Harmonizing semantic annotations for computational models in biology

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol.Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the Computational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation

Relationship between fatigue index and number of repetition maxima with sub-maximal loads in Biceps Curl

The aim of this study was to investigate the relationship between the number of repetition maxima to volitional failure (RM) at 60%, 75%, 90% of 1RM and fatigue index (FI), a determinant of the muscular endurance level. Thirty four resistance trained male participants attended two testing sessions. The first session was conducted to assess 1RM load and RM at 60%, 75% and 90% of 1RM in the supine biceps curl (SBC) exercise. In the second session, a FI test protocol consisting of five sets of SBC with 90 s rest between sets was performed to determine FI values. Each set was performed to volitional failure using a sub-maximal load in the range of 15-20RM. Hypothetical high FI and low FI groups (17 participants with the highest and lowest FI values, respectively) were formed for statistical analyses. ANOVA results revealed that RM at 60%, 75%, 90% of 1RM were not significantly different between FI groups when controlled for mean repetition tempo (p=0.11, p=0.38, p=0.13, respectively). Pearson's correlation coefficients revealed that no significant relationship was present between FI values and RM at 60%, 75%, 90% of 1RM (p=0.40, p=0.46, p=0.14, respectively). In conclusion, the muscular endurance level of participants defined in terms of FI value was not an indicator of RM in SBC. Therefore, athletes with different muscular endurance levels can use similar percentages of 1RM in biceps curl exercise in their training programs when the aim is to elicit training adaptations related to specific RM zones. © Editorial Committee of Journal of Human Kinetics