What would be an appropriate research question to guide Jonathans research project?
Nat Rev Mol Prison cell Biol. Author manuscript; available in PMC 2009 Jun 1.
Published in final edited form as:
PMCID: PMC2675886
NIHMSID: NIHMS103120
How to succeed in science: a concise guide for immature biomedical scientists. Part II: making discoveries
Jonathan W. Yewdell
Laboratory of Viral Diseases, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892, United states of america. Due east-mail: vog.hin.diain@LLEDWEYJ
Abstract
Making discoveries is the most important function of being a scientist, and also the most fun. Young scientists need to develop the experimental and mental skill sets that enable them to make discoveries, including how to recognize and exploit serendipity when it strikes. Here, I provide practical advice to young scientists on choosing a research topic, designing, performing and interpreting experiments and, concluding simply non least, on maintaining your sanity in the process.
You're back for more advice, despite my best efforts in Function I (REF. 1) to paint the bleakest possible picture of career prospects in biomedical research? Well, I am delighted you lot oasis't enlisted in the French Strange Legion just withal. In fact, it'due south a great pleasure to welcome you equally a fellow practitioner of 'Scientific Methodism'. Your mission now is to discover something completely unexpected about how cells or animals piece of work. Y'all might think that such surprises height nigh every scientist'southward 'to exercise' list, but this is non the example. The present culture in biomedical inquiry favours conservative science, which essentially entails refining accepted models.
Swim against this current. Your mission as a scientist is to discover how electric current models are wrong, not right, and to create new paradigms. When you succeed, you will have to fight to publish and fund your research. However, if yous persist (and are really right) then the world will eventually come effectually to your point of view. At this point, your mission will exist to expose the flaws in your new paradigm, and and then on. The best office of your newly chosen career is that you volition never have to worry about running out of things to notice.
Choosing a project
Experience counts
To make a discovery you'll first need to choose a research project. Every bit a graduate educatee, it is wise for the principal investigator (PI) to cull the initial project, or at least play a major part in choosing the projection. You lot simply don't have the experience and judgment at this signal to choose an interesting project with a significant take chances of success. At a postdoctoral level, the decision is more than provisional. If you are continuing in the field of your Ph.D. studies, you lot should be capable of choosing a good projection. If it is a new field, however, your advisor will need to provide guidance every bit to what is viable and interesting.
Brand the most of your surroundings
In choosing a projection, information technology is crucial to exploit the intellectual and physical resources of your immediate surround. This does not but mean that you should plow the same furrow that the laboratory has already seeded and harvested. Introducing new techniques and approaches to your laboratory provides many advantages. For example, you lot will gain conviction in your ability to follow up your findings wherever they lead. It is much easier, however, when you tin larn from the expertise of neighbouring laboratories. Imagine, for example, that your institution has a first-charge per unit confocal microscope facility, simply that confocal microscopy has never been applied to the major research involvement of your own laboratory, even though it has a number of obvious applications. Should you accept advantage of the state of affairs? Of grade! An extreme case to exist sure, but many projects have foundered before they started because of the sheer impossibility of gaining admission to the requisite technology or reagents.
"The best part of your newly chosen career is that you volition never have to worry almost running out of things to find."
Basic or applied inquiry?
There is an important dichotomy betwixt practical and basic research. Funding agencies put a tremendous accent on applied research, which is clearly important, as it is the sole means of translating discoveries into therapies. However, applied enquiry is based on the cognition at hand, regardless of whether it is sufficiently sophisticated to have a reasonable hazard of improving existing therapies. Furthermore, applied research is far less likely than basic enquiry to atomic number 82 to serendipitous findings that volition provide novel insights into unexpected quarters. The nature of practical research is such that if a clinical trial does non work, the project is usually kaput. By contrast, biological science is such a complex tapestry woven from a myriad of components and pathways that, with some patience, properly performed bones research will always lead to interesting discoveries. The problem is that translating these discoveries into therapies is often indirect, and invariably requires decades. This requires a level of patience from funding agencies that is difficult to maintain in the face of political force per unit area to provide firsthand therapies and cures.
Big or piddling questions?
