general a finding is. Is it specific to my particular organism, or is it broadly applicable? A typical comparative approach would be comparing the sequence of a gene from one organism with that from the other organisms in which that gene is found. One example of this is the observation that the actin genes from humans and budding yeast are 89% identical and 96% similar. 比较性研究通常在当问及实验发现的普遍存在程度时被应用。它是否是我研究的特异微生物所特有的，或者是它广泛存在？典型的比较方法是将含有某种基因的微生物的基因序列与其它发现该基因的微生物相比。例如发现人类和芽生酵母的肌动蛋白基因有89％相同，96％类似。 Analytical research generally takes place when we know enough to begin formulating hypotheses about how a system works, about how the parts are interconnected, and what the causal connections are. A typical analytical approach would be to devise two (or more) alternative hypotheses about how a system operates. These hypotheses would all be consistent with current knowledge about the system. Ideally, the approach would devise a set of experiments todistinguish among these hypotheses. A classic example is the Meselson-Stahl experiment. 分析性研究通常应用于当我们所知道的足以开始对该体系如何运作，局部如何关联和局部的因果关系等进行假设时。典型的分析性方法是设计体系如何工作的两个（或多个）备选假说。这些假说与所知的一致。理想状态下，分析手段应设计一整套实验来从这些假说中辨别正确的。经典的例子是Meselson-Stahl实验。 Of course, many papers are a combination of these approaches. For instance, researchers might sequence a gene from their model organism; compare its sequence to homologous genes from other organisms; use this comparison to devise a hypothesis for the function of the gene product; and test this hypothesis by making a site-directed change in the gene and asking how that affects the phenotype of the organism and/or the biochemical function of the gene product. Being aware that not all papers have the same approach can orient you towards recognizing the major questions that a paper addresses. 当然，很多论文是这些方法的结合。例如，研究者们将他们的典型微生物测序，将它的序列与其它微生物的同源基因相比，利用该比较来设计一个关于该基因产物的假说；通过该基因的点突变来验证这个假说，并寻找它如何影响该微生物的表型或该基因产物的生物学功能。 要知道，并非所有运用同样方法的论文会引导你认识该文提出的主要问题。 What are these questions? In a well-written paper, as described above, the Introduction generally goes from the general to the specific, eventually framing a question or set of questions. This is a good starting place. In addition, the results of experiments usually raise additional questions, which the authors may attempt to answer. These questions usually become evident only in the Results section. 这些问题是什么？在一篇好的论文中，如上所述，引言通常从普遍到特殊，最终对一个或多个问题提出设想。这是个好的开始。另外，实验结果通常提出另外的问题，它是作者试图回答的。这些问题通常在结果部分才明显提出。 b. What are the main conclusions of the paper? This question can often be answered in a preliminary way by studying the abstract of the paper. Here the authors highlight what they think are the key points. This is not enough, because abstracts often have severe space constraints, but it can serve as a starting point. Still, you need to read the paper with this question in mind. 该文的主要结论是什么？ 这个问题可通过学习该文的摘要就能初步得到答案。在摘要里作者会突出他们认为的关键点。这是不够的，因为摘要通常只有几行的内容，但它却可能开个好头。还有，你需要带着这个问题去读该文。 c. What evidence supports those conclusions? Generally, you can get a pretty good idea about this from the Results section. The description of the findings points to the relevant tables and figures. This is easiest when there is one primary experiment to support a point. However, it is often the case that several different experiments or approaches combine to support a particular conclusion. For example, the first experiment might have several possible interpretations, and the later ones are designed to distinguish among these. In the ideal case, the Discussion begins with a section of the form "Three lines of evidence provide support for the conclusion that... First, ...Second,... etc." However, difficulties can arise when the paper is poorly written (see above). The authors often do not present a concise summary of this type, leaving you to make it yourself. A skeptic might argue that in such cases the logical structure of the argument is weak and is omitted on purpose! In any case, you need to be sure that you understand the relationship between the data and the conclusions. 