- by Silva, D. A., Eqbal, M., Broos, L., Wierucka, K.Integrating multi-sensor data from biologging tags is key to understanding animal behavior, particularly in group-living species, where communication, movement, and spatial dynamics are closely linked. However, analyzing such data at scale is often hindered by proprietary binary formats or manual decoding workflows in existing software. We present VesperFlow, an open-source Python pipeline that automates the decoding of inertial measurement unit (IMU), audio, and GPS data from Vesper Wildlife tags. VesperFlow batch-processes large datasets from multiple individuals, synchronizes timestamps across sensors […]
- by CEYHUN, A., Venturelli, L., Jacobs, J., Sifrim, A.Targeted spatial transcriptomics requires selecting a gene panel before any experiment is run. Choosing well across tens of thousands of candidate genes under platform-specific probe, panel-size, and sensitivity constraints is difficult to do manually, and impossible to correct once a panel has been used. A growing number of computational tools to automate this selection have been designed, yet it remains unclear whether they are adopted in practice. Several factors could limit uptake: validation uncertainty about panel performance, workflow friction between […]
- by Shternshis, A., Singh, P., Hugerth, L. W.Longitudinal studies with human participants frequently face the challenge of missing samples, which lead to incomplete trajectories of participant biomarkers and a reduction in data size. Existing approaches focus on single-variable imputation or model features one at a time, while neural networks typically require a large number of parameters and substantial training data. To address these challenges, we present an explainable model for multiple imputation of compositional samples based on a Gaussian random field (GRF). The model is specifically designed […]
- by Belleau, P., Li, X., Deschenes, A., Marrah, L., Krasnitz, A.Molecular properties of human diseases and conditions often exhibit dependence on the genetic ancestry of the donor. In order to make more human molecular data available for ancestry-informed research, we developed a set of software tools termed Robust Ancestry Inference using Data Synthesis (RAIDS) for inference of genetic ancestry from sequence data that pose challenges to genotyping. Here we describe a recent expansion and refinement of RAIDS, applicable to nucleic-acid sequence data resultant from a broad range of experimental strategies. […]
- by Wang, R. H., Benard, B. A., Ilerten, I., Zdravkovic, S., Al-Humadi, R., Nasr, S., Howitt, B., Gentles, A. J.Immunotherapy has transformed the management of many cancers, such as clear cell renal cell carcinoma (ccRCC), yet durable clinical benefit is achieved in only a subset of patients. Immunotherapy outcomes are governed by the multicellular tumor microenvironment (TME), through the structured and directional interplay of regulatory programs and ligand-receptor communications. Yet most existing methods for immunotherapy response prediction rely on independent signatures or cell types and fail to model the structured and directional signaling network within the TME. To address […]
- by Velland, M., Norwick, E., Ardene, S., Marwick, T., Corven, L., Solmere, A., Calder, N., Quillon, R., Renn, I., Elian, M.Human skin atlases resolve a diverse set of cellular states, yet connecting these states to their responses to intervention remains difficult across independently sampled tissues. Here we present VirtualSkin, a cell language model that aligns skin transcriptomes with biological descriptions and supports intervention conditioned response prediction. We evaluated the model across independent atlas, disease, anatomical and perturbation cohorts, with donors, studies and perturbations withheld according to the experimental design. VirtualSkin improved inflammatory skin annotation by 0.056 macro F1 points and […]
- by Yang, S., Pan, A., Shin, H., Chen, H., Zhang, Z., Shad, A., Huang, W., Liu, Y., Liu, W., Luo, H., Xu, C., Chen, J., Xu, M., Luo, W., Yu, H., Shen, L.Automated detection of mouse scratching behavior could reduce manual annotation and is essential for preclinical itch research. However, robust performance across laboratories remains a challenge for current methods. We present Scratch-AID+, a framework dedicated to automated mouse scratching detection, including a diverse and progressive set of approaches: classic ResNet-based detectors, task-adaptive fine-tuning of video foundation models, and in-context learning with advanced multimodal large language models. To simulate real-world use cases, we benchmark on a public dataset and utilize additional cross-laboratory […]
