...are systematically studied, revealing power-law scaling in data-rich single-cell transcriptomics, but negligible scaling when data is limited.
...are systematically studied, revealing power-law scaling in data-rich single-cell transcriptomics, but negligible scaling when data is limited.
integrates quant. annealing with novel NNs to enhance drug-likeness of generated molecules beyond training data.
integrates quant. annealing with novel NNs to enhance drug-likeness of generated molecules beyond training data.
forecasts future cardiac events by enabling long signal inference via a specialized ECG encoder for cross-understanding with text, trained with LLM methods.
forecasts future cardiac events by enabling long signal inference via a specialized ECG encoder for cross-understanding with text, trained with LLM methods.
Aligns & combines multimodal feats (via copula trans. & multi-rel. attn.) to overcome fixed graph lims in episodic meta-learning.
Aligns & combines multimodal feats (via copula trans. & multi-rel. attn.) to overcome fixed graph lims in episodic meta-learning.
Robust mol reps from integrating phys-chem&struct biases via novel pretrain objs & byte-BPE tok on large SMILES.
Robust mol reps from integrating phys-chem&struct biases via novel pretrain objs & byte-BPE tok on large SMILES.
A deep learning framework predicts atom coordinates from cryo-ET subtoms overcoming comp. limits of physics-based fitting.
A deep learning framework predicts atom coordinates from cryo-ET subtoms overcoming comp. limits of physics-based fitting.
...leverages quantitative data for robust annotation in complex tissues, identifying rare cell types via ML and FDR.
...leverages quantitative data for robust annotation in complex tissues, identifying rare cell types via ML and FDR.
are adapted to generate missing 2D tilt images, directly addressing distortions in 3D tomogram reconstructions.
are adapted to generate missing 2D tilt images, directly addressing distortions in 3D tomogram reconstructions.
integrates diverse data (tab, img, txt) via attention mech for computational BBB permeability prediction, trained on an extensive aggregated dataset.
integrates diverse data (tab, img, txt) via attention mech for computational BBB permeability prediction, trained on an extensive aggregated dataset.
...derived from discretizing protein space into an evolutionary vocabulary, capturing higher-order signals for bio discovery and programmable engineering.
...derived from discretizing protein space into an evolutionary vocabulary, capturing higher-order signals for bio discovery and programmable engineering.
Auto-extract microwell array design params from literature, build database for accelerated microfluidic dev.
Auto-extract microwell array design params from literature, build database for accelerated microfluidic dev.
... leverages scalograms & phasograms from CWT with DL & ensemble-fusion for interpretable, generalizable 5-superclass ECG classification.
... leverages scalograms & phasograms from CWT with DL & ensemble-fusion for interpretable, generalizable 5-superclass ECG classification.
Flawed metrics misrepresenting model performance, esp. in high-dimensional data, needs robust guidelines for reliable virt-cell model development.
Flawed metrics misrepresenting model performance, esp. in high-dimensional data, needs robust guidelines for reliable virt-cell model development.
...overcomes data scarcity and generalization challenges with self-supervised pretraining, KAN, CNN, and Transformer Encoder for robust prediction.
...overcomes data scarcity and generalization challenges with self-supervised pretraining, KAN, CNN, and Transformer Encoder for robust prediction.
combines Fast-DDPM w/ wavelets, reducing steps and using wavelet inputs for rapid missing MRI modality synthesis frm existing scans.
combines Fast-DDPM w/ wavelets, reducing steps and using wavelet inputs for rapid missing MRI modality synthesis frm existing scans.
...systematically targets and injects single neurons in dense organoid tissue, enabling high-throughput manipulation for brain development studies.
...systematically targets and injects single neurons in dense organoid tissue, enabling high-throughput manipulation for brain development studies.
models DD & DDI as coupled tensors, using diverse drug sim side info for incompleteness & sparsity.
models DD & DDI as coupled tensors, using diverse drug sim side info for incompleteness & sparsity.
finds spatial marker genes by pseudobulking gene detections & cells in clusters for LM input, accnting for spatial distr.
finds spatial marker genes by pseudobulking gene detections & cells in clusters for LM input, accnting for spatial distr.
...coupling toehold switches & retron RT to transduce transient RNA to stable DNA records for quant. host suscept. profiling.
...coupling toehold switches & retron RT to transduce transient RNA to stable DNA records for quant. host suscept. profiling.
Using exp coll cross-section data guiding docking of predicted subunits, refining protein complex assembly.
Using exp coll cross-section data guiding docking of predicted subunits, refining protein complex assembly.
DL segments MD binding sites into frag-spec regions. Monitors apo ligand binding for docking & design.
DL segments MD binding sites into frag-spec regions. Monitors apo ligand binding for docking & design.
Pre-trained protein embeddings require task-specific fine-tuning to capture localized mutations in bioengineering datasets.
Pre-trained protein embeddings require task-specific fine-tuning to capture localized mutations in bioengineering datasets.