Although it is a skilful thought to avoid following the herd, don't shy abroad from pursuing important questions, which by their very nature will attract the attention of other laboratories. It is normally no more difficult to piece of work on something interesting and of import than it is to work on something of limited involvement that will be hard to publish and fund. Ideally, you will be far ahead of the pack and won't accept to worry about direct contest until you spill the beans about your bang-up findings. Having such a pb isn't ever possible, but y'all should always aim to accept a novel approach to your research question, fifty-fifty if your arroyo is a bit oblique.
Designing experiments
Ideas: they don't come from storks
About graduate students take had minimal contained research experience and will depend heavily on their advisors (or on the postdoctoral fellows that they are teamed up with) to become a feel for designing experiments. Within their first yr full time at the bench, yet, students should be designing their own experiments. experimental pattern encompasses many parameters. The about important, of class, is the hypothesis the experiment is designed to test. For this you demand to have an original thought. But where do ideas come up from?
Although really adept ideas seem to come from nowhere (at the same time, they also seem obvious after the discovery), they are seeded past information from external sources. The key concept is cross-pollination. Talk to your fellow students and more senior scientists in your section and at meetings. Discuss your (and their) research. commonly, ideas and techniques that are standard in one field are novel in another, and their application can lead to breakthroughs. read widely, but not necessarily deeply. Browse the major journals; if the championship is interesting then read the abstract. Still intrigued? read the give-and-take. Just if the newspaper seems relevant should you actually look at the information and and so carefully read all of the sections. While on this topic, reading the methods sections of irrelevant papers can give you good ideas about how to ameliorate your experimental protocols or can advise novel strategies to set on your problem. You should also attend seminars in other disciplines, but sit near the back and beat a strategic retreat if the talk turns out to be of little interest.
Growing your wings
There is zip similar enthusiastic naiveté to seed a discovery. Knowing too much about a topic can really be a barrier to discovery. experiments that experts know won't work sometimes do, because either the experts' assumptions are wrong, or new reagents or technologies became available that let nature to be queried in a new way. Imagine you have only read the latest issue of Nature Reviews Molecular Prison cell Biological science and are struck with a stupendous idea. Y'all excitedly clomp into the office of your PI and propose your killer experiment. She spends the next 30 minutes explaining in excruciating detail, with impeccable logic, why the experiment not only can't possibly work, but will be uninterpretable if it does. Dejected, you lot stumble from the office in a haze of self-recrimination and incertitude. Only so, while cycling home, you regain your bravura and decide that you lot are going to do the experiment anyway.
This is exactly the right attitude that you lot should have. It is crucial during your training that you develop confidence in your insight and larn to recollect independently of your mentor (in the wise words of my commencement mentor, "the upshot of the perfect preparation experience is that you get out the laboratory thinking that your mentor is a good person, but a bit dumb"). So yous do the experiment, and 95 times out of 100 the experiment doesn't piece of work. Don't freak out. Here's a hole-and-corner from the PI earth: if y'all don't tell us, we won't know that you even did the experiment. When I walk through my laboratory, I take no idea what the postdoctoral fellows are doing. I know what experiments they've done recently, and what nosotros discussed they should probably do next (it'southward their conclusion), simply on a 24-hour interval-to-24-hour interval footing, I really don't know. Just watching them pipetting something or looking into a microscope, whatever the purpose, puts a smile on my face — they might discover something today!
So when the experiment doesn't piece of work, put the data in your notebook (the failure will probably be useful down the road) and don't tell your PI. On the rare occasion when the experiment gives you a glorious result, you will have the great pleasure of strolling into the PI'due south office with a wide smiling on your face up and request (magnanimously, of grade) whether they would intendance to see the data from the 'experiment that would never work'. Simply a control freak PI (encounter figure 2 in Part I (REF. 1)) could fail to share your joy and excitement. In fact, when you lot are a PI yourself be careful when discouraging your mentees from performing experiments, no affair how spectacularly flawed they might seem. There is merely no substitute for enthusiasm in scientific discipline, and you douse it both at your ain peril and at the peril of those whose careers are your responsibleness.
