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Raja, K.

Publications and source records attributed to Raja, K..

2 recordsLinked to original sources

A haplotype-resolved genome assembly of the Nile rat facilitates exploration of the genetic basis of diabetes

The Nile rat (Avicanthis niloticus) is an important animal model for biomedical research, including the study of diurnal rhythms and type 2 diabetes. Here, we report a 2.5 Gb, chromosome-level reference genome assembly with fully resolved parental haplotypes, generated with the Vertebrate Genomes Project (VGP). The assembly is highly contiguous, with contig N50 of 11.1 Mb, scaffold N50 of 83 Mb, and 95.2% of the sequence assigned to chromosomes. We used a novel workflow to identify 3,613 segmental duplications and quantify duplicated genes. Comparative analyses revealed unique genomic features of the Nile rat, including those that affect genes associated with type 2 diabetes and metabolic dysfunctions. These include 14 genes that are heterozygous in the Nile rat or highly diverged from the house mouse. Our findings reflect the exceptional level of genomic detail present in this assembly, which will greatly expand the potential of the Nile rat as a model organism for genetic studies.

genomics↗

SKiM - A generalized literature-based discovery system for uncovering novel biomedical knowledge from PubMed

Literature-based discovery (LBD) uncovers undiscovered public knowledge by linking terms A to C via a B intermediate. Existing LBD systems are limited to process certain A, B, and C terms, and many are not maintained. We present SKiM (Serial KinderMiner), a generalized LBD system for processing any combination of A, Bs, and Cs. We evaluate SKiM via the rediscovery of discoveries by Don Swanson, who pioneered LBD. Using only literature from the 19th century up to a year before Swansons discoveries, SKiM uncovers all five discoveries. We apply SKiM to repurposing drugs for 26 conditions of high prevalence. Manual analysis confirmed 65 discoveries useful for four diseases from Swansons discoveries from one to 31 years prior to their first validation by clinical trials. SKiM predicts many new potential drug candidates representing prime targets for wet lab validation. SKiM can be applied to any biomedical inquiry sufficiently mentioned in the literature.

bioinformatics↗