Results 111 to 120 of about 1,551,832 (303)

Discovering Significant Topics from Legal Decisions with Selective Inference [PDF]

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalised regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually ...
arxiv   +1 more source

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

TAN-NTM: Topic Attention Networks for Neural Topic Modeling [PDF]

arXiv, 2020
Topic models have been widely used to learn text representations and gain insight into document corpora. To perform topic discovery, most existing neural models either take document bag-of-words (BoW) or sequence of tokens as input followed by variational inference and BoW reconstruction to learn topic-word distribution.
arxiv  

Multidimensional OMICs reveal ARID1A orchestrated control of DNA damage, splicing, and cell cycle in normal‐like and malignant urothelial cells

Molecular Oncology, EarlyView.
Loss of the frequently mutated chromatin remodeler ARID1A, a subunit of the SWI/SNF cBAF complex, results in less open chromatin, alternative splicing, and the failure to stop cells from progressing through the cell cycle after DNA damage in bladder (cancer) cells. Created in BioRender. Epigenetic regulators, such as the SWI/SNF complex, with important
Rebecca M. Schlösser, Florian Krumbach, Eyleen Corrales, Geoffroy Andrieux, Christian Preisinger, Franziska Liss, Alexandra Golzmann, Melanie Boerries, Kerstin Becker, Ruth Knüchel, Stefan Garczyk, Bernhard Lüscher   +11 more
wiley   +1 more source

ShcD adaptor protein drives invasion of triple negative breast cancer cells by aberrant activation of EGFR signaling

Molecular Oncology, EarlyView.
We identified adaptor protein ShcD as upregulated in triple‐negative breast cancer and found its expression to be correlated with reduced patient survival and increased invasion in cell models. Using a proteomic screen, we identified novel ShcD binding partners involved in EGFR signaling pathways.
Hayley R. Lau, Hayley S. Smith, Begüm Alural, Claire E. Martin, Laura A. New, Manali Tilak, Sara L. Banerjee, Hannah N. Robeson, Nicolas Bisson, Anne‐Claude Gingras, Jasmin Lalonde, Nina Jones   +11 more
wiley   +1 more source

Uncovering Flat and Hierarchical Topics by Community Discovery on Word Co-occurrence Network

Data Science and Engineering
Topic modeling aims to discover latent themes in collections of text documents. It has various applications across fields such as sociology, opinion analysis, and media studies.
Eric Austin, Shraddha Makwana, Amine Trabelsi, Christine Largeron, Osmar R. Zaïane   +4 more
doaj   +1 more source

A New Horizo-Vertical Distributed Feature Selection Approach

Cybernetics and Information Technologies, 2018
Feature selection technique has been a very active research topic that addresses the problem of reducing the dimensionality. Whereas, datasets are continuously growing over time both in samples and features number.
Zerhari B., Lehcen A. Ait, Mouline S.
doaj   +1 more source

Targeting the AKT/mTOR pathway attenuates the metastatic potential of colorectal carcinoma circulating tumor cells in a murine xenotransplantation model

Molecular Oncology, EarlyView.
Dual targeting of AKT and mTOR using MK2206 and RAD001 reduces tumor burden in an intracardiac colon cancer circulating tumor cell xenotransplantation model. Analysis of AKT isoform‐specific knockdowns in CTC‐MCC‐41 reveals differentially regulated proteins and phospho‐proteins by liquid chromatography coupled mass spectrometry. Circulating tumor cells
Daniel J. Smit, Thais Pereira‐Veiga, Helena Brauer, Michael Horn, Paula Nissen, Thomas Mair, Bente Siebels, Hannah Voß, Ruimeng Zhuang, Marie‐Therese Haider, Desiree Loreth, Margarita Iskhakova, Bele Lindemann, Julian Kött, Laure Cayrefourcq, Jasmin Wellbrock, Hartmut Schlüter, Klaus Pantel, Catherine Alix‐Panabières, Manfred Jücker   +19 more
wiley   +1 more source

Topic relevance and diversity in information retrieval from large datasets: A multi-objective evolutionary algorithm approach [PDF]

, 2017
Rocío L. Cecchini, Carlos M. Lorenzetti, Ana Gabriela Maguitman, Ignacio Ponzoni   +3 more
openalex   +1 more source