RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left" rowspan="2">Residue</td><td class="align_center" colspan="2">Positive windows</td><td class="align_center">Negative</td></tr><tr class="thead"><td class="align_center">Before</td><td class="align_center">After</td><td class="align_center">Used</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Ser</td><td class="align_center">20577</td><td class="align_center">1554</td><td class="align_center">1543</td></tr><tr><td class="align_left">Thr</td><td class="align_center">5596</td><td class="align_center">707</td><td class="align_center">453</td></tr><tr><td class="align_left">Tyr</td><td class="align_center">2124</td><td class="align_center">267</td><td class="align_center">226</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

The number of windows before and after redundancy removal for size = 9.

BioMed Research International

tab2

Table 2

Table 2: RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest 