Good Papers

Showing Genomics & single-cell Show all papers

78%Highly rated
?Highly ratedVote to see the score

Agta hunter-gatherer oral microbiomes are shaped by contact network structure

Agta hunter-gatherer oral microbiomes resemble Central African foragers more than neighbors, with contact networks predicting bacterial transmission and central individuals as supersharers.

Federico Musciotto, Begoña Dobón, Michael John Greenacre, Álex Mira and 12 more

Published Dec 31, 2030 · 0 citations

100% Readers1 of 1 upvoted
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 5/10
strict 1/5
67%Highly rated
?Highly ratedVote to see the score

scMAF: Single-Cell Multi-Omics Clustering via Adaptive Modality Fusion

Jun Fu, Yiding Lu, Ruohong Yang, Xi Peng and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

Causally Structured Differential Network Modeling for Single-Cell Perturbation Prediction

Jiayi Dong, Xinyue Gu, Fei Wang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
65%Worth a look
?Worth a lookVote to see the score

Layout Before Pixels: Topology-Anchored Transcriptome-to-Histology Generation

Jianwei Zhao, Xin Li, Fan Yang, Qiang Zhai and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

100% Readers1 of 1 upvoted
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

When Transcriptomic Foundation Models Scale: Domain-Focused Pretraining for Drug Development in Immunology and Inflammation

Karim El Kanbi, Yannis Cattan, Aziz Fouché, Charlotte Claye and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

WaveSem: Frequency-Adaptive Tokenization for Disentangling Semantics and Noise in Genomics

Shou Z Chen, Bing He, Zhenchao Tang, Jun Zhu and 8 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes

Ethan Baron, Alan Amin, Andrew Wilson

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Learning Biological Hierarchies in Single-Cell Foundation Models

Xiangyu Guo, Ricardo Henao

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

GRNAgent: A Multimodal Graph Reasoning Agent for Gene Regulatory Network Inference

Akshata Hegde, Kyler Zook, Yanli Wang, Jianlin Cheng

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Identifiable Feedback-Controlled Latent Flow for Unpaired Single-cell Spatio-Temporal Dynamics

Jianle Sun, Kun Zhang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

PerturbReason: A Knowledge-Grounded Benchmark and Framework for Cell-State–Conditioned Mechanistic Reasoning of Perturbation Effects

Dongkwan Kim, Yiming Gao, Yining Yang, Yang Shen

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Spectral Adaptive Repositioning for Flow-Based Single-Cell Perturbation Modeling

Shourya Verma, Mengbo Wang, Simran Kadadi, Shahin Mohammadi and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Benchmarks Design under Data Scarcity: From Coarse Labels to Diagnostic Evaluation of Biosynthetic Gene Cluster Models

Hanlin Xiao, Eriko Takano, Mauricio A Álvarez, Rainer Breitling

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

LeCellModel: Interpretable Density Estimation over the Gene Expression Manifold

Gil Karin, Artemy Bakulin, Nir Yosef

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Adapting Vision Transformers to Organoid Imaging

Yu Takagi

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

ImmuVis: Hyperconvolutional Foundation Models for Imaging Mass Cytometry

Dawid Uchal, Marcin Możejko, Krzysztof Gogolewski, Piotr Kupidura and 13 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

scTrilemma: Balancing Identity, Invariance, and Reconstruction in Single-Cell Representation Learning

Yunhak Oh, Yoonho Lee, Junseok Lee, Namkyeong Lee and 8 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Forecasting Microbial Dynamics: Evaluation Protocol and Prior-Spectrum Benchmark

Fedor Sergeev, Anna Győrffy-Kerekes, Tristan Gollmart, Vincent Fortuin and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Dynamic Regulatory Graph Learning for Histology-to-Spatial Transcriptomics

Yikai Luo, Peng Zhang, Heyang Zhao, Hongming Shan and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

UGM: Unified Multi-scale Genomic Event Modeling with Site-level Joint Prediction

Jiayang Wu, Chenchen Qin, Xu YANG, Yu Zhao and 7 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

TraceSim: A Generative Simulator and Benchmark for Joint scRNA-seq and Lineage Tracing

Mehrshad Sadria, Katsuki Fujisawa, Xun Shen

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

sMMC-22M: A Context-Aware Dataset and Benchmark for Single-Cell Spatial Transcriptomics

Xi Li, Yaqi Hu, Ziheng Duan, Xinyi Wang and 4 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

TargetSage: Identifying Therapeutic Target Genes with Interpretable and Robust LLM Reasoning

Ziheng Duan, Tong Wu, Xi Li, Simon D Sun and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Toward in Silico Strain Evaluation: A Multimodal Surrogate for Fermentation Dynamics with Metabolic Graph Pretraining

Yunxiao Li, Difeng Gao, Yubin Zheng, JIJIAO ZENG

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Designing Cell-Type-Specific Regulatory DNA with Guided Discrete Diffusion

Animesh Awasthi, Martin Stoll, Raphael Bednarsky, Moritz Schaefer and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Nüwa.RNA: An RNA Foundation Model for Unified Representation with Deep Structure Infusion

Kun Huang, Jiyang Li, Xin Guo, LIMEI HAN and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

PRISM: Phenotype-Resolved Inference in Single-Cell Mixed Models via Latent Disease States and Contextualized Differential Expression

Andrea Rubbi, Lama Salem, Caleb Ellington, Pietro Lió and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

What DNA Foundation Models Learn Beyond Sequence Composition

Vincenzo Y. Civale, Andrew Bagdanov, Alberto Magi

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

MUSS: A Multi-scale and Sequence-based Model for Single-cell Gene Regulation

Kangjie Zheng, Amirhossein Vahidi, Liying Jin, Joseph Clarke and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

UncertainGen: Scalable Uncertainty-Aware Representation Learning of DNA Sequences

Abdulkadir Celikkanat, Andres Masegosa, Mads Albertsen, Thomas Nielsen

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Cross-Cell-Line Perturbation Prediction Needs Controls

Xingyu Fan, Jinghao Wang, kim hsieh, Chunbin Gu and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

ATLAS: Adaptive Temporal Learning for Single-Cell Multi-Omics Alignment and Dynamics

Ye Zhang, Zijie Fang, Zhixiang Lin

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

Pathway-Aligned Regulator Tokens for Interpretable Spatial Gene Expression Prediction from Histologyatial Transcriptomics Prediction from Histology

Hyun Namgung, Sanghyun Park

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score

Multi-Scale Representation Learning for Single-Cell Multi-Omics

Zhijie Zheng, Meng Lan, Fei Gu

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
83%Must read
?Must readVote to see the score

Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction

IDER formulates image-based differential expression ranking to evaluate whether predicted spatial gene expression preserves contrast-specific DEG rankings, improving agreement and pathway overlap over reconstruction objectives.

Kaito Shiku, Kazuya Nishimura, Yasuhiro Kojima, Ryoma Bise

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
86%Must read
?Must readVote to see the score

Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images

CELLO predicts single-cell spatial transcriptomics from histology via grid sampling and distance-decay cross-attention, achieving 14x faster inference than DeepSpot2Cell without upstream segmentation.

Zijun Gao, Chunbin Gu, Xiangde Luo, Jinxi Xiang and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
91%Must read
?Must readVote to see the score

Plausibility Is Not Prediction: Contrastive Evidence for LLM-Based Cellular Perturbation Reasoning

LLM-based cellular perturbation reasoning relies on intrinsic gene tendencies rather than true perturbation effects, and contrastive evidence organization improves prediction accuracy substantially.

XINYU YUAN, Xixian Liu, Jianan Zhao, Ya Shi Zhang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
17/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5
83%Must read
?Must readVote to see the score

Simulation-free Unbalanced Dynamic Optimal Transport with General Growth Penalty

SUDO enables simulation-free unbalanced dynamic optimal transport for general convex growth penalties, matching WFR accuracy with faster speed while supporting asymmetric biological priors.

Junda Ying, Yuxuan Wang, Bowen Yang, Peijie Zhou and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 3/5
medium 9/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score

Flexible Flows for Biological Sequence Design

Flexible Flows for Biological Sequence Design proposes structured couplings and latent edit-based rate parameterization to achieve state-of-the-art results across diverse biological sequence generation tasks.

Yogesh Verma, Dani Korpela, Harri Lähdesmäki, Vikas Garg

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 1/5
89%Must read
?Must readVote to see the score

How Post-Training Shapes Biological Reasoning Models

Continued pre-training aligns biological language, supervised fine-tuning improves in-domain but harms out-of-domain reasoning, and reinforcement learning recovers generalization when rewards align.

