Each node corresponds to a possible metastatic state and is represented by a binary string which signifies which organ is positive or negative for metastases. For convenience the nodes are named from 1 to 18. The rates are obtained from the flow rates in the anatomic network (Fig 3) by considering the rate at which individual sites become positive based on the state of the other sites.</p
The tumour cells spread either via regional lymph nodes or directly to the lung where they form meta...
<p>The ISIS algorithm identified four independent binary partition classifications (splits) of 129 o...
The formation of metastases is driven by the ability of cancer cells to disseminate from the site of...
Each node corresponds to a possible metastatic state and is represented by a binary string which sig...
Each panel corresponds to a site/organ and shows the probability of finding a metastases at the site...
<p>Nodes represent the state of the model and arcs represent the transition of patient from one stat...
Introduction: Ovarian cancer is caused by malignant changes in the cells of the ovary. In various st...
Abstract: Ovarian cancer is the most lethal gynecologic malignancy. Despite advances in chemotherapy...
Ovarian cancer is the most lethal gynecologic malignancy. Despite advances in chemotherapy, the five...
This figure shows the reconstructed signaling network from a combination of databases. An arrow show...
<p>Ellipses define the four different health states of the model (HIV−, HIV+, HIV++ and Death). The ...
The formation of metastases is driven by the ability of cancer cells to disseminate from the site of...
Ovarian cancer is usually diagnosed at an advanced stage, rendering the possibility of cure unlikely...
<p>The four candidate ovarian cancer-related genes are colored in red, ovarian cancer-related genes ...
<p>The discrete landscape including 97 nodes (representing the GRN states) and 192 links (representi...
The tumour cells spread either via regional lymph nodes or directly to the lung where they form meta...
<p>The ISIS algorithm identified four independent binary partition classifications (splits) of 129 o...
The formation of metastases is driven by the ability of cancer cells to disseminate from the site of...
Each node corresponds to a possible metastatic state and is represented by a binary string which sig...
Each panel corresponds to a site/organ and shows the probability of finding a metastases at the site...
<p>Nodes represent the state of the model and arcs represent the transition of patient from one stat...
Introduction: Ovarian cancer is caused by malignant changes in the cells of the ovary. In various st...
Abstract: Ovarian cancer is the most lethal gynecologic malignancy. Despite advances in chemotherapy...
Ovarian cancer is the most lethal gynecologic malignancy. Despite advances in chemotherapy, the five...
This figure shows the reconstructed signaling network from a combination of databases. An arrow show...
<p>Ellipses define the four different health states of the model (HIV−, HIV+, HIV++ and Death). The ...
The formation of metastases is driven by the ability of cancer cells to disseminate from the site of...
Ovarian cancer is usually diagnosed at an advanced stage, rendering the possibility of cure unlikely...
<p>The four candidate ovarian cancer-related genes are colored in red, ovarian cancer-related genes ...
<p>The discrete landscape including 97 nodes (representing the GRN states) and 192 links (representi...
The tumour cells spread either via regional lymph nodes or directly to the lung where they form meta...
<p>The ISIS algorithm identified four independent binary partition classifications (splits) of 129 o...
The formation of metastases is driven by the ability of cancer cells to disseminate from the site of...