Hadooping the genome: The impact of big data tools on biology

A (metaphorical) moment for RNA-based biotechnology? : Current metaphors for RNA limit development of and public communication about RNA-based technologies

Technical and societal hurdles are both likely to hinder the development of RNA biotechnologies. The use of current metaphors to describe RNA and its function could be an important factor for a common challenge.

Groundwork for AI: Enforcing a benchmark for neoantigen prediction in personalized cancer immunotherapy

This article expands on recent studies of machine learning or artificial intelligence (AI) algorithms that crucially depend on benchmark datasets, often called 'ground truths.' These ground-truth datasets gather input-data and output-targets, thereby establishing what can be retrieved computationally and evaluated statistically. I explore the case of the Tumor nEoantigen SeLection Alliance (TESLA), a consortium-based ground-truthing project in personalized cancer immunotherapy, where the 'truth' of the targets-immunogenic neoantigens-to be retrieved by the would-be AI algorithms depended on a broad technoscientific network whose setting up implied important organizational and material infrastructures. The study shows that instead of grounding an undisputable 'truth', the TESLA endeavor ended up establishing a contestable reference, the biology of neoantigens and how to measure their immunogenicity having slightly evolved alongside this four-year project. However, even if this controversy played down the scope of the TESLA ground truth, it did not discredit the whole undertaking. The magnitude of the technoscientific efforts that the TESLA project set into motion and the needs it ultimately succeeded in filling for the scientific and industrial community counterbalanced its metrological uncertainties, effectively instituting its contestable representation of 'true' neoantigens within the field of personalized cancer immunotherapy (at least temporarily). More generally, this case study indicates that the enforcement of ground truths, and what it leaves out, is a necessary condition to enable AI technologies in personalized medicine.

DNA as in-formation

Traces are fundamental vectors of information. This is the first of seven forensic principles formulated by the 2022 Sydney declaration. To better understand the trace as information, this article proposes the notion of in-formation. DNA is matter in becoming. DNA changes as it travels across forensic sites and domains. New formations occur as humans, technologies and DNA interact. Understanding DNA as in-formation is of particular relevance vis-à-vis the increase of algorithmic technologies in the forensic sciences and the rendering of DNA into (big) data. The concept can help identifying, acknowledging and communicating those moments of techno-scientific interaction that require discretion and methodical decisions. It can assist in tracing what form DNA will take and what consequences this may have. This article is categorized under:Crime Scene Investigation > From Traces to Intelligence and EvidenceForensic Biology > Ethical and Social ImplicationsForensic Biology > Forensic DNA Technologies.

Why epigenetics is (not) a biosocial science and why that matters

Epigenetic modifications offer compelling evidence of the environmental etiology of complex diseases. Social and biographical conditions, as well as material exposures, all modulate our biology with consequences for risk predispositions and health conditions. Elucidating these complex biosocial loops is one of the main challenges animating epigenetics. Yet, research on the development of epigenetic biomarkers often pulls in a direction that departs from a view of biological determinants of health embedded in their social and material environment. Taking the example of the epigenetics of cardiovascular diseases, this paper illustrates how common understandings of epigenetic biomarkers strongly lean toward considering them as mere targets for molecular intervention, rather than as correlates of a complex biological and social patterning of disease. This reductionism about biosocial dynamics of disease, we argue, hampers the pursuit of the goals epigenetics has given itself (in cardiology and beyond). If epigenetic mechanisms point to the deep socio-environmental embeddedness of our health, we conclude, future designs and methods of this research may require an improved methodological consideration of a biosocial perspective.

Complicated legacies: The human genome at 20

Millions of people today have access to their personal genomic information. Direct-to-consumer services and integration with other “big data” increasingly commoditize what was rightly celebrated as a singular achievement in February 2001 when the first draft human genomes were published. But such remarkable technical and scientific progress has not been without its share of missteps and growing pains. Science invited the experts below to help explore how we got here and where we should (or ought not) be going.