We then integrated cell landscapes from eight representative metazoan species to study gene regulation across evolution. Using these uniformly constructed cross-species landscapes, we developed a deep-learning-based strategy, Nvwa, to predict gene expression and identify regulatory sequences at the single...
The increasing availability of large-scale single-cell atlases has enabled the detailed description of cell states. In parallel, advances in deep learning allow rapid analysis of newly generated query datasets by mapping them into reference atlases. However, existing data transformations learned to map ...
In this work, we present DANCE as a deep learning library and benchmark platform to facilitate research and development for single-cell analysis. DANCE provides an end-to-end toolkit to facilitate single-cell analysis algorithm development and fair performance comparison on different benchmark datasets...
As seen above, more and more research efforts attempt to explore the potential of deep learning in the prediction of DNA methylations, and certain progress has been made in the improvement of predictive performance. However, existing deep learning predictors have not fully explored the power of fe...
The utilisation of convolutional neural networks in detecting pulmonary nodules: a review. Br J Radiol 2018;91:20180028. 4. Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional d...
2.2. Deep learning We used our previously developed algorithm for RGB-based tree identification, which was used at a single site (Weinstein et al., 2019). This method uses the Retinanet one-stage object detector (Gaiser et al., 2018) with a Resnet-50 classification backbone, which allows ...
(1) to select and optimize multiple DL architectures depending on the respective features of single-cell hypercubes, and compare their discriminative performance with conventional machine learning (ML) methods, (2) to develop “Fusion-Net” by stacking multiple DL frameworks using fusion strategy and...
To strengthen its competitive edge, the Company plans to significantly increase its AI-focused R&D efforts. By integrating resources accumulated over the past four years and deploying DeepSeek locally, the Company will leverage targeted algorithms and AI-driven data mining to perform cross-database, ...
Single-cell sequencing is a crucial tool for dissecting the cellular intricacies of complex diseases. Its prohibitive cost, however, hampers its application in expansive biomedical studies. Traditional cellular deconvolution approaches can infer cell typ
More specifically, we introduce MEISTER, a framework of MS for integrative single-cell and tissue analysis with deep-learning-based reconstruction that integrates high-throughput MS platforms with several technical innovations: (1) a deep-learning-based signal reconstruction approach capable of producing ...