AI x Bio Discovery
@aixbiobot.bsky.social
Automated discovery of AI x Bio preprint papers.
Heuristics for lab robotics, and where its future may go [new]
...explores strategies (software, hardware, AI) to lower automation barriers, fostering centralized cloud labs for more impactful R&D.
...explores strategies (software, hardware, AI) to lower automation barriers, fostering centralized cloud labs for more impactful R&D.
February 15, 2026 at 4:13 PM
Heuristics for lab robotics, and where its future may go [new]
...explores strategies (software, hardware, AI) to lower automation barriers, fostering centralized cloud labs for more impactful R&D.
...explores strategies (software, hardware, AI) to lower automation barriers, fostering centralized cloud labs for more impactful R&D.
February 15, 2026 at 4:12 PM
Modeling mitochondrial inheritance enables high-precision single-cell lineage tracing in humans [new]
Integrating drift & sparse measurements, prob. framework refines clonal trees linking lineage hist. & cell state in health/disease.
Integrating drift & sparse measurements, prob. framework refines clonal trees linking lineage hist. & cell state in health/disease.
February 15, 2026 at 4:04 PM
Modeling mitochondrial inheritance enables high-precision single-cell lineage tracing in humans [new]
Integrating drift & sparse measurements, prob. framework refines clonal trees linking lineage hist. & cell state in health/disease.
Integrating drift & sparse measurements, prob. framework refines clonal trees linking lineage hist. & cell state in health/disease.
A scalable approach to resolving variants of uncertain significance [new]
...leveraging comprehensive experimental & predictive data across 40 genes to reclassify existing VUS and preclassify future variants.
...leveraging comprehensive experimental & predictive data across 40 genes to reclassify existing VUS and preclassify future variants.
February 15, 2026 at 11:03 AM
A scalable approach to resolving variants of uncertain significance [new]
...leveraging comprehensive experimental & predictive data across 40 genes to reclassify existing VUS and preclassify future variants.
...leveraging comprehensive experimental & predictive data across 40 genes to reclassify existing VUS and preclassify future variants.
dsRBD Redesign: A Targeted Strategy for Inhibition of RNA Helicase DHX9 [new]
uses computationally designed protein binders to block DHX9's autoregulatory dsRBD2-core interface preventing interaction and inhibiting helicase activity.
uses computationally designed protein binders to block DHX9's autoregulatory dsRBD2-core interface preventing interaction and inhibiting helicase activity.
February 15, 2026 at 11:01 AM
dsRBD Redesign: A Targeted Strategy for Inhibition of RNA Helicase DHX9 [new]
uses computationally designed protein binders to block DHX9's autoregulatory dsRBD2-core interface preventing interaction and inhibiting helicase activity.
uses computationally designed protein binders to block DHX9's autoregulatory dsRBD2-core interface preventing interaction and inhibiting helicase activity.
The generation and validation of a de novo-designed titin binder for use in fluorescence microscopy [new]
Binder labels M10 domain in M-band, enabling Ab-free vis. validating in silico prot. design for complex bio targets.
Binder labels M10 domain in M-band, enabling Ab-free vis. validating in silico prot. design for complex bio targets.
February 15, 2026 at 3:09 AM
The generation and validation of a de novo-designed titin binder for use in fluorescence microscopy [new]
Binder labels M10 domain in M-band, enabling Ab-free vis. validating in silico prot. design for complex bio targets.
Binder labels M10 domain in M-band, enabling Ab-free vis. validating in silico prot. design for complex bio targets.
Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologies [new]
Compares HTS validating comp. des. miniprot. binder libs, addressing exp. bottleneck to scale therapy disc.
Compares HTS validating comp. des. miniprot. binder libs, addressing exp. bottleneck to scale therapy disc.
February 15, 2026 at 1:58 AM
Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologies [new]
Compares HTS validating comp. des. miniprot. binder libs, addressing exp. bottleneck to scale therapy disc.
Compares HTS validating comp. des. miniprot. binder libs, addressing exp. bottleneck to scale therapy disc.
