Biology subjects

Ross, C.

Publications and source records attributed to Ross, C..

At least 19 recordsLinked to original sources

bioRxiv2026

H3K27me3 Drives Constricted Migration Induced 3D Genome Rewiring in Melanoma

Repeated exposure of neoplastic cells to mechanical stresses during metastasis can drive stable morphological and physiological changes. We previously showed that A375 human melanoma cells subjected to 10 rounds of constricted migration ("Bottom-10 cells") became significantly more migratory and exhibited H3K9me3 relocalization, transcriptional remodeling, and chromatin compartment changes relative to naive parental A375 cells. Because these phenotypes persist across cell divisions, we hypothesized they are driven and maintained by specific epigenetic mechanisms. Here, we profiled candidate histone modifications by CUT&RUN and applied a computational model to identify marks that explain compartment switches. In parental cells, H3K9me3 and H3K4me1 strongly predict locus stability in the B and A compartments, respectively. In contrast, changes in H3K27me3 dynamically predict A-to-B compartment switching after constricted migration. Consistently, altered H3K27me3 enrichment correlates with both differentially regulated genes and chromatin compartment changes between Bottom-10 and parental populations. We therefore tested whether inhibiting H3K27me3 deposition alters migratory potential and/or the "memory" of the increased migratory phenotype. Inhibiting EZH1/2 reduced migration efficiency overall, with a stronger effect on constricted than unconstricted migration. This reduction was accompanied by decreased genomic H3K27me3 enrichment and reversal of some compartment changes in Bottom-10 cells. However, acute treatment did not durably reverse the highly migratory Bottom-10 phenotype; cells returned to their initial state after drug removal. Chronic inhibition across many sequential rounds of constricted migration dramatically reduced the fraction of cells able to migrate. Notably, cells that migrated despite chronic EZH inhibition appeared to escape treatment, acquiring many typical Bottom-10 H3K27me3 and compartment changes even though acute inhibition tends to prevent them. Overall, these results highlight H3K27me3 as a key contributor to establishing and maintaining constricted migration-induced 3D genome changes.

genomics↗

bioRxiv2026

WildAlert: A Real-Time, AI-Driven Early Warning System for Wildlife Health and Ecological Threat Detection

Emerging infections and environmental disruptions increasingly threaten wildlife and ecosystem health. Free-ranging wildlife often serve as early indicators of ecological instability, making timely detection of morbidity and mortality events critical for early warning. Yet, existing systems lack the analytical capacity for real-time outbreak detection. We present WildAlert, an AI-driven early warning system that integrates fine-tuned BERT-based natural language processing models with unsupervised anomaly detection framework to identify unusual wildlife health events using real-time pre-diagnostic clinical data from wildlife rehabilitation organizations. The NLP module achieved high accuracy across clinical classifications and circumstances of admissions, enabling a pre-diagnostic syndromic surveillance framework. Retrospective validation demonstrated that WildAlert anomalies frequently coincided with or preceded confirmed morbidity events, including highly pathogenic avian influenza (HPAI), harmful algal bloom-associated toxicosis, cold-stunning in sea turtles, mass stranding events, West Nile virus, and mycoplasmosis. WildAlert establishes the worlds largest standardized, near real-time wildlife health surveillance system, transforming wildlife rehabilitation clinical records into actionable intelligence capable of detecting anomalies across taxa and regions, often before other surveillance methods. WildAlert provides a transferable analytical framework and scalable One Health model linking biodiversity monitoring, zoonotic disease preparedness, and ecosystem-linked environmental threats, with implications for conservation, public health and environmental hazard response.

ecology↗

bioRxiv2026

Systemic neoantigen-specific T cells reveal central determinants of PD-(L)1 blockade efficacy

