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Anish M S on Muck Rack

Anish M S

As seen in: Bioinformatics, Oxford Academic, Biomed Central (BMC)
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Articles by Anish M S

PHIStruct: Improving phage-host interaction prediction at low sequence similarity settings using structure-aware protein embeddings

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By mark M, Bioinformatics Lab, De La Salle, Anish M S
| Bioinformatics Verified
We present PHIStruct, a multilayer perceptron that takes in structure-aware embeddings of receptor-binding proteins, generated via the structure-aware protein language model SaProt, and then predicts the host from among the ESKAPEE genera. Compared against recent tools, PHIStruct exhibits the best balance of precision and recall, with the highest and most stable F1 score across a wide range of confidence thresholds and sequence similarity settings.
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DNA-protein quasi-mapping for rapid differential gene expression analysis in non-model organisms - BMC Bioinformatics

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By Anish M S, Bioinformatics Lab, Kyle Christian L
| Biomed Central (BMC)
References Vijay N, Poelstra JW, Künstner A, Wolf JBW. Challenges and strategies in transcriptome assembly and differential gene expression quantification a. comprehensive in-silico assessment of RNA-seq experiments. Mol Ecol. 2012;22(3):620–34. Article PubMed Google Scholar Hsieh P-H, Oyang Y-J, Chen C-Y. Effect of de novo transcriptome assembly on transcript quantification. Sci Rep. 2019;9(1):8304. Article PubMed PubMed Central Google Scholar Shrestha AMS, Guiao JEB, Santiago KCL.
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RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci

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By Bioinformatics Lab, De La Salle, mark M, Anish M S
| Oxford Academic Verified
Rice is a global food staple feeding half of humanity. To address the dual concerns of meeting the demands of a growing world population while minimizing contribution to climate change, scientists and breeders are continually seeking genetic sources for high-yield, sustainable, and robust rice varieties [1]. Paramount to this task are the identification and elucidation of the genetic and molecular basis of agronomically important traits.
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