Lukas Fesser, Hanlin Zhang, Michelle M Li, Eric Wang and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 3 on Hugging Face

– ReadersNo votes yet
16/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 4/5
91%Must read
?Must readVote to see the score

STRAND: Sequence-Conditioned Transport for Single-Cell Perturbations

STRAND predicts single-cell transcriptional responses to perturbations by conditioning on regulatory DNA sequence, enabling zero-shot inference across ~95% of the genome with improved discrimination and transfer performance.

Boyang Fu, Sameer Gabbita, George Dasoulas, xiang lin and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
17/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5
74%Highly rated
?Highly ratedVote to see the score

Likelihood-free inference of phylogenetic tree posterior distributions

A likelihood-free neural network estimates phylogenetic tree posteriors via sequence pair encodings and subtree merges, outperforming likelihood-based methods especially for intractable evolutionary models.

Luc Blassel, Noémie Sauvage, Pierre Barrat-Charlaix, Bastien Boussau and 2 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 4/10
strict 2/5
86%Must read
?Must readVote to see the score

On the Recoverability of Causal Relations from Bulk Gene Expression Data

Causal gene relations are recoverable from bulk expression only under linear aggregation and affine equations, which real data rarely satisfy.

Gongxu Luo, Boyang Sun, Kun Zhang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 3/5
91%Must read
?Must readVote to see the score

mRNABench: A curated benchmark for mature mRNA property and function prediction

mRNABench benchmarks mature mRNA property predictions across 59 tasks and 135K experiments, revealing synergies between self-supervised objectives that yield a compact state-of-the-art Mamba model using 700x fewer parameters.

Ruian (Ian) Shi, Taykhoom Dalal, Philip Fradkin, Divya Koyyalagunta and 9 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
18/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 18 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 4/5
86%Must read
?Must readVote to see the score

Querying Counterfactuals on Tissue Graphs with Supervised Disentanglement

Cellina defines tissue graph counterfactuals as spatial edge or node interventions and uses supervised disentanglement to separate intrinsic cell states from context, outperforming competitors across millions of cells and revealing cancer subdomains.

Abdul Moeed, Stefan Schrod, Martin Rohbeck, Marc J Bonder and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
91%Must read
?Must readVote to see the score

GeneZip: Region-Aware Compression for Long Context DNA Modeling

GeneZip uses region-aware compression to achieve high base-pairs-per-token ratios, improves DNA modeling benchmarks, and enables 128K-context training on limited hardware.

Jianan Zhao, Xixian Liu, Zhihao Zhan, XINYU YUAN and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
17/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 2/5
86%Must read
?Must readVote to see the score

CellMSA: Context Modeling for Single-Cell Representation Learning

CellMSA improves single-cell representation learning by modeling cross-batch and cross-cell-type context via MSA-inspired gene-pair representations, outperforming existing methods across benchmarks.

Suyuan Zhao, Minghao Liu, Yizhen Luo, Zaiqing Nie

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
88%Must read
?Must readVote to see the score

C3P: Contrastive promoter-protein pretraining yields representations capturing bacterial gene regulation

C3P uses contrastive promoter-protein pretraining to learn bacterial promoter representations that outperform genome language models on regulatory inference and zero-shot co-regulated gene retrieval.

Cameron Dufault, Scott Xu, Alan Moses

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

100% Readers1 of 1 upvoted
14/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
83%Must read
?Must readVote to see the score

PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference

PACE infers continuous single-cell dynamics via geometry-aware Riemannian transport, reducing reconstruction distances by 23.7% without paired cells or velocity supervision.

Chenglei Yu, Chuanrui Wang, Bangyan Liao, Tailin Wu

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
13/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 13 of 20 reviewers recommend it
lenient 3/5
medium 8/10
strict 2/5
71%Highly rated
?Highly ratedVote to see the score

Multiscale Supervised Unbalanced Optimal Transport Flow Matching

MUST-FM scales unbalanced optimal transport via hierarchical structure and optional transition priors for efficient atlas-scale single-cell trajectory inference.

Qiangwei Peng, Lezhi Chen, Peijie Zhou

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
7/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 7 of 20 reviewers recommend it
lenient 4/5
medium 3/10
strict 0/5