Genome-wide single-cell perturbation screens with VIPerturb-seq [new]
...are now routine through probe-based detection and phenotypic enrichment, using combinatorial indexing for expanded throughput.
...are now routine through probe-based detection and phenotypic enrichment, using combinatorial indexing for expanded throughput.
February 14, 2026 at 11:56 AM
Genome-wide single-cell perturbation screens with VIPerturb-seq [new]
...are now routine through probe-based detection and phenotypic enrichment, using combinatorial indexing for expanded throughput.
...are now routine through probe-based detection and phenotypic enrichment, using combinatorial indexing for expanded throughput.
Unifying Non-Equilibrium Information Thermodynamics and Genome Engine Dynamics: Maxwell's Demon Control of Cancer Cell Fates [new]
Maxwell's Demon crit. pt., orders cancer genome dynamics for global coherence & irreversible fate.
Maxwell's Demon crit. pt., orders cancer genome dynamics for global coherence & irreversible fate.
February 14, 2026 at 11:54 AM
Unifying Non-Equilibrium Information Thermodynamics and Genome Engine Dynamics: Maxwell's Demon Control of Cancer Cell Fates [new]
Maxwell's Demon crit. pt., orders cancer genome dynamics for global coherence & irreversible fate.
Maxwell's Demon crit. pt., orders cancer genome dynamics for global coherence & irreversible fate.
CodonRL: Multi-Objective Codon Sequence Optimization Using Demonstration-Guided Reinforcement Learning [new]
...learns struct. priors from folding feedback & expert sequences, enabling user-ctrl tradeoffs for enhanced mRNA design.
...learns struct. priors from folding feedback & expert sequences, enabling user-ctrl tradeoffs for enhanced mRNA design.
February 14, 2026 at 11:30 AM
CodonRL: Multi-Objective Codon Sequence Optimization Using Demonstration-Guided Reinforcement Learning [new]
...learns struct. priors from folding feedback & expert sequences, enabling user-ctrl tradeoffs for enhanced mRNA design.
...learns struct. priors from folding feedback & expert sequences, enabling user-ctrl tradeoffs for enhanced mRNA design.
Discovery of TDP-43 aggregation inhibitors via a hybrid machine learning framework [new]
integrating GNN, descriptors, & annotations to identify berberrubine & PE859, inhibiting aggregation in cells and C. elegans.
integrating GNN, descriptors, & annotations to identify berberrubine & PE859, inhibiting aggregation in cells and C. elegans.
February 14, 2026 at 11:08 AM
Discovery of TDP-43 aggregation inhibitors via a hybrid machine learning framework [new]
integrating GNN, descriptors, & annotations to identify berberrubine & PE859, inhibiting aggregation in cells and C. elegans.
integrating GNN, descriptors, & annotations to identify berberrubine & PE859, inhibiting aggregation in cells and C. elegans.
Feature-based in-silico model to predict the Mycobacterium tuberculosis bedaquiline phenotype associated with Rv0678 variants [new]
Uses 5 feats (evo conserv, funct site prox) to interpret Rv0678 var impact & guide clin mgmt.
Uses 5 feats (evo conserv, funct site prox) to interpret Rv0678 var impact & guide clin mgmt.
February 14, 2026 at 11:06 AM
Feature-based in-silico model to predict the Mycobacterium tuberculosis bedaquiline phenotype associated with Rv0678 variants [new]
Uses 5 feats (evo conserv, funct site prox) to interpret Rv0678 var impact & guide clin mgmt.
Uses 5 feats (evo conserv, funct site prox) to interpret Rv0678 var impact & guide clin mgmt.
February 14, 2026 at 11:04 AM
Democratised single cell proteomics uncovers tumor associated macrophage signature in CYLD cutaneous syndrome skin tumors [new]
Accessible, cost-effective, label-free tech found novel TME remodeling macrophage pop in CCS skin tumors.
Accessible, cost-effective, label-free tech found novel TME remodeling macrophage pop in CCS skin tumors.
