Aggregating new biological models

Written by Louis Joslyn - November 09, 2020
Figure 1

Screenshot of BioSimBoard.

BioSimBoard: aggregating new biological models so you can quickly find new research

Searching through scientific literature for mathematical or computational models in biology is a difficult and at times frustrating process. As mathematical biologists, we often find ourselves at the cross-section of multiple fields and are asked to communicate results to mathematicians, engineers, immunologists, biologists, or statisticians. As such, our published models and their results are located within and across various journals and fields. In an effort to alleviate wasted time and effort to locate these models, I developed BioSimBoard, a model-aggregator that allows users to quickly identify the latest articles in model development and application.

Inspiration for BioSimBoard

The importance of literature review became quite apparent when I joined my dissertation lab at the University of Michigan. Crucially, the literature review for my first few projects was focused only on a few specific biological questions and modeling techniques. Within this narrow scope, searching for relevant papers was relatively easy given a few keywords and the power of Google Scholar. Even still, I remember searching for the ‘perfect paper’ as a first-year student. To no avail, I searched endlessly for a paper that outlined the development of a mechanistic model that mapped differentiation and proliferation of CD4+ T cells in response to different Mycobacterium tuberculosis antigens. (Later, I published that exact paper!)

As I started to develop a firmer grasp of the tuberculosis modeling literature, I wondered about modeling techniques employed in other fields. In part, this curiosity was brought on by viewing incredible subgroup talks at the Society of Mathematical Biology meetings that revealed new and interesting applications of modeling. Now, as I transition from a graduate student into a more independent researcher, I find myself inspired to expand my knowledge of modeling techniques and the fields in which they can be applied.

Initially, I broadened my literature review through traditional means. I signed up for email alerts from journals, scoured preprint archives weekly, and became more intentional about who I followed on Twitter. As a matter of personal preference, and amid an ocean of emails and notifications, I quickly realized that this was not the most efficient method to identify new and exciting modeling manuscripts. In short, I wanted one place where I could access the latest scientific literature on biological models and simulations. With this in mind, I created my own model aggregation website called BioSimBoard.

What is BioSimBoard?

Briefly, BioSimBoard works like other famous news aggregation websites, i.e., which has similar goals – to provide one location that aggregates breaking news and information in real time using RSS (Really Simple Syndication) feeds. While these feeds have recently declined in popularity as search engine optimization algorithms have grown more powerful, the feeds still allow the transfer of information from one website to another without user intervention. Instead of using RSS feeds from news sites, BioSimBoard utilizes RSS feeds from journals to aggregate newly published biological models.

BioSimBoard has four pages: model board, job board, podcast board, and past features. On the model board, which is also the home page, many journals and preprints are listed, along with titles of the most recently published works. Users can click on titles and will be sent directly to the article’s online journal entry. Throughout the day, the links are autonomously updated to reflect the most recent papers published. Some journals publish more often than others. Hence some paper links on BioSimBoard are not updated as quickly.

Importantly, BioSimBoard links are pre-filtered such that only papers that include a mathematical or computational framework are listed. When implementing this feature, I could have used a custom python implementation (or your favorite coding language) to parse for keywords like “modeling” since RSS is XML-formatted plain text. However, I decided not to reinvent the wheel, and used a plug-in for this purpose.

In addition to journal links, BioSimBoard searches Twitter and lists the most recent tweets that utilize the #mathbio, #compbio, and #systemsbiology hashtags. Like the model board page, BioSimBoard also lists a job board and a podcast board, which are filtered to include jobs/episodes focused on modeling.

On the fourth page, I occasionally select a new tool, model or finding for a featured write-up. As the viewership for BioSimBoard grows, I anticipate including more features. In fact, in the next week, I will be highlighting the most viewed BioSimBoard paper in October.

Reach out and provide feedback!

If you or your colleagues have a paper that should be considered for a feature, please reach out. In fact, I would be happy to link any job postings on the job board as well.

My hope for BioSimBoard is to provide mathematical biologists a place to identify new literature and modeling techniques. I suggest quickly scanning the page during your morning coffee - as I do!

← Previous Post Next Post