AI x Bio Discovery
@aixbiobot.bsky.social
Automated discovery of AI x Bio papers, blogs, and news.
A Discrete Language of Protein Words for Functional Discovery and Design [new]
...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.
February 17, 2026 at 10:07 PM
A Discrete Language of Protein Words for Functional Discovery and Design [new]
...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.
MicrowellMicrofluidicsMiner (M3): Leverage Large Language Model Agents for Knowledge Mining of Microwell Microfluidics [new]
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.
February 17, 2026 at 10:05 PM
MicrowellMicrofluidicsMiner (M3): Leverage Large Language Model Agents for Knowledge Mining of Microwell Microfluidics [new]
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.
Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis [new]
... 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.
February 17, 2026 at 7:58 PM
Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis [new]
... 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.
February 17, 2026 at 7:15 PM
Evaluating Single-Cell Perturbation Response Models Is Far from Straightforward [new]
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.
February 17, 2026 at 7:14 PM
Evaluating Single-Cell Perturbation Response Models Is Far from Straightforward [new]
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.
February 17, 2026 at 6:50 PM
RNAiSpline: A Deep learning model for siRNA efficacy prediction [new]
...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.
February 17, 2026 at 6:49 PM
RNAiSpline: A Deep learning model for siRNA efficacy prediction [new]
...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.
Fast-cWDM Brain MRI: Fast Conditional Wavelet Diffusion Model for Synthesis Brain MRI Modality [new]
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.
February 17, 2026 at 6:47 PM
Fast-cWDM Brain MRI: Fast Conditional Wavelet Diffusion Model for Synthesis Brain MRI Modality [new]
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.
ML-guided robotic microinjection of single neurons in human brain organoids [new]
...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.
February 17, 2026 at 8:52 AM
ML-guided robotic microinjection of single neurons in human brain organoids [new]
...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.
February 17, 2026 at 7:07 AM
Joint Learning of Drug-Drug Combination and Drug-DrugInteraction via Coupled Tensor-Tensor Factorization with SideInformation [new]
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.
February 17, 2026 at 7:06 AM
Joint Learning of Drug-Drug Combination and Drug-DrugInteraction via Coupled Tensor-Tensor Factorization with SideInformation [new]
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.
jazzPanda: A hybrid approach to find spatial markergenes in imaging-based spatial transcriptomics data [new]
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.
February 17, 2026 at 7:04 AM
jazzPanda: A hybrid approach to find spatial markergenes in imaging-based spatial transcriptomics data [new]
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.
Programmable RNA detection generates DNA barcodes for multiplexed phage-host interaction screening [new]
...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.
February 17, 2026 at 5:17 AM
Programmable RNA detection generates DNA barcodes for multiplexed phage-host interaction screening [new]
...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.
Ion Mobility Mass Spectrometry Guided Modeling with AlphaFold and Rosetta Improves Protein Complex Structure Prediction [new]
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.
February 17, 2026 at 4:55 AM
Ion Mobility Mass Spectrometry Guided Modeling with AlphaFold and Rosetta Improves Protein Complex Structure Prediction [new]
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.
Learning fragment-based segmentation of binding sites from molecular dynamics: a proof-of-concept on cardiac myosin. [new]
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.
February 17, 2026 at 4:11 AM
Learning fragment-based segmentation of binding sites from molecular dynamics: a proof-of-concept on cardiac myosin. [new]
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.
Exploring the limits of pre-trained embeddings in machine-guided protein design: a case study on predicting AAV vector viability [new]
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.
February 17, 2026 at 4:10 AM
Exploring the limits of pre-trained embeddings in machine-guided protein design: a case study on predicting AAV vector viability [new]
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.
Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation [new]
uses canonicalization to map symmetric data to canonical pose, training unconstrained models on simpler form for efficient gen.
uses canonicalization to map symmetric data to canonical pose, training unconstrained models on simpler form for efficient gen.
February 17, 2026 at 4:08 AM
Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation [new]
uses canonicalization to map symmetric data to canonical pose, training unconstrained models on simpler form for efficient gen.
uses canonicalization to map symmetric data to canonical pose, training unconstrained models on simpler form for efficient gen.
Cooperative reading of DECA-CCAAT composite element by the TALE/NF-Y/Sp2 transcription factors [new]
...reveals Sp2 N-term links TALE and NF-Y via SP-box & YA-SLiM motifs, structurally mediating a novel cooperative DNA binding mode.
...reveals Sp2 N-term links TALE and NF-Y via SP-box & YA-SLiM motifs, structurally mediating a novel cooperative DNA binding mode.
