NETME: on-the-fly knowledge network construction from biomedical literature

Background The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks.

Scenes From Tick Physiology: Proteins of Sialome Talk About Their Biological Processes

Ticks are blood-sucking parasites with different strategies of feeding depending on the tick family. The major families are Ixodidae or Argasidae, being slow or fast feeders, respectively. In the recent years, the advances in molecular sequencing techniques have enabled to gain knowledge about the proteome of the tick’s salivary glands. But an holistic view of the biological processes underlying the expression of the sialome has been neglected. In this study we propose the use of standard biological processes as a tool to draw the physiology of the tick’s salivary glands. We used published data on the sialome of Rhipicephalus sanguineus s.l. (Ixodidae) and Ornithodoros rostratus (Argasidae). A partial set of proteins obtained by these studies were used to define the biological process(es) in which proteins are involved. We used a directed network construction in which the nodes are proteins (source) and biological processes (target), separately for the low-level processes (“children”) and the top-level ones (“parents”). We applied the method to feeding R. sanguineus at different time slices, and to different organs of O. rostratus. The network connects the proteins and the processes with a strength directly proportional to the transcript per millions of each protein. We used PageRank as a measure of the importance of each biological process. As suggested in previous studies, the sialome of unfed R. sanguineus express about 30% less biological processes than feeding ticks. Another decrease (25%) is noticed at the middle of the feeding and before detachment. However, top-level processes are deeply affected only at the onset of feeding, demonstrating a redundancy in the feeding. When ixodid-argasid are compared, large differences were observed: they do not share 91% of proteins, but share 90% of the biological processes. However, caution must be observed when examining these results. The hypothesis of different proteins linked to similar biological process(es) in both ticks is an extreme not confirmed in this study. Considering the limitations of this study, carried out with a selected set of proteins, we propose the networks of proteins of sialome linked to their biological processes as a tool aimed to explain the biological processes behind families of proteins.

Candidate microRNA Biomarkers in Lupus Nephritis: A Meta-Analysis of Profiling Studies in Kidney, Blood and Urine Samples

Lupus nephritis (LN) is a kidney disease caused by systemic lupus erythematosus in which kidneys are attacked by the immune system. MiRNAs participate in the pathogenesis of LN as modulatory effectors in immune responses and nephrogenesis pathways. Despite the large number of miRNAs that are expressed deferentially, identifying the most suitable biomarker candidate for LN is challenging. The aim of this study was to introduce a consensus panel of potential miRNA biomarkers by performing a meta-analysis of miRNA profiles in the kidney, blood, and urine samples of LN patients. A comprehensive literature review approach was considered to find LN-related miRNA expression profiles. After including the 41 eligible studies and performing the data extraction, meta-analysis was done based on the vote-counting rank strategy and as well as meta-analysis of p-value. The result of the meta-analysis was three lists of consensus miRNAs with altered expression profiles in the various tissue samples of LN patients. Of the 13 studies on kidney tissue, the meta-miRNAs were let-7a, miR-198, let-7e, miR-145, and miR-26a. In addition, meta-miRNAs of miR-199a, miR-21, miR-423, miR-1260b, miR-589, miR-150, miR-155, miR-146a, and miR-183 from 21 studies on blood samples, and miR-146a, miR-204, miR-30c, miR-3201, and miR-1273e from 11 studies on urine samples can be considered as non-invasive biomarker panels for LN. The meta-miRNAs and their related genes were subjected to functional enrichment analyses and network construction. Functional enrichment analysis confirmed the involvement of their target genes in nephropathy-related signaling pathways. Network construction showed miR-145-5p in blood and miR-155-5p in kidney, the best hob miRNAs as candidate drug targets. In conclusion using a meta-analysis approach, our study proposes three meta-miRNA panels that could be the target of further research to assess their potential as biomarkers / therapeutic targets in LN disease.

A Novel High-Dimensional Trajectories Construction Network based on Multi-Clustering Algorithm

A novel marine transportation network based on high-dimensional AIS data with a multi-level clustering algorithm is proposed to discover important waypoints in trajectories based on selected navigation features. This network contains two parts: the calculation of major nodes with CLIQUE and BIRCH clustering methods and navigation network construction with edge construction theory. Unlike the state-of-art work for navigation clustering with only ship coordinate, the proposed method contains more high-dimensional features such as drafting, weather, and fuel consumption. By comparing the historical AIS data, more than 220,133 lines of data in 30 days were used to extract 440 major nodal points in less than 4 minutes with ordinary PC specs (i5 processer). The proposed method can be performed on more dimensional data for better ship path planning or even national economic analysis. Current work has shown good performance on complex ship trajectories distinction and great potential for future shipping transportation market analytical predictions.