Modeling Systems: How IPA Helps Manchester Scientist


Adam Stevens, Senior Research Associate at The University of Manchester’s Institute of Human Development.

At The University of Manchester, network modeling expert Adam Stevens uses QIAGEN’s Ingenuity Pathway Analysis to predict upstream regulators, molecular activity, and more for integrated ’omics data sets.

A senior research associate in endocrine sciences at Manchester’s Institute of Human Development, Stevens uses his background in drug discovery on certain projects related to growth development. He deploys IPA for systems modeling, including predicting molecular activity and the function of upstream regulators. “My job is almost entirely in silico now,” Stevens says, “and I’m loving every minute of it.”

A publication in The Pharmacogenomics Journal describes a large study in which Stevens and his team pulled together metabolomic and transcriptomic data to create a detailed view of how growth rates differ for children born smaller than normal. “Insights into the pathophysiology of catch-up compared with non-catch-up growth in children born small for gestational age: an integrated analysis of metabolic and transcriptomic data,” a paper for which Stevens was lead author, reports biological differences between kids who later caught up to normal size and those who remained small for their age. In addition to being a useful source of information about differences in growth rates, the project was important because children who exhibit catch-up growth are more likely to develop cardiometabolic diseases later in life.

For this work, Stevens says, IPA played a key role in data analysis. “We used IPA because it has fantastic metabolomics features,” he notes. “It helped me decode what was going on in these two data sets.” The paper demonstrates Stevens’ first use of the new Molecule Activity Predictor tool in IPA, which helped reveal the primary functional relevance of the data. He also found the Upstream Regulator Analysis to be very powerful. “It’s elegantly accessed in IPA and is tied in with Mechanistic Networks and the Molecule Activity Predictor,” he says.

Stevens’ appreciation for in silico science means that he reserves the relatively expensive bench work for procedures that can’t be done any other way, such as validating computational observations. “Bench work is expensive and time-consuming,” he says. “An Ingenuity Pathway Analysis license is a lot more affordable than somebody who’s working with cell cultures and running all sorts of transfections.”

For more on Adam Stevens, including his scientific career path and how he uses IPA, check out this case study.