- by Dreyfuss, J. M., Dubey, D., Zhang, Y., Brown, M. R., Rotter, J. I., Rich, S. S., Liu, P. Y., Redline, S., Wang, H., Gerszten, R. E., Clish, C. B., Wyss, A. B., Morrison, A. C., Bressler, J., Sarnowski, C., Yu, B., Lutsey, P. L., Lucey, B. P., Moon, J.-Y., Pan, H., Djordjilovic, V., Sofer, T.The robust replication of scientific findings across independent studies is essential, yet it remains challenging in high-dimensional biological datasets. A critical aspect of true replication requires detecting not only the repeated presence but also the consistent direction of an effect. Traditional methods for evaluating replication often ignore effect directionality or lack adequate statistical power when adjusting for multiple comparisons. To address this, we extend the directional MaxP test (DMT) and our screening-integrated procedure, ScreenDMT, to evaluate directional replication across an […]
- by Liang, W.-L., Yang, Y.-B., Zhang, Q.-Y., Feng, J.-C., Wang, Q.-F., Zou, D., Tang, J.-L., Liu, Y., Wang, S.-Y., Duan, J., Bai, Y., Li, Y.-F., Sun, W.-Y., Cao, Y.-F., He, R.-R.Few-shot adaptation can help or harm single-cell perturbation prediction, but conventional evaluation shares a control estimate between calibration responses and held-out targets. We show how methods carry control error into their predictions and derive its contribution to score inflation. Nested control-depth experiments support inverse-depth scaling of inner-product inflation; correlation inflation also depends on the control noise-to-signal ratio. Independent-control scoring changed the rank of 40 of 52 configuration-dataset entries. We introduce SafeDelta, a split-control criterion that uses calibration data to decide […]
- by K C, R., Zhou, S., Cheng, R., Penaherrera, M. A., Lizarazo, S., Van Bortle, K.Protein-protein interactions (PPIs) are fundamental to the regulation and function of all cellular processes, yet our current understanding of the human interactome is limited by the specific PPI-related experiments performed to date. Moreover, whereas proteins with minimal research interest may have relatively few interaction-probing studies, other factors such as cancer related proteins are frequently represented in PPI studies, producing a highly uneven bias across current PPI data. Here, we apply effective conductance – a concept from circuit theory – to […]
- by Maire, K., Zheng, W.Nearest-neighbour retrieval in T cell receptor distance spaces is uneven: some receptors enter many neighbour lists while others enter none. We quantified this hubness in paired variable-domain distances and evaluated local scaling as a post-processing correction. Across ITRAP-filtered dextramers, VDJdb and McPAS-TCR, the skewness of the ten-neighbour occurrence count was 1.26 to 1.50. Local scaling reduced it to 0.13 to 0.31. Under a diagnostic restriction requiring different V families on both chains, macro retrieval gain increased by 0.1418 on VDJdb […]
- by Pozzobon, D., Khusial, N., Spreafico, R., Csala, A.Background: The selection of efficacious and safe antibody-based oncology targets depends on tumor specificity and normal-tissue expression, and remains challenging. Bulk RNA-seq can identify tumor-enriched surface genes, but may obscure tumor specificity and normal-cell expression patterns that are relevant to the therapeutic window. We evaluated whether single-cell RNA-seq-derived expression features improve retrospective prioritization of clinically pursued antibody targets. Methods: We developed a bulk and single-cell RNA expression-based ranking framework across six solid tumor indications. 4,532 candidate surfaceome targets were scored […]
- by Adil, S., de Kok, T. M., Willighagen, E., Abbassi-Daloii, T., Martens, M.Chemical safety assessment is moving towards new approach methodologies (NAMs) to improve human safety and reduce animal testing. The Adverse Outcome Pathway (AOP) is a NAM framework describing toxicity as a chain of Key Events (KEs). Many AOP-Wiki KEs describe molecular, cellular, or tissue-level processes and can therefore be assessed with gene expression data, making transcriptomics of human in vitro models a NAM data generator. In AOP-Wiki, KEs are described by Key Event Components (KECs). A gene set can be […]