The contribution of neoantigen-specific T cells to PD-(L)1 efficacy has largely been inferred from tumor mutational burden. We functionally profiled circulating T cell responses against 7,038 predicted HLA-I-restricted and 21,453 HLA-II-restricted neopeptides in 27 patients with advanced non-small cell lung cancer treated with anti-PD-(L)1. CD4 responses were frequent and correlated with neoantigen availability but not clinical benefit. In contrast, the magnitude and breadth of neoantigen-specific CD8 T cell responses were associated with clinical benefit, progression-free and overall survival, independently of tumor mutational burden. Patients mounting coordinated CD4 and CD8 responses experienced improved progression-free survival. Tumors from CD8 responders displayed immune signatures indicative of both T cell priming and effector functions. Circulating neoantigen-specific CD8 T cells recognized endogenously processed antigens, trafficked to tumors, and selectively expanded under therapy while retaining CD28, CD226, and CXCR3 expression. These findings identify coordinated, functionally engaged neoantigen-specific T cell responses as central determinants of PD-(L)1 efficacy.

cancer biology↗

bioRxiv2026

The Bayesian Inference library for Python R and Julia

O_LIBayesian modeling is a cornerstone of modern ecological and evolutionary research, offering the flexibility to account for hierarchical structures, imperfect detection, and spatial dependencies. However, as ecological datasets grow in scale and complexity--from high-resolution telemetry to phylogenomics--researchers increasingly face a "computational ceiling" where traditional CPUbound inference becomes prohibitively slow. C_LIO_LIThe current software landscape is fragmented. Researchers must often choose between high-level interfaces (e.g., brms in R) that are intuitive but sometimes rigid or slow for massive datasets, and low-level probabilistic programming languages (e.g., Stan, PyMC, JAX) that offer high performance but require specialized programming expertise. C_LIO_LIThis fragmentation is compounded by an "interoperability tax," where code developed in one language (e.g., R) cannot easily leverage the hardware-accelerated backends (GPUs/TPUs) typically found in Python-centric machine learning frameworks. C_LIO_LITo address these issues, we introduce BayesForge(BF), a cross-platform software ecosystem available in Python, R, and Julia. BF provides a unified, intuitive syntax that bridges the gap between ease-of-use and high-performance computation. By leveraging JAX-based backends (NumPyro and TensorFlow Probability), BF enables seamless hardware acceleration under-the-hood. C_LIO_LIWe demonstrate BFs utility through three ecological case studies: social network analysis (Social Relations Model), macroevolutionary uncertainty propagation across posterior tree sets, and latent-variable estimation for vocal repertoires. Benchmarks reveal that BF can achieve up to a 270-fold speedup over Stan implementations for large-scale networks, transforming weeks of computation into minutes and enabling more robust, uncertainty-aware ecological inference. C_LI

bioinformatics↗

bioRxiv2025

Machine Learning Guided Structure Activity Discovery of Polymer Configurations in Lipid Nanoparticles for Kiss-and-Run Endosomal Escape

Endosomal escape remains a major barrier to effective nucleic acid delivery via lipid nanoparticles (LNPs). Here, we address this challenge by incorporating a pH-sensitive polymer, polyhistidine, into LNPs (pLNPs) to facilitate endosomal escape, with a focus on optimizing the polymers molecular weight (MW) and configuration--parameters that remain largely unexplored. Through systematic engineering, we designed linear and branched polyhistidine architectures with varied MWs and configurations. In vivo screening identified an optimized pLNP formulation incorporating a symmetrical bis-lysine histidine dendron with a MW of [~]1800 g/mol, which achieved a 266-fold increase in liver bioluminescence following intravenous delivery of luciferase mRNA compared to standard LNPs at an equivalent RNA dose. Mechanistic studies revealed that polymer configuration within pLNPs is critical for eliciting the proton sponge effect, leading to osmotic swelling and endosomal rupture. This configuration also promoted rapid endosomal membrane destabilization via a kiss-and-run mechanism, enabling efficient cytosolic release. When delivering base editor mRNA and single-guide RNA, the optimized pLNPs achieved 8% gene editing efficiency in the mouse liver at a low dose of 0.1 mg/kg, compared to 1% with standard LNPs. To accelerate discovery and address macromolecular design challenges, we developed a machine learning (ML) framework based on amino acid-level graph neural networks (GNNs). This approach identified branched, dendritic configurations with densely arranged histidine residues on a multivalent core as key determinants of delivery performance. The top ML-predicted candidate, NS535, achieved a 705-fold increase in liver bioluminescence over standard LNPs, validating our data-driven design strategy. Together, these findings establish a closed-loop platform integrating rational design, mechanistic validation, and ML-guided optimization to advance RNA delivery. By elucidating structure-activity relationships for polyhistidine carriers and demonstrating efficient, low-dose genome editing, this work provides a blueprint for next-generation nucleic acid therapeutics.

