Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules

Background
It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein networks are one particular network type of special importance, because proteins form the functional base units of every biological cell. On a mesoscopic level of protein networks, modules are of significant importance because these building blocks may be the next elementary functional level above individual proteins allowing to gain insight into fundamental organizational principles of biological cells.
Results
In this paper, we provide a comparative analysis of five popular and four novel module detection algorithms. We study these module prediction methods for simulated benchmark networks as well as 10 biological protein interaction networks (PINs). A particular focus of our analysis is placed on the biological meaning of the predicted modules by utilizing the Gene Ontology (GO) database as gold standard for the definition of biological processes. Furthermore, we investigate the robustness of the results by perturbing the PINs simulating in this way our incomplete knowledge of protein networks.
Conclusions
Overall, our study reveals that there is a large heterogeneity among the different module prediction algorithms if one zooms-in the biological level of biological processes in the form of GO terms and all methods are severely affected by a slight perturbation of the networks. However, we also find pathways that are enriched in multiple modules, which could provide important information about the hierarchical organization of the system

Gaining biological perspectives from schistosome genomes

Characterization of the genomic basis underlying schistosome biology is an important strategy for the development of future treatments and interventions. Genomic sequence is now available for the three major clinically relevant schistosome species, Schistosoma mansoni, S. japonicum and S. haematobium, and this information represents an invaluable resource for the future control of human schistosomiasis. The identification of a biologically important, but distinct from the host, schistosome gene product is the ultimate goal for many research groups. While the initial elucidation of the genome of an organism is critical for most biological research, continued improvement or curation of the genome construction should be an ongoing priority. In this review we will discuss prominent recent findings utilizing a systems approach to schistosome biology, as well as the increased use of interference RNA (RNAi). Both of these research strategies are aiming to place parasite genes into a more meaningful biological perspective.

Statistical modelling of the rheological and mucoadhesive properties of aqueous poly(methylvinylether-co-maleic acid) networks: Redefining biomedical applications and the relationship between viscoelasticity and mucoadhesion

Poly(methylvinylether-co-maleic acid) (PMVE/MA) is commonly used as a component of pharmaceutical platforms, principally to enhance interactions with biological substrates (mucoadhesion). However, the limited knowledge on the rheological properties of this polymer and their relationships with mucoadhesion has negated the biomedical use of this polymer as a mono-component platform. This study presents a comprehensive study of the rheological properties of aqueous PMVE/MA platforms and defines their relationships with mucoadhesion using multiple regression analysis. Using dilute solution viscometry the intrinsic viscosities of un-neutralised PMVE/MA and PMVE/MA neutralised using NaOH or TEA were 22.32 ± 0.89 dL g-1, 274.80 ± 1.94 dL g-1 and 416.49 ± 2.21 dL g-1 illustrating greater polymer chain expansion following neutralisation using Triethylamine (TEA). PMVE/MA platforms exhibited shear-thinning properties. Increasing polymer concentration increased the consistencies, zero shear rate (ZSR) viscosities (determined from flow rheometry), storage and loss moduli, dynamic viscosities (defined using oscillatory analysis) and mucoadhesive properties, yet decreased the loss tangents of the neutralised polymer platforms. TEA neutralised systems possessed significantly and substantially greater consistencies, ZSR and dynamic viscosities, storage and loss moduli, mucoadhesion and lower loss tangents than their NaOH counterparts. Multiple regression analysis enabled identification of the dominant role of polymer viscoelasticity on mucoadhesion (r > 0.98). The mucoadhesive properties of PMVE/MA platforms were considerable and were greater than those of other platforms that have successfully been shown to enhance in vivo retention when applied to the oral cavity, indicating a positive role for PMVE/MA mono-component platforms for pharmaceutical and biomedical applications.

CoO nanoparticles embedded in three-dimensional nitrogen/sulfur co-doped carbon nanofiber networks as a bifunctional catalyst for oxygen reduction/evolution reactions

High-performance and low-cost bifunctional electrocatalysts play crucial roles in oxygen reduction and evolution reactions. Herein, a novel three-dimensional (3D) bifunctional electrocatalyst was prepared by embedding CoO nanoparticles into nitrogen and sulfur co-doped carbon nanofiber networks (denoted as CoO@N/S-CNF) through a facile approach. The carbon nanofiber networks were derived from a nanostructured biological material which provided abundant functional groups to nucleate and anchor nanoparticles while retaining its interconnected 3D porous structure. The composite possesses a high specific surface area and graphitization degree, which favors both mass transport and charge transfer for electrochemical reaction. The CoO@N/S-CNF not only exhibits highly efficient catalytic activity towards oxygen reduction reaction (ORR) in alkaline media with an onset potential of about 0.84 V, but also shows better stability and stronger resistance to methanol than Pt/C. Furthermore, it only needs an overpotential of 1.55 V to achieve a current density of 10 mA cm^-2, suggesting that it is an efficient electrocatalyst for oxygen evolution reaction (OER). The ΔE value (oxygen electrode activity parameter) of CoO@N/S-CNF is calculated to be 0.828 V, which demonstrates that the composite could be a promising bifunctional electrocatalyst for both ORR and OER.