- by Li, Y., Diab, A. R., Lamane, A., Lindsay, J. R., Rodig, S. J., Irizarry, R. A., Lotter, W.Multiplex immunofluorescence (mIF) assays such as ImmunoProfile provide standardized quantification of prognostic immune markers but are costly and not routinely used in clinical settings. We developed a weakly-supervised AI model, HistoProfile, to estimate intratumoral cell densities of key immune biomarkers (CD8, FOXP3, PD-1, and PD-L1) and the PD-L1 tumor proportion score from routine H&E-stained whole-slide images. Trained on a large pan-cancer cohort with paired H&E and mIF data, HistoProfile discriminated biomarker-high from biomarker-low tumors in held-out samples and tumor-specific subgroups […]
- by Matthias, J. H., Yao, J., Hicks, S. C.The rapid adoption of spatial transcriptomics (ST) technologies has been accompanied by substantial growth in computational methods, creating an increasing need for systematic and reliable benchmarking, particularly as analyses increasingly extend from individual tissue sections to three-dimensional (3D) tissue reconstruction. Existing benchmarks often rely on a small and similar set of experimentally-derived datasets because they offer a reliable ground truth label, which is hard to find in practice. Simulated or synthetic data provide an alternative, yet most existing simulators either […]
- by Singh, H., SINGH, R. K., Krishna, C. S., Srivastava, S. P., Gorantla, R.Efficient lipid design under limited experimental budgets is a central challenge in computational chemistry and drug discovery. We introduce LEAF (Lipid Evolutionary Adaptive Framework), a matched-budget protocol for testing whether language-model proposers improve combinatorial molecular search relative to classical baselines. The study uses a 30,044-candidate ionizable-lipid space, a frozen Gaussian-process oracle fitted to experimental potency labels, and a separate active-learning surrogate. Four language models evaluated over eight seeds and three splits show no significant improvement over genetic-algorithm or random-search baselines. […]
- by Meng, L., Zhu, J., Han, B., Zang, Y., Li, W., Zong, K., Zhong, J., Yang, Y., Liu, J., Jia, J., Sun, R., Yu, G., Han, J., Chen, Y., Zhang, L., Xu, J.Single-cell foundation models typically represent cells as flat sequences of individual genes, requiring higher-order biological organization to be inferred implicitly from sparse expression profiles. Similar to the evolution from character-level to semantic tokenization in natural language processing,we hypothesize that cellular states can be more efficiently represented using biologically meaningful intermediate units. Here we present BioMod, a 50-million-parameter single-cell foundation model that introduces biological modules as representation units between genes and cells. BioMod constructs an overlapping vocabulary of 660 biological modules […]
- by Otto, D. J., Baasri, S., Setty, M.Cell-by-cell and gene-by-gene relationships, such as kernels and correlations, shape most single-cell analyses but are rarely inspected directly due to a lack of visualization tools that display them. AnnZarro is a point-and-click browser viewer that shows these matrices linked to an AnnData object's cells x genes data. Using AnnZarro, experimental biologists can explore data without code and computational biologists can probe the relationships behind their analyses. One focused cell and one focused gene drive every panel. Clicking a cell paints […]
- by Salami, R. O., Kumordzi, S. M., Amuna, D. N., Carr, R. A., Morang'a, C. M.Integrative macromolecular docking pipelines generate thousands of candidate structural decoys, relying on downstream pairwise ensemble analysis, including Root-Mean-Square Deviation (RMSD) matrices and Fraction of Common Contacts (FCC) clustering, to identify biologically relevant binding poses. However, pairwise structural comparisons scale quadratically (O(N^2)), and canonical workflows in HADDOCK3 historically rely on disk-bound trajectory serialization and iterative CPU set operations, creating a quadratic computational and storage bottleneck for large ensembles. Here, we demonstrate that these operations can be reformulated as continuous linear algebra […]
- by Liehrmann, A., Carrel Billiard, L., Bastide, P., Gallopin, M., Richard, H., Laine, E.Alternative splicing diverges rapidly between species, yet its comparative analysis lags far behind that of gene expression: junction orthology is defined on a single reference genome, species are treated as independent samples, and detected shifts are rarely grounded in sequence-level evidence. We present phyloDS, an RNA-seq–driven framework that resolves all three limitations. phyloDS defines orthologous splice junctions on multiple sequence alignments of one-to-one orthologous genes, tests their differential usage with a regularized Ornstein–Uhlenbeck model, and cross-validates detected shifts against splice-site […]
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