Hello!
Since I started my doctoral studies, I have noticed that there has been an emphasis and shift towards multidisciplinary approaches that can leverage the knowledge of biology and engineering towards a holistic exploration of biological systems. While there is an expectation that new results can be built on the knowledge from existing literature, existing data and methods may need to be reanalysed to facilitate their interpretation in the light of new findings. This is also applicable from the perspective of a research group, where incremental advances are made while trying to follow a clear line of research. On this note, I would like to expand on some of the approaches we consider in our group when discussing new results and explore ways to integrate the scientific results we have been obtaining over the years.
Brainstorming
One of the first essential aspects is to assemble or create opportunities for an interdisciplinary team to discuss our scientific results. The most straightforward way, in our case, has been to incorporate scientific discussions in team meetings (intended initially to sort logistic matters) and group meetings. Often, all it takes is a figure panel that someone is preparing for a conference abstract or manuscript to kickstart a discussion on the topic and identify aspects that need to be polished, either in the work presented or as a group effort in future projects. As hinted in a previous post, and due to the diverse audience present, not all ideas and suggestions produced may be technically feasible, but they are valuable in identifying areas that can be readily addressed or require further exploration. Still, one struggle we have observed is that there is often not enough time to actually reach a clear solution, requiring several meetings to address the main items identified initially. In any case, these presentations and scientific discussions have been tremendously positive in sharing knowledge within the group and, at least, produced an abundance of ideas for the presenter to consider in their next steps.
Implementation
On that note, the second element I would like to address is the implementation of those ideas. It is expected and assumed that whoever is driving a project is interested in seeing it succeed, which translates to a drive and motivation to experiment with possible approaches until a solution addresses the concerns raised in the team discussion. Nonetheless, it is often the case that several iterations are needed until a functional outcome is achieved. Here, my experience has been that it takes time to implement ideas that sound good into reproducible methods. Not only do we have to investigate if the result is plausible, but we also need an extra level of attention to spot bugs and overlooked operations since we are, ultimately, developing ideas in uncharted territory where the results can turn out to be unexpected.
Furthermore, I have found it extremely helpful to intentionally protect time to think about the problems we are trying to solve. After several hours of attempts and collecting a reasonable amount of practical experience with the implementation challenges, I aim to go for a walk or do sports, which will move my attention towards something else but keep my mind thinking about the problem. Eventually, I have noticed that I often reach new ideas, which help me get closer to a functional solution.
Verification
At last, it is crucial to verify our implementation. This can be one of the most challenging steps, but it is also among the most important. If our proposed solution is intended to work, we need to confidently show that it behaves as expected and produces understandable results consistently and reproducibly. In my case, mainly working with computational analysis, we often have to resort to verifying the results rather than properly validating the analysis since we typically cannot independently produce additional data in experiments that could be used for validation purposes. In any case, a standard approach is to pick up datasets from previous studies focusing on different aspects of our research topic (e.g., bone healing, bone adaptation, bone loss), apply our solution and explore if the outcomes are meaningful and aligned with our hypothesis and expectations. If we can confidently see the trends we aimed to identify, then we can be more confident that the implementation proposed works as expected. Ultimately, these new results are brought in again into another team meeting so that we can ensure that the novel analysis is understood by all colleagues and reasonable based on their experience and scientific background. If there are still unresolved questions, this cycle can be repeated until a successful outcome is reached.
Conclusion
It has been gratifying to be part of a diverse interdisciplinary team, especially when it motivates and enables each member to push scientific knowledge in our projects. While it can be difficult and stressful to manage such discussions, filter the relevant content and go through high-intensity coding sessions to reach a working solution, the joy of reaching a new insight and the drive to advance science is gratifying. For this reason, even as I am approaching the end of my project, I am excited to finalise my results and share them with the community in a research article.
Please feel free to share your thoughts about your process to discuss science!
Have a great day!