bioengineering↗

bioRxiv2025

Disparate social structures are underpinned by distinct social rules across a primate radiation

Over six decades of research on wild baboons and their close relatives (collectively, the African papionins) have uncovered substantial variation in their behavior and social systems. While most papionins form discrete social groups (single-level societies), a few others form small social units that are nested within larger supergroups (multi-level societies). These two systems are generally thought to be qualitatively distinct, but data from wild populations increasingly suggest that there may be areas of overlap. To quantify this potential gradient in social structure, a more systematic, comparative analysis is needed. Here, we constructed a database of behavioral and demographic records spanning 135 group-years, 28 social groups, 13 long-term field studies, and 11 species to quantify variation in grooming network structure, and identify the individual and dyadic properties (e.g., kinship and social status effects) that underlie this variation. Consistent with accumulating observations in the field, the single-level species could be divided into two categories: cohesive and cliquish. Cohesive single-level networks were dense, kin-biased, and moderately rank-structured, while cliquish single-level networks were more differentiated, slightly more kin-biased, and strongly rank-structured. As expected, multi-level networks were very modular and shaped by females ties to specific dominant males but varied in their kin biases. Taken together, these data suggest that (i) kin and rank biases are widespread but vary in their strength; (ii) male-centered subgroups are exclusive to multi-level systems; and (iii) increases in network modularity can emerge in response to heightened nepotism and male-centered clustering. SIGNIFICANCE STATEMENTWhat forces explain variation in primate societies? While kinship and dominance shape the social lives of many of our close relatives, it is unclear how their effects differ across species. Using a new database comprising decades of field research, we found that baboons and their close relatives fell into three general patterns: one in which groups were cohesive, kin-biased, and moderately rank-biased, another in which groups were more cliquish and nepotistic, and a third in which groups were divided into clusters centered on dominant males. Distinct primate societies may thus reflect differences in the strength of females nepotistic biases and the degree of males social influence.

animal behavior and cognition↗

bioRxiv2025

A global genetic interaction map of a human cell reveals conserved principles of genetic networks

We generated a genome-scale, genetic interaction network from the analysis of more than 4 million double mutants in the haploid human cell line, HAP1. The network maps [~]90,000 genetic interactions, including thousands of extreme synthetic lethal and genetic suppression interactions. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes, pathways, biological processes, and cellular compartments. Comparative analyses showed that general principles of genetic networks are conserved from yeast to human cells. A genetic interaction network mapped in a single genetic background complements the DepMap gene co-essentiality network, recapitulating many of the same biological connections and also capturing unique functional information to reveal roles of uncharacterized genes and molecular determinants of specific cancer cell line genetic dependencies.

systems biology↗

bioRxiv2025

Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens

Genetic interaction (GI) networks in model organisms have revealed how combinations of genome variants can impact phenotypes. To advance efforts toward a reference human GI network, we developed the quantitative Genetic Interaction (qGI) score, a method for precise GI measurement from genome-wide CRISPR-Cas9 screens in different query mutants constructed in a single human cell line. We found surprising prevalent systematic variation unrelated to GIs in CRISPR screen data, including both genomically linked effects and functionally coherent covariation. Leveraging [~]40 control screens in wild-type cells and half a billion differential fitness effect measurements, we developed a pipeline for CRISPR screen data processing and normalization to correct these artifacts and measure accurate, quantitative GIs. We also comprehensively characterized GI reproducibility by characterizing 4 - 5 biological replicates for [~]125,000 unique gene pairs. The qGI framework enables systematic identification of human GIs and provides broadly applicable strategies for analyzing context-specific CRISPR screen data.

