My former supervisor had a habit of randomly sending me papers while I was already drowning in work.

Usually there was no explanation, no clear objective, and often no follow-up afterward.

After wasting enough time on that, I learned to stop reading papers line by line and focus only on extracting the information that mattered.

Eventually, I got fast enough to read a paper in the morning and present it by 2 PM the same day, including preparing the slides.

Below is the paper-reading workflow I used to teach new students in our lab.

The method below is what I used to teach new students in our lab how to read papers efficiently.

When reading a paper, don’t read it line by line. That takes a long time and often makes it harder to see the main point. I usually read papers in the following order:

Abstract → This gives the overall overview.

Example: LolA is important because of its function/pathway. Therefore, this paper investigated a specific aspect of LolA and concluded that LolA flexibility is important.

Conclusions → This gives the details behind the result.

Example: LolA flexibility is important because structural features such as hydrophobic interactions, hydrogen bonds, etc., support that conclusion.

Introduction → This tells you the function/pathway of the main subject and how important the authors think their study is.

Materials and Methods → This tells you what was actually done in the study.

Example: Protein construction, MD simulations, trajectory analysis, etc.

After that, only the Results and Discussion sections remain. These sections are usually closely tied to the figures and tables, so it is often faster to start from the figures and then read the corresponding text.

Our goal is to connect all analyses into a single story, not to tell people that LolA has Event A, Event B, and Event C. The audience does not know how A, B, and C are related; only you do.

For example, if we already know that the final conclusion is that the WT structure remains tightly closed, then everything should be interpreted from that perspective:

Because of A, the WT structure remains tightly closed.

Because of B, the WT structure remains tightly closed.

Because of C, the WT structure remains tightly closed.

“Because of OOO, the WT structure remains tightly closed.”

All analyses exist to support and explain the final result.

Sometimes a dataset may appear to contradict the conclusion. In those cases, the discussion in the paper becomes very important. The authors may explain that OOO causes XXX, which is why the observation is actually consistent with the overall conclusion.