Size matters
Having a adept thought (or even a bad thought, sometimes any idea will practice, every bit they can all pb to serendipity) is only the beginning. Designing experiments is an fine art that y'all will continue to improve for as long as you work at the bench or supervise those who do. The size of the experiment is crucial (FIG. 1). It should exist just large plenty to take a sufficient number of repeat samples and positive and negative controls for you to interpret the results with confidence. Small-scale experiments are much more than probable to work than large ones, every bit there is less to become wrong. Furthermore, no matter how much idea you give to the experiment, the crucial controls will occur to you after doing the experiment, typically only after many repetitions, if at all. rare is the scientist who has not been confronted with an essential control when the piece of work is presented in a seminar or for publication. By doing a series of minor experiments with constant modifications based on each preceding experiment, yous will progress much more rapidly than by performing larger experiments that endeavour to anticipate all of the issues and possible outcomes. An important psychological advantage of small, rapid experiments is that failure (the typical fate of new experiments) is much less depressing than after spending huge amounts of time and energy in a much larger but equally unsuccessful effort.
Doing experiments
Golden eyes
Every well-established laboratory has a 'Hall of Fame' of legendary alumni with 'aureate easily'. Golden hands? Gilded eyes is closer to the marking. experimental science does not demand the dexterity of neurosurgery, only it does demand the neurosurgeon's focus on the task at paw. The central to being a adept experimentalist is obsessive attention to particular. They are constantly thinking nigh the matter at mitt (and not near dinner, their adjacent work-out or the cute student in the next laboratory). They constantly apply their eyes to monitor every relevant detail. For instance, is the water bathroom also hot? Is the CO2 setting in the incubator correct? Is the buffer cloudy or off-colour? In cell-based experiments, the golden eyed pay close attention to the cells. They have a feel for how cultured cells look when they are thriving and for how to keep cells in tip-tiptop shape for each experiment. They are constantly scrutinizing the cells during the experiment, even using the microscope when convenient to monitor cell happiness (and to brand the odd discovery based on the macro-behaviour of cells). They detect the size, colour and texture of the cell pellets and how they disperse. Details, details, details!
Skillful experimenters sympathise every part of an experiment (including buffer and detergent selection) and apace learn to recognize which are the about of import aspects of an experiment and which steps tin be shortened or even discarded. While doing the experiment they are already planning how each step could be improved or done more efficiently (doing things more chop-chop allows more samples to be included or more experiments to be performed, and can be crucial for making discoveries).
Although the repetition of experiments is an essential step to gain confidence in a finding, it is a poor experimenter who does not frequently make at to the lowest degree pocket-size changes to their protocol. In fact, making the aforementioned finding after modifying an experiment bolsters the validity of the finding. Higher up all, as an experimental scientist, yous must be certain that your observations are reproducible (BOX 1).
Laboratory notebook: the scientist'southward best friend
An essential part of each experiment is to record accurate and appropriately detailed notes. Start each experiment entry with a statement regarding the hypothesis yous are testing. In describing your actions, make certain you include all of the unique details of the experiment that you will need in order to echo information technology. Those who don't heed this advice are fated to make an incredibly heady finding that they will never be able to repeat. Believe me, this really hurts.
Tape the important events that occurred that will help you interpret your findings (such as when the centrifuge tube cap flew off in the centrifuge and (Argh!) weird fabric nerveless in your cell pellet). neatly write or record data into your notebook. After careful thought, strength yourself to write a conclusion: what went right, what went wrong, how does your hypothesis look at present and what is the next step. Writing the conclusion is important — it is all besides easy to fall into the trap of working hard without thinking hard. If you lot are going to be an independent scientist, yous must exercise both.
There is an element of luck behind most great discoveries. Your luck will be proportional, however, to the number of well-conceived and expertly performed experiments that you execute and on how prepared your mind is to process unexpected findings. As famously attributed to Louis Pasteur, one of the greatest experimentalists of all time, "Dans les champs de 50'observation, le hasard ne favorise que les esprits préparés" (in the fields of observation, chance favours only the prepared mind).