什么证据支持这些结论？ 通常，你能从结论部分知之确凿。这些发现的描述会指向相关的图表。最容易的是一个基本的实验支持一个观点。然而，通常的情形是几个不同的实验或方法结合起来支持一个特定的结论。例如，起初的实验会有几个可能的解释，但后来的会设计实验来辨别这些解释。 在理想的情况下，讨论会以这种形式开始“三条证据支持该结论，第一……第二……等”。然而，当论文写得不好时，就会出现困难了。作者通常没有提出这种精简的概括，而是让你自己来总结。持怀疑态度者会认为这种情况下结论的逻辑结构差或是故意省略！在任何情况下，你都要确信理解了数据和结论间的关系。 d. Do the data actually support the conclusions? One major advantage of doing this is that it helps you to evaluate whether the conclusion is sound. If we assume for the moment that the data are believable (see next section), it still might be the case that the data do not actually support the conclusion the authors wish to reach. There are at least two different ways this can happen: i. The logical connection between the data and the interpretation is not sound ii. There might be other interpretations that might be consistent with the data. One important aspect to look for is whether the authors take multiple approaches to answering a question. Do they have multiple lines of evidence, from different directions, supporting their conclusions? If there is only one line of evidence, it is more likely that it could be interpreted in a different way; multiple approaches make the argument more persuasive. Another thing to look for is implicit or hidden assumptions used by the authors in interpreting their data. This can be hard to do, unless you understand the field thoroughly. 这些数据真的支持结论吗？ 这样做的一个主要好处是它帮助你评价结论是否合理。如果我们暂假设这些些数据是可信的（见下节），仍有可能出现数据并不真正的支持作者希望得出的结论。至少有两种不同的途径导致这种情况的发生。 １、数据和解释间的逻辑联系不合理；２、可能有其它解释与数据一致。 一个重要的需要注意的方面是作者采用多种方法来回答一个问题。他们是否有多条的证据，从不同的角度来支持他们的结论？如果只有一条证据，那它很可能通过不同的方法来解释；多种方法可使结论更具说服力。 另一件需要注意的是作者在解释他们的数据时含蓄或隐藏的假设。这比较难以做到，除非你对这个领域了解很全面。 e. What is the quality of that evidence? This is the hardest question to answer, for novices and experts alike. At the same time, it is one of the most important skills to learn as a young scientist. It involves a major reorientation from being a relatively passive consumer of information and ideas to an active producer and critical evaluator of them. This is not easy and takes years to master. Beginning scientists often wonder, "Who am I to question these authorities? After all the paper was published in a top journal, so the authors must have a high standing, and the work must have received a critical review by experts." Unfortunately, that's not always the case. In any case, developing your ability to evaluate evidence is one of the hardest and most important aspects of learning to be a critical scientist and reader. 那个证据的品质如何？ 这是最难以回答的问题，对新手和专家同样如此。同时，它是成为年轻科学家所需学习的最重要的技能之一。它关系到从一个相对被动的信息观点接收者变成一个主动的制作者和严格的评论者的重新定位。这很不容易，可能要好几年才能掌握。入门的科学家时常困惑，“我够资格向这些权威提问吗？毕竟这些论文都发表在顶级杂志上，所以这些作者肯定具有很高的地位，文章肯定要经专家的严格评审才能接受。”不幸的是，事实并不总是如此。在任何情况下，拓展你评价论据的能力是成长为一个严格的科学家和读者最困难也是最重要的方面之一。 How can you evaluate the evidence? 你如何能够评价论据？ First, you need to understand thoroughly the methods used in the experiments. Often these are described poorly or not at all. The details are often missing, but more importantly the authors usually assume that the reader has a general knowledge of common methods in the field (such as immunoblotting, cloning, genetic methods, or DNase I footprinting). If you lack this knowledge, as discussed above you have to make the extra effort to inform yourself about the basic methodology before you can evaluate the data. 