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Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

ABSTRACT: There is a growing appreciation for the network biology that regulates the coordinated expression of molecular and cellular markers however questions persist regarding the identifiability of these networks. Here we explore some of the issues relevant to recovering directed regulatory networks from time course data collected under experimental constraints typical of in vivo studies. NetSim simulations of sparsely connected biological networks were used to evaluate two simple feature selection techniques used in the construction of linear Ordinary Differential Equation (ODE) models, namely truncation of terms versus latent vector projection. Performance was compared with ODE-based Time Series Network Identification (TSNI) integral, and the information-theoretic Time-Delay ARACNE (TD-ARACNE). Projection-based techniques and TSNI integral outperformed truncation-based selection and TD-ARACNE on aggregate networks with edge densities of 10-30%, i.e. transcription factor, protein-protein cliques and immune signaling networks. All were more robust to noise than truncation-based feature selection. Performance was comparable on the in silico 10-node DREAM 3 network, a 5-node Yeast synthetic network designed for In vivo Reverse-engineering and Modeling Assessment (IRMA) and a 9-node human HeLa cell cycle network of similar size and edge density. Performance was more sensitive to the number of time courses than to sample frequency and extrapolated better to larger networks by grouping experiments. In all cases performance declined rapidly in larger networks with lower edge density. Limited recovery and high false positive rates obtained overall bring into question our ability to generate informative time course data rather than the design of any particular reverse engineering algorithm.

SUBMITTER: Vashishtha S

PROVIDER: S-EPMC4435750 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

Vashishtha Saurabh S Broderick Gordon G Craddock Travis J A TJ Fletcher Mary Ann MA Klimas Nancy G NG

PloS one 20150518 5

There is a growing appreciation for the network biology that regulates the coordinated expression of molecular and cellular markers however questions persist regarding the identifiability of these networks. Here we explore some of the issues relevant to recovering directed regulatory networks from time course data collected under experimental constraints typical of in vivo studies. NetSim simulations of sparsely connected biological networks were used to evaluate two simple feature selection tec ...[more]

PMID: 25984725

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Project description:BACKGROUND AND AIM:Understanding the maturation of upper limb (UL) movement characteristics in typically developing (TD) children is key to explore UL deficits in those with neurodevelopmental disorders. Three-dimensional motion analysis (3DMA) offers a reliable tool to comprehensively evaluate UL motion. However, studies thus far mainly focused on specific pre-defined parameters extracted from kinematic waveforms. Here, we investigated age-related differences in UL movement characteristics over the entire movement cycle in TD children. PARTICIPANTS AND METHODS:We assessed the non-dominant UL of 60 TD children (mean age 10y3m±3y1m) using 3DMA during eight tasks: reaching (forwards (RF), upwards (RU), sideways (RS)), reach-to-grasp (sphere (RGS), vertical cylinder (RGV)) and activities-of-daily-living mimicking tasks (hand-to-head (HTH), hand-to-mouth (HTM), hand-to-shoulder (HTS)). We investigated differences between four age-groups (5-7y, 8-10y, 11-12y, 13-15y) in: (1) spatiotemporal parameters (movement duration, peak velocity, time-to-peak velocity and trajectory straightness), and (2) 12 UL joint angles, using Statistical Parametric Mapping (SPM). RESULTS:We found that the 5-7y children moved with lower peak velocity and less straight trajectories compared to the 11-12y group (peak velocity: RS, HTS, p<0.01; trajectory: RU, RS, RGV, HTS, p<0.01) and the 13-15y group (peak velocity: RF, RS, RGS, RGV, HTH, HTS, p<0.01; trajectory, all tasks, p<0.01). The 5-7y children showed increased scapular protraction compared to older children (8-10y and 11-12y, HTS), as well as increased scapular medial rotation compared to the 13-15y group (RGS). During RU, the 5-7y children moved more towards the frontal plane (shoulder), unlike the 13-15y group. Lastly, the 5-7y group used less elbow flexion than older children (11-12y and 13-15y) during HTH and HTS. DISCUSSION AND CONCLUSION:In conclusion, our results point toward a maturation in UL movement characteristics up to age 11-12y, when UL motion seemed to reach a plateau. The reference values provided in this study will help to further optimize the interpretation of UL deficits in children with neurodevelopmental disorders.

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Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

Publications

Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

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