Support vector machine algorithms in the search of KIR gene associations with disease

KIR Genes and Patterns Given by the A Priori Algorithm: Immunity for Haematological Malignancies

“…This rule also refers to the genes KIR2DL2 and KIR2DL5, which are also inhibitory but not present in this haplotype which can be thought of more likely to tolerate tumours in our study population (with strict absence of KIR2DS2), that is, Mexican mestizos of San Luis Potosi State. This pattern was not discovered with previous studies on the same study population [ 33 ]. The methodology proposed in this paper provides a new insight into the analysis of datasets that allow researchers to find biomarkers for cancer and other diseases.…”

“…Previous findings based on our data employing multivariate analysis of KIR carrier frequencies with a traditional statistical comparison (contingency tables using Pearson's or Fishers' exact test [ 31 ]) revealed only that KIR2DL2 was more frequent amongst patients with haematological malignancy in comparison to the healthy donors ( p ≤ 0.0001). Decision trees (ID3 algorithm [ 32 ]) generated at 50% and 75% training data also provided support the importance of KIR2DL2 [ 33 ]. Other findings produced with the ID3 algorithm on our similar data suggest a protective effect for (i) cB03 motif (KIR2DL3, KIR2DL5, KIR2DS5, KIR2DP1, and KIR2DL1 genes) in agreement with KIR3DS1-2DL5-2DS5-2DS1 genotype with protection from Hodgkin's lymphoma [ 34 ]; (ii) KIR3DS1 gene (only provided a protective effect when observed in the absence of KIR2DL2 or KIR2DL5 genes) as suggested previously [ 25 , 34 , 35 ]; and (iii) KIR2DS1 when present together with KIR2DL2, KIR2DS2, and KIR2DL3 but in the absence of KIR3DL1 [ 33 ].…”

“…Nevertheless, the ID3 algorithm failed to find associations related to the KIR2DS3, as described previously by others researchers [ 35 – 37 ]. Neither KIR2DL1 nor KIR2DL3 are on their own important factors in the ID3 decision processes [ 33 ]. One reason is that the ID3 algorithm is based only on entropy of information, which could not identify other patterns with this measure of information.…”

“…The a priori algorithm is an algorithm that belongs to the family of data mining algorithms in the field of machine learning and artificial intelligence [ 39 – 41 ]. Regarding classification algorithms, previous research has already described the potential that support vector machines (SVM) have [ 33 ], as well as that of other state-of-the-art classification algorithms including Deep Neural Networks and Convolutional Neural Networks [ 42 ]. Moreover, research on classification algorithms is also focusing on creating an ensemble of classifiers such as LibD3C [ 43 ].…”

Gene Network Biological Validity Based on Gene-Gene Interaction Relevance

“…The left column in the figure represents the study for pure random topology, and the rightmost shows the scale-free topology. Each graph contains five lines that encode the behavior of GeneNetVal considering the distance levels from one to four and the precision measure [30, 39] for the classical use of KEGG. In total, more than 11000 (3 input networks × 2 topologies × 5 measures/levels × 385 networks) evaluations were carried out.…”