首先，你需要完整理解实验中所用的方法。通常这些阐述很少，或根本就不描述。尽管通常是不作细节描述的，但更重要的是作者常认为读者已对这个领域的普通方法有了常识（如免疫印迹，克隆，基因手段，或DNase I脚印法）。如果你缺乏此知识，就象上面已讨论的，你必须得多花些气力在评价这些资料前知晓这些基本的方法学。 Sometimes you have to go to the library, or to a lab that has a lot of back issues of common journals, to trace back the details of the methods if they are important. One new development that eventually will make this much easier is the increasing availability of journals on the Web. 有时你得去图书馆或实验室，去查询那儿的过刊来追查重要方法的细节。新出现的手段可使这个工作容易得多，那就是要增强你对网络杂志的可利用度。 Second, you need to know the limitations of the methodology. Every method has limitations, and if the experiments are not done correctly they can't be interpreted. 其次，你需要知道某个方法的局限。每个方法都有局限，如果实验作法不正确，就无法进行阐释。 For instance, an immunoblot is not a very quantitative method. Moreover, in a certain range of protein the signal increases (that is, the signal is at least roughly "linear"  , but above a certain amount of protein the signal no longer increases. Therefore, to use this method correctly one needs a standard curve that shows that the experimental lanes are in a linear range. Often, the authors will not show this standard curve, but they should state that such curves were done. If you don't see such an assertion, it could of course result from bad writing, but it might also not have been done. If it wasn't done, a dark band might mean "there is this much protein or an indefinite amount more". 例如，免疫印迹不是一个真正的定量手段。而且，在一定程度内蛋白信号是增加的（即，信号是最低限度的粗略的“线性”），但超过一定量后，蛋白信号就不再增强。因此，要正确运用这个方法，就需要标准曲线来显示实验条带是在线性范围内。通常，作者不会显示这个标准曲线，但他们会提到这种曲线已作过。如果你不明白这种声明，当然会写不好，尽管你可能已作了这些。如果没有作，黑色的条带意味着“这种蛋白质很多或多得无法定量”。 Third, you need to distinguish between what the data show and what the authors say they show. The latter is really an interpretation on the authors' part, though it is generally not stated to be an interpretation. Papers usually state something like "the data in Fig. x show that ...". This is the authors' interpretation of the data. Do you interpret it the same way? You need to look carefully at the data to ensure that they really do show what the authors say they do. You can only do this effectively if you understand the methods and their limitations. 第三，你需要分辨数据显示了什么而作者认为这些数据显示了什么。后者是站在作者的立场的真正的解释，尽管它通常不是以解释来陈述的。论文通常这样描述“在图X中的数据表明……”这是作者对数据的解释。你对它是否有同样的诠释？你需要仔细观察数据确认它们显示果真是和作者解释的内容一样。如果能够理解方法及它们的局限性，你就能很有效地作到这点。 Fourth, it is often helpful to look at the original journal (or its electronic counterpart) instead of a photocopy. Particularly for half-tone figures such as photos of gels or autoradiograms, the contrast is distorted, usually increased, by photocopying, so that the data are misrepresented. 第四，看原刊（或它的电子版）而不是影印版通常是有帮助的。特别是有一半是图片，如凝胶或自显影的图时，对比度通常因复印是增强歪曲了，所以数据易误传信息。 Fifth, you should ask if the proper controls are present. Controls tell us that nature is behaving the way we expect it to under the conditions of the experiment. If the controls are missing, it is harder to be confident that the results really show what is happening in the experiment. You should try to develop the habit of asking "where are the controls?" and looking for them. 第五，你应该询问是否有对照组。对照组可告诉我们希望在实验条件下产生的反应的特性。如果没有对照组，它很难令人信服结果真正地显示了在实验条件下所发生的。你应该试图养成询问“对照组在哪儿”的习惯，并去寻找它们。 结果为什么重要？ f. Why are the conclusions important? Do the conclusions make a significant advance in our knowledge? Do they lead to new insights, or even new research directions? Again, answering these questions requires that you understand the field relatively well. 结论是否使我们知识有一个显著的提高？它们是否产生一个新的见识，或甚至指引新的研究方向？ 再一次强调，回答这些问题需要你对该研究领域非常了解。 (John W. Little and Roy Parker--University of Arizona) |
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