Results 51 to 60 of about 112,978 (252)

Spatial heterogeneity of hotspot mutations and clonal relatedness in ovarian endometrioid carcinoma

Molecular Oncology, EarlyView.
Spatially resolved analysis revealed heterogeneous distributions of selected cancer‐associated mutations within ovarian endometrioid carcinomas. Shared mutations between paired endometrial and ovarian tumors supported clonal relatedness. These findings highlight the value of sampling multiple tumor regions when interpreting molecular profiles ...
Takahito Ashihara, Kosuke Murakami, Shiro Takamatsu, Akiko Kanto, Seiichi Mori, Tomoyuki Otani, Kazuko Sakai, Yasushi Kotani, Kazuto Nishio, Kaoru Abiko, Noriomi Matsumura   +10 more
wiley   +1 more source

Tumour‐proximal deep serum proteomics identifies biomarkers associated with ovarian cancer

Molecular Oncology, EarlyView.
New biomarkers are needed for early ovarian cancer detection. Ovarian (tumour‐proximal) and peripheral vein serum from healthy women and patients with benign or malignant tumours underwent nanoparticle‐enriched deep proteomics. Ovarian serum yielded more protein identifications and revealed tumour‐reflective signatures.
Darren Lau, Daniel Pincher, Clifford Young, Nicholas Chappell, Noor A. Lokman, Parul Mittal, Leigh Donnellan, Martin K. Oehler, Doug A. Brooks, Peter Hoffmann   +9 more
wiley   +1 more source

Deep learning-driven medical image analysis for computational material science applications

Frontiers in Materials
IntroductionDeep learning has significantly advanced medical image analysis, enabling precise feature extraction and pattern recognition. However, its application in computational material science remains underexplored, despite the increasing need for ...
Li Lu, Mingpei Liang
doaj   +1 more source

The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection

Molecular Oncology, EarlyView.
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński, Krzysztof Pastuszak, Anna Samelak‐Czajka, Zuzanna Cemka, Paulina Jackowiak, Tomasz Stefaniak, Sylwia Łapińska‐Szumczyk, Jacek Jassem, Anna J. Żaczek, Matthew T. Rondina, Myron G. Best, Sjors G. J. G. In 't Veld, Anna Supernat   +12 more
wiley   +1 more source

Imaging mass spectrometry data reduction: Automated feature identification and extraction [PDF]

Journal of the American Society for Mass Spectrometry, 2010
Imaging MS now enables the parallel analysis of hundreds of biomolecules, spanning multiple molecular classes, which allows tissues to be described by their molecular content and distribution. When combined with advanced data analysis routines, tissues can be analyzed and classified based solely on their molecular content.
McDonnell, L.A., Remoortere, A. van, Velde, N. de, Zeijl, R.J.M. van, Deelder, A.M.   +4 more
openaire   +3 more sources

Automated FRAP microscopy for high‐throughput analysis of protein dynamics in chromatin organization and transcription

FEBS Open Bio, EarlyView.
RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz, Bart Geverts, Johan A. Slotman, Andrea Sacchetti, Stefan Prekovic, Martin E. van Royen, Adriaan B. Houtsmuller   +6 more
wiley   +1 more source

Unsupervised Categorization of Hysteresis Loops: A Comparative Study of Expert-Driven Feature Engineering vs. Deep 1D-Convolutional Autoencoders

Engineering Proceedings
Hysteresis defines a system’s state as a function of its historical trajectory, manifesting as path-dependent loops where variables diverge based on the direction of change. Intrinsic to both information storage and irreversible thermodynamic dissipation,
Ivelin Karageorgiev, Sevil Ahmed-Shieva, Nikola Shakev, Ivaylo Minev   +3 more
doaj   +1 more source

Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies

FEBS Open Bio, EarlyView.
We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli, Mohammad Nour Alsamsam, Ugnė Bagdonaitė, Van Truc Vu, Chun‐Jen Huang, Polina Kuzhir, Mindaugas Zaremba, Aurimas Kopūstas, Marijonas Tutkus   +8 more
wiley   +1 more source

Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability [PDF]

Neuroinformatics
Abstract This paper introduces the Automated Lesion and Feature Extraction (ALFE) pipeline, an open-source, Python-based pipeline that consumes MR images of the brain and produces anatomical segmentations, lesion segmentations, and human-interpretable imaging features describing the lesions in the brain.
Reza Eghbali, Pierre Nedelec, David A. Weiss, Radhika Bhalerao, Long Xie, Jeffrey D. Rudie, Chunlei Liu 0004, Leo P. Sugrue, Andreas M. Rauschecker   +8 more
openaire   +3 more sources

RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells

FEBS Open Bio, EarlyView.
RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour, Christine Volmert, Valentina Piano   +2 more
wiley   +1 more source