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Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating…

Genomics · Quantitative Biology 2017-01-02 Junhua Zhang , Shihua Zhang

Recent breakthroughs in cancer research have come via the up-and-coming field of pathway analysis. By applying statistical methods to prior known gene and protein regulatory information, pathway analysis provides a meaningful way to…

Genomics · Quantitative Biology 2017-10-11 Yue Zhao

Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently…

Molecular Networks · Quantitative Biology 2021-06-15 Michael A. Kochen , Steven S. Andrews , H. Steven Wiley , Song Feng , Herbert M. Sauro

BACKGROUND: Breast cancer has emerged as one of the most prevalent cancers among women leading to a high mortality rate. Due to the heterogeneous nature of breast cancer, there is a need to identify differentially expressed genes associated…

Machine Learning · Computer Science 2021-11-30 Sheetal Rajpal , Ankit Rajpal , Manoj Agarwal , Naveen Kumar

The pathogenesis of cancer in human is still poorly understood. With the rapid development of high-throughput sequencing technologies, huge volumes of cancer genomics data have been generated. Deciphering those data poses great…

Genomics · Quantitative Biology 2016-04-06 Junhua Zhang , Shihua Zhang

We propose a methodology for the identification of transcription factors involved in the deregulation of genes in tumoral cells. This strategy is based on the inference of a reference gene regulatory network that connects transcription…

Molecular Networks · Quantitative Biology 2020-04-20 Magali Champion , Julien Chiquet , Pierre Neuvial , Mohamed Elati , François Radvanyi , Etienne Birmelé

Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identifying the key factors of a biological network that are…

Applications · Statistics 2014-09-02 Lisa M. Pham , Luis Carvalho , Scott Schaus , Eric D. Kolaczyk

Cells regulate themselves via dizzyingly complex biochemical processes called signaling pathways. These are usually depicted as a network, where nodes represent proteins and edges indicate their influence on each other. In order to…

Molecular Networks · Quantitative Biology 2021-01-13 David Merrell , Anthony Gitter

Identifying driver genes is crucial for understanding oncogenesis and developing targeted cancer therapies. Driver discovery methods using protein or pathway networks rely on traditional network science measures, focusing on nodes, edges,…

Molecular Networks · Quantitative Biology 2024-10-01 Rodrigo Henrique Ramos , Yago Augusto Bardelotte , Cynthia de Oliveira Lage Ferreira , Adenilso Simao

The advent of high--throughput transcription profiling technologies has enabled identification of genes and pathways associated with disease, providing new avenues for precision medicine. A key challenge is to analyze this data in the…

Quantitative Methods · Quantitative Biology 2019-01-11 Sahil D. Shah , Rosemary Braun

Cancer cell lines have frequently been used to link drug sensitivity and resistance with genomic profiles. To capture genomic complexity in cancer, the Cancer Genome Project (CGP) (Garnett et al., 2012) screened 639 human tumor cell lines…

Applications · Statistics 2017-02-09 Hongmei Liu , J. Sunil Rao

The explosion of data throughout the biomedical sciences provides unprecedented opportunities to learn about the dynamics of evolution and disease progression, but harnessing these large and diverse datasets remains challenging. Here, we…

Quantitative Methods · Quantitative Biology 2019-12-03 Sam F. Greenbury , Mauricio Barahona , Iain G. Johnston

Identifying altered pathways that are associated with specific cancer types can potentially bring a significant impact on cancer patient treatment. Accurate identification of such key altered pathways information can be used to develop…

Machine Learning · Statistics 2017-12-05 Sunho Park , Tae Hyun Hwang

Cancer is a complex disease driven by dynamic regulatory shifts that cannot be fully captured by individual molecular profiling. We employ a data-driven approach to construct a coarse-grained dynamic network model based on hallmark…

Quantitative Methods · Quantitative Biology 2025-02-28 Jiahe Wang , Yan Wu , Yuke Hou , Yang Li , Dachuan Xu , Changjing Zhuge , Yue Han

Individual cancer cells carry a bewildering number of distinct genomic alterations i.e., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here we performed…

Accurate prediction of cancer progression remains a challenge due to the high heterogeneity of molecular omics data across patients. While biologically informed models have improved the interpretability of these predictions, a persistent…

Machine Learning · Computer Science 2026-04-21 Koushik Howlader , Md Tauhidul Islam , Wei Le

One of the important issues in oncology is finding the genes that perturbation the cell functionality, and result in cancer propagation. The genes, namely driver genes, when they mutate in expression, result in cancer through activation of…

Molecular Networks · Quantitative Biology 2020-12-16 Mostafa Akhavansafar , Babak Teimourpour

Finding cancer driver genes has been a focal theme of cancer research and clinical studies. One of the recent approaches is based on network structural controllability that focuses on finding a control scheme and driver genes that can steer…

Molecular Networks · Quantitative Biology 2022-06-14 Xizhe Zhang , Chunyu Pan , Xinru Wei , Meng Yu , Shuangjie Liu , Jun An , Jieping Yang , Baojun Wei , Wenjun Hao , Yang Yao , Yuyan Zhu , Weixiong Zhang

We present an applied study in cancer genomics for integrating data and inferences from laboratory experiments on cancer cell lines with observational data obtained from human breast cancer studies. The biological focus is on improving…

Applications · Statistics 2010-10-07 Daniel Merl , Julia Ling-Yu Chen , Jen-Tsan Chi , Mike West

Gallbladder cancer (GBC) is the most frequent cause of disease among biliary tract neoplasms. Identifying the molecular mechanisms and biomarkers linked to GBC progression has been a significant challenge in scientific research. Few recent…

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