Manipal University

About: Manipal University is a education organization based out in Manipal, Karnataka, India. It is known for research contribution in the topics: Population & Medicine. The organization has 9525 authors who have published 11207 publications receiving 110687 citations.

Thousands of large-scale RNA sequencing experiments yield a comprehensive new human gene list and reveal extensive transcriptional noise

Abstract: We assembled the sequences from 9,795 RNA sequencing experiments, collected from 31 human tissues and hundreds of subjects as part of the GTEx project, to create a new, comprehensive catalog of human genes and transcripts. The new human gene database contains 43,162 genes, of which 21,306 are protein-coding and 21,856 are noncoding, and a total of 323,824 transcripts, for an average of 7.5 transcripts per gene. Our expanded gene list includes 4,998 novel genes (1,178 coding and 3,819 noncoding) and 97,511 novel splice variants of protein-coding genes as compared to the most recent human gene catalogs. We detected over 30 million additional transcripts at more than 650,000 sites, nearly all of which are likely to be nonfunctional, revealing a heretofore unappreciated amount of transcriptional noise in human cells.

An Improved Multivariate Chart Using Partial Least Squares With Continuous Ranked Probability Score

Abstract: Reliable fault detection systems in industrial processes provide pertinent information for improving the safety and process reliability and reducing manpower costs. Here, we present a flexible and efficient fault detection approach based on the continuous ranked probability score (CRPS) metric to detect faults in multivariate data. This approach merges partial least squares (PLS) models and the CRPS metric to separate normal from abnormal features by simultaneously taking advantage of the feature representation ability of a PLS and the fault detection capacity of a CRPS-based scheme. The proposed approach uses PLS to generate residuals, and then apply the CRPS-based chart to reveal any abnormality. Specifically, two monitoring schemes based on the CRPS measure have been introduced in this paper. The first approach uses the Shewhart scheme to evaluate the CRPS of the response variables residuals from the PLS model. The second approach merges the CRPS into the exponentially weighted moving average monitoring chart. We assess the effectiveness of these approaches by using real and simulated distillation column data. We also compare the detection quality of PLS-based CRPS charts with that of PLS-based $T^{2}$ , $Q$ , multivariate cumulative sum, and multivariate exponentially weighted moving average methods. Results show that the capacity of the proposed scheme can reliably detect faults in multivariate processes.

A comprehensive manually curated reaction map of RANKL/RANK-signaling pathway

Abstract: Receptor activator of nuclear factor-kappa B ligand (RANKL) is a member of tumor necrosis factor (TNF) superfamily that plays a key role in the regulation of differentiation, activation and survival of osteoclasts and also in tumor cell migration and bone metastasis. Osteoclast activation induced by RANKL regulates hematopoietic stem cell mobilization as part of homeostasis and host defense mechanisms thereby linking regulation of hematopoiesis with bone remodeling. Binding of RANKL to its receptor, Receptor activator of nuclear factor-kappa B (RANK) activates molecules such as NF-kappa B, mitogen activated protein kinase (MAPK), nuclear factor of activated T cells (NFAT) and phosphatidyl 3-kinase (PI3K). Although the molecular and cellular roles of these molecules have been reported previously, a systematic cataloging of the molecular events induced by RANKL/RANK interaction has not been attempted. Here, we present a comprehensive reaction map of the RANKL/RANK-signaling pathway based on an extensive manual curation of the published literature. We hope that the curated RANKL/RANK-signaling pathway model would enable new biomedical discoveries, which can provide novel insights into disease processes and development of novel therapeutic interventions. Database URL: http://www.netpath.org/pathways?path_id=NetPath_21