NetworKIN analysis of BIC VUSs affecting biologically characterized phosphorylation motifs in BRCA1 and BRCA2.

<p>In <b>bold</b> are BRCA1 mutations that directly mutate an experimentally identified phosphorylation site. ^aThe position and change at the amino acids specified by the missense variant is as reported in the BIC database. ^bThe nucleotide change conforms to the HGVS nomenclature. ^cSNP IDs correspond to the dbSNP database <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062468#pone.0062468-Sherry1" target="_blank">[73]</a> SNP identifiers. ^dFrequency represents the number of times reported in the BIC database. ^eThe ten-residue long biologically uncharacterized kinase recognition motifs are shown. The biologically uncharacterized Serine (S), and threonine (T) residues shown to be phosphorylated by NetworKIN are underlined.</p

Figure 1

<p><b>a.</b> Summary of phosphorylation sites studied in BRCA1. Residues in green represent <i>in vivo</i> phosphorylation sites have been biologically characterized in the literature. Residues in red represent <i>in vivo</i> phosphorylation sites identified via throughput methods where biological functions have not yet been determined. <b>b.</b> Summary of phosphorylation sites studied in BRCA2. Residues in green represent <i>in vivo</i> phosphorylation sites that have been biologically characterized in the literature. Residues in red represent <i>in vivo</i> phosphorylation sites identified via throughput methods where biological functions have not yet been determined.</p

NetworKIN analysis of VUS affecting biologically uncharacterized phosphorylation sites in BRCA1 and BRCA2.

<p>In <b>bold</b> are BRCA1 mutations that fall within an experimentally identified but biologically uncharacterized phosphorylation site. ^aThe position and change at the amino acids specified by the missense variant is as reported in the BIC database. ^bThe nucleotide change conforms to the HGVS nomenclature. ^cSNP IDs correspond to the dbSNP database <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062468#pone.0062468-Sherry1" target="_blank">[73]</a> SNP identifiers. ^dFrequency represents the number of times reported in the BIC database. ^eThe ten-residue long biologically uncharacterized kinase recognition motifs are shown. The biologically uncharacterized Serine (S), and threonine (T) residues shown to be phosphorylated by NetworKIN are underlined. * Sites that retained a score but was considered to be “abolished” due to score falling below 5 with the presence of the VUS.</p

Multiple sequence alignment demonstrating phylogenetic conservation of the three biologically characterized phosphorylated BRCA2 residues affected by missense variants of unknown clinical significance.

<p>Multiple sequence alignment demonstrating phylogenetic conservation of the three biologically characterized phosphorylated BRCA2 residues affected by missense variants of unknown clinical significance.</p

Additional file 1: of Associations of single nucleotide polymorphisms with mucinous colorectal cancer: genome-wide common variant and gene-based rare variant analyses

Table S1. Top ten most significant common SNPs identified based on the univariable analyses and the subsequent multivariable analyses under the additive genetic models. Table S2. Top ten most significant common SNPs identified based on the univariable analyses and the subsequent multivariable analysis under the dominant genetic models. Table S3. Top ten most significant common SNPs identified based on the univariable analyses and the subsequent multivariable analyses under the recessive genetic models. Table S4. Top ten most significant common SNPs identified under the univariable analyses and the subsequent multivariable analyses under the co-dominant genetic models. Table S5. Baseline characteristics selected through a stepwise variable selection method under the multivariable model. Table S6. AIC estimates under the multivariable models of common SNPs identified in the univariable analysis. Table S7. Haploreg results for the top 10 SNPs in the common variant analysis. Table S8. Proteins which have reported evidence of binding to the genomic region in which kgp10457679 resides (extracted from RegulomeDB). (PDF 360 kb

Kaplan-Meier curves for the <i>BRM</i>-741 indel under the co-dominant genetic model in the colorectal cancer cases.

<p>P value of the log-rank test is 0.017.</p

<i>BRM</i> promoter indels and progression-free survival in colorectal cancer.

<p><i>BRM</i> promoter indels and progression-free survival in colorectal cancer.</p

Epidemiological approach to assess risk factors and current distortion incidence on distribution networks

A methodology based on epidemiological analysis for assessing risk factors and harmonic distortion incidence rate in a distribution network is proposed in this paper. The methodology analyzes the current harmonics emission risk at the PCC due to the connection of disturbing loads. These loads are modeled and multiple loads connection scenarios are simulated using Monte Carlo Algorithms. From the simulation results, potential risk factors for critical harmonics indicators are identified, leading to a classification of the scenarios into groups of exposed or unexposed to risk factors. Finally, the incidence rate of harmonics is calculated for each load connection scenario and the risk of critical harmonics scenarios due to the exposure to risk factors is estimated

Associations between <i>BRM</i> promoter indels and colon cancer risk.

<p>Associations between <i>BRM</i> promoter indels and colon cancer risk.</p

Additional file 2: of Mitochondrial DNA polymorphisms, its copy number change and outcome in colorectal cancer

Table S2. Results of the univariate analyses for the clinicopathological features (SNP genotyped cohort)