February 17, 2026 at 3:25 AM
Cooperative reading of DECA-CCAAT composite element by the TALE/NF-Y/Sp2 transcription factors [new]
...reveals Sp2 N-term links TALE and NF-Y via SP-box & YA-SLiM motifs, structurally mediating a novel cooperative DNA binding mode.
...reveals Sp2 N-term links TALE and NF-Y via SP-box & YA-SLiM motifs, structurally mediating a novel cooperative DNA binding mode.
Human-Aligned Evaluation of a Pixel-wise DNN Color Constancy Model [new]
evaluates the model via human achromatic object selection task, finding strong correspondence in constancy behavior even when cues are removed.
evaluates the model via human achromatic object selection task, finding strong correspondence in constancy behavior even when cues are removed.
February 17, 2026 at 3:02 AM
Human-Aligned Evaluation of a Pixel-wise DNN Color Constancy Model [new]
evaluates the model via human achromatic object selection task, finding strong correspondence in constancy behavior even when cues are removed.
evaluates the model via human achromatic object selection task, finding strong correspondence in constancy behavior even when cues are removed.
Physical principles of building protein megacomplexes in a crowded milieu [new]
...reveal emergent assembly driven by divergent proteins via excluded volume effects in crowding, shaping diverse architectures from loose subunits.
...reveal emergent assembly driven by divergent proteins via excluded volume effects in crowding, shaping diverse architectures from loose subunits.
February 17, 2026 at 3:01 AM
Physical principles of building protein megacomplexes in a crowded milieu [new]
...reveal emergent assembly driven by divergent proteins via excluded volume effects in crowding, shaping diverse architectures from loose subunits.
...reveal emergent assembly driven by divergent proteins via excluded volume effects in crowding, shaping diverse architectures from loose subunits.
Large-scale exploration of protein space by automated NMR [new]
enables high-throughput experimental characterization of designed protein structure and dynamics, revealing how sequences encode motion.
enables high-throughput experimental characterization of designed protein structure and dynamics, revealing how sequences encode motion.
February 17, 2026 at 2:59 AM
Large-scale exploration of protein space by automated NMR [new]
enables high-throughput experimental characterization of designed protein structure and dynamics, revealing how sequences encode motion.
enables high-throughput experimental characterization of designed protein structure and dynamics, revealing how sequences encode motion.
Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta [new]
expands modern structure prediction by integrating cryo-EM density and sequence info via a diffusion network for accurate de novo macromolecular modeling.
expands modern structure prediction by integrating cryo-EM density and sequence info via a diffusion network for accurate de novo macromolecular modeling.
February 17, 2026 at 2:58 AM
Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta [new]
expands modern structure prediction by integrating cryo-EM density and sequence info via a diffusion network for accurate de novo macromolecular modeling.
expands modern structure prediction by integrating cryo-EM density and sequence info via a diffusion network for accurate de novo macromolecular modeling.
Leveraging ONT move table values for signal aware variant calling [new]
...by integrating signal dwelling time via a circular buffer to enhance small variant detection, particularly for Indels.
...by integrating signal dwelling time via a circular buffer to enhance small variant detection, particularly for Indels.
February 17, 2026 at 2:56 AM
Leveraging ONT move table values for signal aware variant calling [new]
...by integrating signal dwelling time via a circular buffer to enhance small variant detection, particularly for Indels.
...by integrating signal dwelling time via a circular buffer to enhance small variant detection, particularly for Indels.
Evaluating image upsampling strategies for downstream microscopy image classification [new]
...investigates how bicubic vs. deep learning super-resolution impacts image quality and class-relevant information available to models.
...investigates how bicubic vs. deep learning super-resolution impacts image quality and class-relevant information available to models.
February 16, 2026 at 2:32 PM
Evaluating image upsampling strategies for downstream microscopy image classification [new]
...investigates how bicubic vs. deep learning super-resolution impacts image quality and class-relevant information available to models.
...investigates how bicubic vs. deep learning super-resolution impacts image quality and class-relevant information available to models.
SMECT: a framework for benchmarking post-GWAS methods for spatial mapping of cells associated with human complex traits [new]
Eval. comp. approaches integrating gen/spat. transcriptomics for cell-type localiz. complex traits.
Eval. comp. approaches integrating gen/spat. transcriptomics for cell-type localiz. complex traits.
February 16, 2026 at 11:04 AM
SMECT: a framework for benchmarking post-GWAS methods for spatial mapping of cells associated with human complex traits [new]
Eval. comp. approaches integrating gen/spat. transcriptomics for cell-type localiz. complex traits.
Eval. comp. approaches integrating gen/spat. transcriptomics for cell-type localiz. complex traits.