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Malpica, N.

Publications and source records attributed to Malpica, N..

2 recordsLinked to original sources

In silico analysis and molecular investigation of the nuclear shuttle protein-interacting kinase 1 (NIK1) in six Solanaceous species

The first layer of innate immunity in plants is initiated through the perception of microbe-associated molecular patterns (MAMPs) or damage-associated molecular patterns (DAMPs) by pattern recognition receptors (PRRs). MAMP/DAMP perception initiates downstream defense responses, a process which ultimately leads to pattern triggered immunity (PTI). In Arabidopsis, the nuclear shuttle protein-interacting kinase 1 (NIK1), among other PRRs, is one of the most important central components of PTI signaling and kinase signaling cascade, since it is involved in the plant antiviral response against geminiviruses. Despite the characterization of the structure and function of the NIK1 receptors made by some groups, studies related to NIK1 importance in the current gene-editing era are missing. By simple in silico analysis, in this study we investigated the NIK1 homologues from six Solanaceous plant species including: tomato (Solanum lycopersicum), potato (Solanum tuberosum), Solanum pennellii, eggplant (Solanum melongena), pepper (Capsicum annum), and Nicotiana benthamiana. The phylogenetic analyses of different NIK1 proteins from Arabidopsis and six Solanaceous plants revealed nine different clades. As expected, we found that these NIK1 orthologs have similar genomic structures suggesting a similar function. We could identify that SotubNIK1, SolyNIK1, SopenNIK1, CANIK1, NibenNIK1, SmeNIK1 have the highest sequence homology with AtNIK1. Additionally, the conserved protein kinase domain (PKD) that is present in NIK1 from Arabidopsis thaliana was bioinformatically analyzed and found in other species. As this highly conserved NIK1 region is present in several crops of economic importance, its potential is highlighted as a possible target site for gene editing, to develop crops tolerant to geminiviral infections.

bioinformatics↗

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-the-art algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, ...), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.

neuroscience↗