MOTIVATION: The cellular composition of a solid tissue can be assessed either through the physical dissociation of the tissue followed by single-cell analysis techniques or by computational deconvolution of bulk gene expression profiles. However, both approaches are prone to significant biases. Tissue dissociation often results in disproportionate cell loss, while deconvolution is hindered by biological and technological inconsistencies between the datasets it relies on. RESULTS: Using calibration datasets that include both experimentally measured and deconvolution-based cell compositions, we present a new method, Harp, which reconciles these approaches to produce more reliable deconvolution results in applications where only gene expression data is available. Both on simulated and real data, harmonizing cell reference profiles proved advantageous over competing state-of-the-art deconvolution tools, overcoming technological and biological batch effects. AVAILABILITY AND IMPLEMENTATION: R package available at https://github.com/spang-lab/harp (archived as 10.5281/zenodo.16851930). Code and data for reproducing the results of this paper are available at https://github.com/spang-lab/harplication (archived as 10.5281/zenodo.16851705) and https://doi.org/10.5281/zenodo.15650057, respectively.

This paper discusses “The Cybernetics Thought Collective: A History of Science and Technology Portal Project,” a collaborative effort among four institutions that maintain archival records vital to the exploration of cybernetic history — the University of Illinois at Urbana-Champaign, the American Philosophical Society, the British Library, and MIT. With recent grant funding from the NEH, the multi-institutional team is developing a prototype web-portal and analysis-engine to provide access to archival material related to the development of the field of cybernetics, which influenced the development of modern computing and provided a common language to articulate similar questions about behavior across disciplines — regardless of whether the subject of study was animal, machine, or social group. The project is also enabling the digitization of the personal archives of four founders of cybernetics — Heinz von Foerster, W. Ross Ashby, Warren S. McCulloch, and Norbert Wiener. Using computational methods based on advanced machine-learning algorithms to yield network and entity relationships maps from the digitized texts, this project seeks to create access to archival material that enables humanities scholars to better understand the development of cybernetic ideas and to enable scientists and engineers to reuse and access cybernetic data.