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We calculate measures of hierarchy in gene and tissue networks of breast cancer patients. We find that the likelihood of metastasis in the future is correlated with increased values of network hierarchy for expression networks of…

Molecular Networks · Quantitative Biology 2014-01-21 Man Chen , Michael W. Deem

Metastasis is a leading cause of cancer-related mortality and remains challenging to detect during early stages. Accurate identification of cancers likely to metastasize can improve treatment strategies and patient outcomes. This study…

Genomics · Quantitative Biology 2024-12-03 Benjamin Osafo Agyare , Alec Chu , Blessing Oloyede

Cancer is a term that denotes a group of diseases caused by abnormal growth of cells that can spread in different parts of the body. According to the World Health Organization (WHO), cancer is the second major cause of death after…

Machine Learning · Computer Science 2023-01-31 Fadi Alharbi , Aleksandar Vakanski

Abnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can…

Molecular Networks · Quantitative Biology 2017-11-28 Fengdan Ye , Dongya Jia , Mingyang Lu , Herbert Levine , Michael W Deem

We present a three-stage probabilistic model for the progression of Chronic Myeloid Leukemia (CML), as manifested by the leukemic stem cells, progenitor cells and mature leukemic cells. This progression is captured through the process of…

Populations and Evolution · Quantitative Biology 2022-04-25 Sonjoy Pan , Siddhartha P. Chakrabarty , Soumyendu Raha

The ALL-1 gene is directly involved in 5-10% of ALLs and AMLs by fusion to other genes or through internal rearrangements. DNA microarrays were utilized to determine expression profiles of ALLs and AMLs with ALL-1 rearrangements. These…

A key aim of systems biology is the reconstruction of molecular networks, however we do not yet have networks that integrate information from all datasets available for a particular clinical condition. This is in part due to the limited…

We have analyzed gene expression data from 3 different kinds of samples: normal human tissues, human cancer cell lines and leukemic cells from lymphoid and myeloid leukemia pediatric patients. We have searched for genes that are over…

Tissues and Organs · Quantitative Biology 2009-11-11 Joseph Lotem , Dvir Netanely , Eytan Domany , Leo Sachs

Leukemia, the cancer of blood cells, originates in the blood-forming cells of the bone marrow. In Chronic Myeloid Leukemia (CML) conditions, the cells partially become mature that look like normal white blood cells but do not resist…

Genomics · Quantitative Biology 2023-02-09 Madiha Hameed , Muhammad Bilal , Tuba Majid , Abdul Majid , Asifullah Khan

Motivation: The consistent amount of different types of omics data requires novel methods of analysis and data integration. In this work we describe Regression2Net, a computational approach to analyse gene expression and methylation…

Computational Engineering, Finance, and Science · Computer Science 2015-07-06 Francesco Gadaleta , Kyrylo Bessonov

Chronic Myeloid Leukemia (CML) is a biphasic malignant clonal disorder that progresses, first with a chronic phase, where the cells have enhanced proliferation only, and then to a blast phase, where the cells have the ability of…

Quantitative Methods · Quantitative Biology 2022-07-14 Suryadeepto Nag , Ananda Shikhara Bhat , Siddhartha P. Chakrabarty

Reconstruction of gene regulatory networks is the process of identifying gene dependency from gene expression profile through some computation techniques. In our human body, though all cells pose similar genetic material but the activation…

We explore how Deep Learning (DL) can be utilized to predict prognosis of acute myeloid leukemia (AML). Out of TCGA (The Cancer Genome Atlas) database, 94 AML cases are used in this study. Input data include age, 10 common cytogenetic and…

Machine Learning · Computer Science 2018-11-01 Mei Lin , Vanya Jaitly , Iris Wang , Zhihong Hu , Lei Chen , Md. Amer Wahed , Zeyad Kanaan , Adan Rios , Andy N. D. Nguyen

Acute myeloid leukaemia (AML) is a type of blood and bone marrow cancer characterized by the proliferation of abnormal clonal haematopoietic cells in the bone marrow leading to bone marrow failure. Over the course of the disease, angiogenic…

Applications · Statistics 2025-07-23 Qiquan Wang , Anna Song , Antoniana Batsivari , Dominique Bonnet , Anthea Monod

Tumors are defined by their intense proliferation, but sometimes cancer cells turn senescent and stop replicating. In the stochastic cancer model in which all cells are tumorigenic, senescence is seen as the result of random mutations,…

Tissues and Organs · Quantitative Biology 2013-08-29 Caterina A. M. La Porta , Stefano Zapperi , James P. Sethna

Recent advances in high-throughput genomic technologies coupled with exponential increases in computer processing and memory have allowed us to interrogate the complex aberrant molecular underpinnings of human disease from a genome-wide…

Genomic alterations lead to cancer complexity and form a major hurdle for a comprehensive understanding of the molecular mechanisms underlying oncogenesis. In this review, we describe the recent advances in studying cancer-associated genes…

Molecular Networks · Quantitative Biology 2007-12-24 Edwin Wang , Anne Lenferink , Maureen O'Connor-McCourt

Acute Myeloid Leukemia (AML) is one of the most aggressive types of hematological neoplasm. To support the specialists' decision about the appropriate therapy, patients with AML receive a prognostic of outcomes according to their…

Machine Learning · Computer Science 2024-05-30 Jade M. Almeida , Giovanna A. Castro , João A. Machado-Neto , Tiago A. Almeida

Clusters of circulating tumor cells (CTCs), although rare, may account for more than 95% of metastases. Inflammatory breast cancer (IBC) is a highly aggressive subtype that chiefly metastasizes via CTC clusters. Theory suggests that…

Molecular Networks · Quantitative Biology 2017-11-28 Shubham Tripathi , Mohit Kumar Jolly , Wendy A. Woodward , Herbert Levine , Michael W. Deem

We develop a modeling framework for cancer progression that distinguishes the order of two possible mutations. Recent observations and information on myeloproliferative neoplasms are analyzed within our framework. In some patients with…

Molecular Networks · Quantitative Biology 2026-05-12 Yue Wang , Blerta Shtylla , Tom Chou
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