February 14, 2026 at 11:03 AM
Democratised single cell proteomics uncovers tumor associated macrophage signature in CYLD cutaneous syndrome skin tumors [new]
Accessible, cost-effective, label-free tech found novel TME remodeling macrophage pop in CCS skin tumors.
Accessible, cost-effective, label-free tech found novel TME remodeling macrophage pop in CCS skin tumors.
Evolution of oncogene amplification across 86,000 cancer cell genomes [new]
...shows distinct evo paths for ICamp & ecDNA amplifications: ICamp has subclonal spec.; ecDNA has variable, rearrangement-driven, tissue-spec. evolution.
...shows distinct evo paths for ICamp & ecDNA amplifications: ICamp has subclonal spec.; ecDNA has variable, rearrangement-driven, tissue-spec. evolution.
February 14, 2026 at 10:40 AM
Evolution of oncogene amplification across 86,000 cancer cell genomes [new]
...shows distinct evo paths for ICamp & ecDNA amplifications: ICamp has subclonal spec.; ecDNA has variable, rearrangement-driven, tissue-spec. evolution.
...shows distinct evo paths for ICamp & ecDNA amplifications: ICamp has subclonal spec.; ecDNA has variable, rearrangement-driven, tissue-spec. evolution.
Cell phenotypes in the biomedical literature: a systematic analysis and text mining corpus [new]
Annotated corpus of literature cell phenotypes links them to Cell Ontology, revealing naming patterns and enabling ontology expansion.
Annotated corpus of literature cell phenotypes links them to Cell Ontology, revealing naming patterns and enabling ontology expansion.
February 14, 2026 at 9:14 AM
Cell phenotypes in the biomedical literature: a systematic analysis and text mining corpus [new]
Annotated corpus of literature cell phenotypes links them to Cell Ontology, revealing naming patterns and enabling ontology expansion.
Annotated corpus of literature cell phenotypes links them to Cell Ontology, revealing naming patterns and enabling ontology expansion.
ChatDIA: A zero-shot large language model workflow for targeted analysis of data-independent acquisition mass spectrometry data [new]
automates targeted DIA peptide ID & interactive data expl. via zero-shot LLM reason chromatograms.
automates targeted DIA peptide ID & interactive data expl. via zero-shot LLM reason chromatograms.
February 14, 2026 at 9:01 AM
ChatDIA: A zero-shot large language model workflow for targeted analysis of data-independent acquisition mass spectrometry data [new]
automates targeted DIA peptide ID & interactive data expl. via zero-shot LLM reason chromatograms.
automates targeted DIA peptide ID & interactive data expl. via zero-shot LLM reason chromatograms.
A single-cell atlas and aging clock define biological age and risk-associated stem cell states in human hematopoiesis [new]
HSPC atlas to define age programs. An ML aging clock predicts age; AML dev. links to gen. risk & survival.
HSPC atlas to define age programs. An ML aging clock predicts age; AML dev. links to gen. risk & survival.
February 14, 2026 at 8:59 AM
A single-cell atlas and aging clock define biological age and risk-associated stem cell states in human hematopoiesis [new]
HSPC atlas to define age programs. An ML aging clock predicts age; AML dev. links to gen. risk & survival.
HSPC atlas to define age programs. An ML aging clock predicts age; AML dev. links to gen. risk & survival.
TOXsiRNA: A web server to predict the toxicity of chemically modified siRNAs [new]
by computationally predicting their toxicity and off-targets using machine learning models trained on various siRNA sequence features.
by computationally predicting their toxicity and off-targets using machine learning models trained on various siRNA sequence features.
February 14, 2026 at 8:57 AM
TOXsiRNA: A web server to predict the toxicity of chemically modified siRNAs [new]
by computationally predicting their toxicity and off-targets using machine learning models trained on various siRNA sequence features.
by computationally predicting their toxicity and off-targets using machine learning models trained on various siRNA sequence features.
evoCancerGPT: Generating Zero-Shot Single-Cell and Single-Sample Cancer Progression Through Transfer Learning [new]
...by forecasting gene exp profiles from pseudotime-ordered sc states to charact. tumor prog. in indiv. pts.
