22 papers · ranked by Valyu relevance
Mario Deng, Johannes Brägelmann, Joachim L. Schultze, Sven Perner
Background The Cancer Genome Atlas (TCGA) is a pool of molecular data sets publicly accessible and freely available to cancer researchers anywhere around the world. However, wide spread use is limited since an advanced knowledge of statistics and statistical software is required. Results In order to improve…
Mohamed Mounir, Marta Lucchetta, Tiago C. Silva, Catharina Olsen + 6 more
The advent of Next-Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data. The Genomic Data…
Chenqi Liao, Xiong Wang
Background Pan-cancer analysis examines both the commonalities and heterogeneity among genomic and cellular alterations across numerous types of tumors. Pan-cancer analysis of gene expression, tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TIME), and methylation…
Mehmet Kemal Samur, Yu Xue
Background & Objective Managing data from large-scale projects (such as The Cancer Genome Atlas (TCGA)) for further analysis is an important and time consuming step for research projects. Several efforts, such as the Firehose project, make TCGA pre-processed data publicly available via web services and data portals…
Anna Díez-Villanueva, Izaskun Mallona, Miguel A. Peinado
Background The Cancer Genome Atlas (TCGA) offers a multilayered view of genomics and epigenomics data of many human cancer types. However, the retrieval of expression and methylation data from TCGA is a cumbersome and time-consuming task. Results Wanderer is an intuitive Web tool allowing real time access and…
M. Emre Kus, Cagatay Sahin, Emre Kilic, Arda Askin + 5 more
The Cancer Genome Atlas (TCGA) initiative has been essential for revealing key mechanisms in human cancer leading to the development of novel therapeutics. Analysis of the cancer transcriptomics data in the TCGA and other public repositories require coding skills that are associated with a steep learning curve for most…
Mohamed Mounir, Tiago C. Silva, Marta Lucchetta, Catharina Olsen + 4 more
The advent of Next Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data. The Genomic Data…
Arata Hayashi, Shmuel Ruppo, Elisheva E. Heilbrun, Chiara Mazzoni + 4 more
The Cancer Genome Atlas (TCGA) and other projects provide informative tumor-associated genomic data for the broad research community. Hence, several useful web-based tools have been generated to ease non-expert users with the analysis and characterization of a specific gene behavior in selected tumors. However, none of…
Tonmoy Das, Geoffroy Andrieux, Musaddeque Ahmed, Sajib Chakraborty
The manifestations of cancerous phenotypes necessitate alterations at different levels of information-flow from genome to proteome. The molecular alterations at different information processing levels serve as the basis for the cancer phenotype to emerge. To understand the underlying mechanisms that drive the…
Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti, Rebeca Sanz‐Pamplona + 5 more
'Rebeca Sanz‐Pamplona' 'De Luca' 'Giancarlo Mauri' 'Vı́ctor Moreno' 'Marco Antoniotti' 'Bud Mishra'] | 1 Introduction | 3 | | --- | --- | | 2 The PicNic pipeline | 6 | | 2.1 Reducing inter-tumor heterogeneity by cohort subtyping | 6 | | 2.2 Selection of driver events | 7 | | 2.3 Fitness equivalence of exclusive…
Haoyang Cai, Nitin Kumar, Michael Baudis
Background: The delineation of genomic copy number abnormalities (CNAs) from cancer samples has been instrumental for identification of tumor suppressor genes and oncogenes and proven useful for clinical marker detection. An increasing number of projects have mapped CNAs using high-resolution microarray based…
Hai Yang, Yuhang Sheng, Yi Jiang, Xiaoyang Fang + 3 more
'Jing Zhang' 'Zhe Wang'] Results: This study proposed Subtype-Former, a deep learning method based on MLP and Transformer Block, to extract the low-dimensional representation of the multi-omics data. K-means and Consensus Clustering are also used to achieve accurate subtyping results. We compared Subtype- Former with…
Santhilata Kuppili Venkata, Dimitra Repana, Joel Nulsen, Lisa Dressler + 5 more
The Network of Cancer Genes (NCG) is a manually curated repository of 2,372 genes whose somatic modification is known or predicted to have a cancer driver role. These genes were collected from 275 publications, including two sources of known cancer genes and 273 cancer sequencing screens of 119 cancer types in 31…
David Tuck
Objectives A novel graph data model of non-small cell lung cancer clinical and genomic data has been constructed with two aims: (1) provide a suitable model for facilitating graph analytics within the Neo4j framework or through tools which can interact through existing Neo4j APIs; and (2) provide a base model…
Siqi Xiang, Siyao Liu, Charles M. Perou, Kai Zhang + 1 more
In The Cancer Genome Atlas (TCGA) data set, there are many interesting nonlinear dependencies between pairs of genes that reveal important relationships and subtypes of cancer. Such genomic data analysis requires a rapid, powerful and interpretable detection process, especially in a high-dimensional environment. We…
Jose A. Bird
We introduce RegNetAgents, an AI-oriented multi-agent framework for structured, query-driven regulatory candidate identification across heterogeneous gene regulatory networks. The system enables unified analysis of bulk tumor and single-cell-derived ARACNe networks by integrating TCGA-derived cancer networks with…
Lei Su, Yang Du
Structure Semantic Segmentation in Whole Slide Image Authors: ['Lei Su' 'Yang Du'] We focus on tertiary lymphoid structure (TLS) semantic segmentation in whole slide image (WSI). Unlike TLS binary segmentation, TLS semantic segmentation identifies boundaries and maturity, which requires integrating contextual…
Jose A. Bird
CASCADE is an agentic framework that predicts downstream transcriptional effects of gene perturbation from precomputed ARACNe regulatory networks, exposed via MCP. Prior work validates such tools by checking whether predicted genes are known cancer genes (membership); we instead test whether the predicted direction of…
Amartya Singh, Gyan Bhanot, Hossein Khiabanian
Clustering approaches that rely on a large number of variables, such as expression levels of thousands of genes, are often not well adapted to address the complexity and heterogeneity of tumors where small sets of genes may drive multiple cellular processes associated with carcinogenesis. Biclustering algorithms that…
Rumiana Tenchov, Aparna Sapra, Janet Sasso, Krittika Ralhan + 3 more
Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcome thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of…
Jacob R. Bradley, Timothy I. Cannings
We introduce a novel data-driven framework for the design of targeted gene panels for estimating exome-wide biomarkers in cancer immunotherapy. Our first goal is to develop a generative model for the profile of mutation across the exome, which allows for gene- and variant type-dependent mutation rates. Based on this…
Authors not listed
Immuno-oncology, a rapidly evolving field at the forefront of cancer research, leverages the body’s immune system to fight cancer. In this follow up report, we extend our natural language processing (NLP)-based analysis to pinpoint the context of emergence of the previously identified emerging concepts. To achieve this…