It's All in the Mix: A New Interprofessional, Blended-Learning Masters' Program for Biomedical Data Science Addressing Physicians and Students from Life Sciences - Didactic Concept and First Experiences.

Progress in methods for biomedical research, such as multi-omics analyses and in data-driven healthcare, such as new procedures in diagnostic imaging lead, along with the rising availability of additional data sources, to a growing demand for experts in biomedical data analysis. Addressing this need in academic education and the challenge of interdisciplinary teamwork in the biomedical domain, the authors have designed and implemented a new Master's program for biomedical data science that accepts students with different educational backgrounds, medical doctors, veterinarians and students with a Bachelor's degree in life sciences, and incorporates blended learning. This paper aims to present the didactic concept of the program, report on feedback from the students and first evaluation results, and discuss the benefits and drawbacks of this approach. Our results show that the program is well-accepted by the students, who stress the benefits of working in interprofessional teams, the option for part-time study along with their jobs with flexible learning opportunities, and of good and intensive interaction offers with their peers and teachers. Readjustments are necessary to improve tutoring support and alignment of content among distinct modules and to decrease workload peaks. While our evaluation results are still preliminary, we are convinced that our approach of mostly online offers, yet with a strong focus on teamwork, practical exercises guided by experts and communication skills, may serve to educate students to be well-prepared for their future tasks and operations in biomedical data science, in research, clinical care and industry.

Conflict Resolution for Mesozoic Mammals: Reconciling Phylogenetic Incongruence Among Anatomical Regions.

The evolutionary history of Mesozoic mammaliaformes is well studied. Although the backbone of their phylogeny is well resolved, the placement of ecologically specialized groups has remained uncertain. Functional and developmental covariation has long been identified as an important source of phylogenetic error, yet combining incongruent morphological characters altogether is currently a common practice when reconstructing phylogenetic relationships. Ignoring incongruence may inflate the confidence in reconstructing relationships, particularly for the placement of highly derived and ecologically specialized taxa, such as among australosphenidans (particularly, crown monotremes), haramiyidans, and multituberculates. The alternative placement of these highly derived clades can alter the taxonomic constituency and temporal origin of the mammalian crown group. Based on prior hypotheses and correlated homoplasy analyses, we identified cheek teeth and shoulder girdle character complexes as having a high potential to introduce phylogenetic error. We showed that incongruence among mandibulodental, cranial, and postcranial anatomical partitions for the placement of the australosphenidans, haramiyids, and multituberculates could largely be explained by apparently non-phylogenetic covariance from cheek teeth and shoulder girdle characters. Excluding these character complexes brought agreement between anatomical regions and improved the confidence in tree topology. These results emphasize the importance of considering and ameliorating major sources of bias in morphological data, and we anticipate that these will be valuable for confidently integrating morphological and molecular data in phylogenetic and dating analyses.

Sharing is caring? Measurement error and the issues arising from combining 3D morphometric datasets.

Geometric morphometrics is routinely used in ecology and evolution and morphometric datasets are increasingly shared among researchers, allowing for more comprehensive studies and higher statistical power (as a consequence of increased sample size). However, sharing of morphometric data opens up the question of how much nonbiologically relevant variation (i.e., measurement error) is introduced in the resulting datasets and how this variation affects analyses. We perform a set of analyses based on an empirical 3D geometric morphometric dataset. In particular, we quantify the amount of error associated with combining data from multiple devices and digitized by multiple operators and test for the presence of bias. We also extend these analyses to a dataset obtained with a recently developed automated method, which does not require human-digitized landmarks. Further, we analyze how measurement error affects estimates of phylogenetic signal and how its effect compares with the effect of phylogenetic uncertainty. We show that measurement error can be substantial when combining surface models produced by different devices and even more among landmarks digitized by different operators. We also document the presence of small, but significant, amounts of nonrandom error (i.e., bias). Measurement error is heavily reduced by excluding landmarks that are difficult to digitize. The automated method we tested had low levels of error, if used in combination with a procedure for dimensionality reduction. Estimates of phylogenetic signal can be more affected by measurement error than by phylogenetic uncertainty. Our results generally highlight the importance of landmark choice and the usefulness of estimating measurement error. Further, measurement error may limit comparisons of estimates of phylogenetic signal across studies if these have been performed using different devices or by different operators. Finally, we also show how widely held assumptions do not always hold true, particularly that measurement error affects inference more at a shallower phylogenetic scale and that automated methods perform worse than human digitization.

Development of microsatellite primers in the protected species Viola elatior (Violaceae) using next-generation sequencing.

PREMISE OF THE STUDY: Viola elatior (Violaceae) is a Eurasian perennial plant species in which French populations are threatened by anthropogenic pressures. Microsatellite primers were developed to investigate its genetic structure and diversity. METHODS AND RESULTS: Eight microsatellite markers were isolated using next-generation sequencing. Loci were amplified and screened for 138 individuals in 17 populations from France. Two of the eight polymorphic loci presented no variability across populations. The total number of alleles per locus varied from two to four. Observed heterozygosity ranged from 0.051 to 1.000. All primers amplified successfully in the closely related species V. pumila. CONCLUSIONS: This set of microsatellites offers a valuable tool for assessing population genetic diversity of the species to improve its conservation and base management efforts. High observed heterozygosity values probably reflect the particular mating system of the species and suggest an important tendency to clonality.