...by forecasting gene exp profiles from pseudotime-ordered sc states to charact. tumor prog. in indiv. pts.
February 14, 2026 at 8:56 AM
evoCancerGPT: Generating Zero-Shot Single-Cell and Single-Sample Cancer Progression Through Transfer Learning [new]
...by forecasting gene exp profiles from pseudotime-ordered sc states to charact. tumor prog. in indiv. pts.
...by forecasting gene exp profiles from pseudotime-ordered sc states to charact. tumor prog. in indiv. pts.
MassID provides near complete annotation of metabolomics data with identification probabilities [new]
cloudbased untargeted end-to-end pipeline using deep learning & DecoID2 for FDR-controlled probabilistic metabolite ID.
cloudbased untargeted end-to-end pipeline using deep learning & DecoID2 for FDR-controlled probabilistic metabolite ID.
February 14, 2026 at 8:53 AM
MassID provides near complete annotation of metabolomics data with identification probabilities [new]
cloudbased untargeted end-to-end pipeline using deep learning & DecoID2 for FDR-controlled probabilistic metabolite ID.
cloudbased untargeted end-to-end pipeline using deep learning & DecoID2 for FDR-controlled probabilistic metabolite ID.
Machine learning-guided design of artificial microRNAs for targeted gene silencing [new]
developing a web platform using NNs and large-scale data to optimize amiRNA sequence-structure-processing for precise, specific gene silencing.
developing a web platform using NNs and large-scale data to optimize amiRNA sequence-structure-processing for precise, specific gene silencing.
February 14, 2026 at 8:51 AM
Machine learning-guided design of artificial microRNAs for targeted gene silencing [new]
developing a web platform using NNs and large-scale data to optimize amiRNA sequence-structure-processing for precise, specific gene silencing.
developing a web platform using NNs and large-scale data to optimize amiRNA sequence-structure-processing for precise, specific gene silencing.
Enzyme Classification via Semi-Supervised Functional ResidueLearning [new]
...by learning sparse functional residue activations via MSA-based data augmentation for robust EC prediction and interpretable annotations.
...by learning sparse functional residue activations via MSA-based data augmentation for robust EC prediction and interpretable annotations.
February 14, 2026 at 8:49 AM
Enzyme Classification via Semi-Supervised Functional ResidueLearning [new]
...by learning sparse functional residue activations via MSA-based data augmentation for robust EC prediction and interpretable annotations.
...by learning sparse functional residue activations via MSA-based data augmentation for robust EC prediction and interpretable annotations.
Parameter-free representations outperform single-cell foundation models on downstream benchmarks [new]
...via simple linear models on norm. scRNA-seq to capture cell ID across diverse/novel tasks, challenging complex deep learning.
...via simple linear models on norm. scRNA-seq to capture cell ID across diverse/novel tasks, challenging complex deep learning.
February 14, 2026 at 8:26 AM
Parameter-free representations outperform single-cell foundation models on downstream benchmarks [new]
...via simple linear models on norm. scRNA-seq to capture cell ID across diverse/novel tasks, challenging complex deep learning.
...via simple linear models on norm. scRNA-seq to capture cell ID across diverse/novel tasks, challenging complex deep learning.
Pragmatic analysis with knowledge-guided for unraveling peptide-protein pairwise non-covalent mechanisms [new]
...integrates contextual information and biological prior knowledge to build residue-level interaction maps.
...integrates contextual information and biological prior knowledge to build residue-level interaction maps.
February 14, 2026 at 8:13 AM
Pragmatic analysis with knowledge-guided for unraveling peptide-protein pairwise non-covalent mechanisms [new]
...integrates contextual information and biological prior knowledge to build residue-level interaction maps.
...integrates contextual information and biological prior knowledge to build residue-level interaction maps.