Interpreting experiments
Think big
Discoveries are not physical entities, simply the products of cogitation. Making discoveries is the best part of scientific discipline: it hooks you as a student and never lets you go. Some discoveries hit you lot like a frying pan and don't require a huge amount of thought. These are a real boot, so enjoy the initial glow because sooner or subsequently doubts will tarnish your bright, shiny, discovery as you carefully consider its implications. Other discoveries are more subtle, at least given our mindset, which is hobbled by existing paradigms. To break the shackles of convention, the first thing you lot should do with fresh data is to come up up with the nearly interesting possible interpretation of the results. This has several benefits. First, occasionally, you lot will really be right. A surprising number of great discoveries were missed by previous investigators who made the aforementioned findings but never made the intellectual jump. Become to plenty meetings and y'all will hear somebody complaining "Oh, we saw that too, but didn't make anything of it". Second, even when the most interesting interpretation is wrong, thinking creatively will help you to place your findings in their proper context and will pay large dividends in designing and interpreting hereafter experiments. 3rd, information technology is fun, specially if it leads to encephalon storming with your mentor and other members of the research team.
Repetition trumps p values
Experiments have two full general outcomes. either they are interesting or they aren't. If they are interesting, you demand to repeat them to the bespeak where you are certain they are correct. It is far better to echo a given miracle in a series of slightly imperfect experiments than to rely on a single experiment with perfect replicates that yield impeccable p values. Although statistics are important, don't be blinded past them — they are simply as practiced as the assumptions they are based on. Statistically significant differences between samples only mean that something was different between the samples. The something might be the thing y'all were testing, or it might be something you didn't consider, like the temporal or spatial order in which yous set up the samples.
Yeah you tin!
You've done a superb experiment and your brilliant and subtle interpretation has led to an of import discovery. This step actually trips upwardly many immature scientists, who lack the conviction to believe that their ain two easily and brain could achieve such a matter. Yous need to become over this mental attitude immediately. Although oversized egos are as big a problem in science as in whatsoever profession, you need a healthy ego to be successful in scientific discipline. You lot accept got to believe that y'all have skilful ideas and can make an important contribution to your field (and don't fret, it'due south really truthful).
Encompass serendipity
What if your neat discovery is not on the list of specific aims? Frequently, the best discoveries are serendipitous. Serendipity is easiest to cover if it provides insight into your question of interest, but information technology oftentimes leads you into other fields. Y'all should seriously consider pursuing these leads, just the last decision volition take to be made by your PI. Afterward all, it is your PI who is paying the bills. When you are a PI, these volition be some of your more than difficult scientific decisions. When you are in this position, remember that an excursion into a new field need non exist permanent, only tin can be an exploratory expedition that may or may not lead to a permanent shift in management.
Avoid the P-word
Without going off the philosophical deep end, it is useful to occasionally pace away from the trenches of day-to-solar day enquiry and contemplate the nature of discoveries. Observations are statistical phenomena that can be verified beyond a shadow of uncertainty. For example, a dead mouse is really and truly dead. By contrast, conclusions are the product of human thought based on an existing theoretical framework that is imposed on a organization (that is, nature) that is inchoate and therefore essentially unknowable — for inspiration, see Huxley's translation of Goethe's view of nature (the system), which is the opening essay in the very showtime issue of Nature (the journal)2. Conclusions, therefore, are conditional; they are always incorrect or incomplete in some fashion, information technology'due south just a question of the degree to which they are incomplete (BOX two). Do non fall into the all too mutual habit of stating that your findings 'prove' a given conclusion. They don't, and thinking this fashion closes your listen to alternative explanations and time to come discoveries.
Remember — science should be fun
Well, that'due south near information technology. Here's one last bit of advice — scientific discipline is much more enjoyable and productive when information technology's fun (BOX 3). Maintain your sense of humour, particularly almost yourself. Higher up all, pass on the joy of science to the next generation.
Now become and find something that shocks everybody and makes your mother proud.
Acknowledgments
The writer is grateful to the many inferior and senior scientists who shared their insights into scientific success. B. Dolan, Yard. Grebe, S. Hensley and J. Ishizuka made valuable suggestions for improvements to the manuscript.
Footnotes
References
1. Yewdell JW. How to succeed in science: a concise guide for young scientists. Function I: taking the plunge. Nature Rev Mol Cell Biol. 2008 April 10; doi: ten.1038/nrm2389. [PMC complimentary article] [PubMed] [CrossRef] [Google Scholar]
2. Huxley Th. Nature: aphorisms by Goethe. Nature. 1869;1:9–eleven. [Google Scholar]
3. Goodman A. Intuition. The Dial Press, Runted Dell Publishing Grouping; 2007. [Google Scholar]
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675886/
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