bioinformatics↗

bioRxiv2025

A new resource of clonal pluripotent human stem cell lines exhibiting inter- and intra-embryo consistency and variability

Human naive pluripotent stem cells can generate all somatic tissues and extra-embryonic components of the blastocyst. We derived multiple clonal naive pluripotent stem cell lines from individual embryos by physical separation of inner cell mass cells and subsequent individual expansion of each resulting dome-shaped colony, providing the foundation for a resource to investigate intra- and inter-embryo variation. Twenty lines were derived from ten embryos donated from nine couples. While differences between lines are observed, the overarching pluripotency circuitry is preserved in each. They can differentiate into extra-embryonic lineages and readily acquire post-implantation pluripotent identity when exposed to culture conditions driving in vitro capacitation, subsequently to generate derivatives of the three germ layers: ectoderm, mesoderm and endoderm. Some lines exhibit intra-chromosomal amplification and deletions and are therefore anticipated to provide a valuable, accessible system for modelling chromosomal mosaicism and its potential consequences using chimeric organoids, such as blastoids and gastruloids.

developmental biology↗

bioRxiv2025

Klebsiella pneumoniae disrupts vasodilation by targeting eNOS post translational modifications via the type VI secretion system and the capsule polysaccharide

Vasodilation is a crucial protective response to inflammation and infection. Endothelial cells control vasodilation through the bioavailability of eNOS-produced nitric oxide (NO), and the generation of endothelium-dependent hyperpolarization (EDH). Here, we demonstrate that Klebsiella pneumoniae, one of the most prevalent blood stream infection pathogens, inhibits agonist-induced vasodilation by blunting the NO-dependent pathway and attenuating the EDH pathway. The type VI secretion system (T6SS) effector VgrG4 licences the kinase PKC{beta} in an NLRX1-controlled mitochondria reactive oxygen species (mtROS)-dependent manner to phosphorylate the eNOS inhibitory site Thr495, effectively dampening eNOS activity. The capsule polysaccharide, on the other hand, limits the phosphorylation of the eNOS activation site Ser1177 by inducing the phosphatase PP2Ac upon activation of an EGF receptor-dependent pathway. VgrG4-induced mtROS attenuates the EDH pathway. Overall, this work reveals a new anti-host activity of the T6SS and illustrates how pathogens can control vascular biology by targeting eNOS post translational modifications.

microbiology↗

bioRxiv2025

Investigating the genomic landscape of mouse models of breast cancer metastasis

Metastasis remains a major cause of cancer mortality. AbstractThis study, expanding upon previous findings in the MMTV-PyMT model, investigated four independent mouse models, representing luminal (MMTV-PyMT, MMTV-Myc), HER2-amplified (MMTV-Her2) and triple negative (C3(1)TAg) breast cancer subtypes. Consistent with previous results, limited evidence for metastasis-associated somatic point mutations was found for all models. We also found that oncogenic drivers significantly influenced the number and size of metastasis-specific copy number variations (MSCNVs), but common driver-independent MSCNVs were rare. Furthermore, analyzing a cohort with varying genetic backgrounds while maintaining a constant oncogenic driver (PyMT) revealed that genetic background profoundly impacts MSCNVs. Transcriptome analysis demonstrated that oncogenic drivers strongly shaped metastasis-specific gene expression (MSGE), with each driver exhibiting distinct expression profiles. In contrast, MSGE in the PyMT-F1 cohort was more variable across strains. Despite the diversity of MSCNV and MSGE, functional analysis revealed that both mechanisms converge on the modulation of key cellular processes, including immune responses, metabolism, and extracellular matrix interactions. These findings emphasize the complex interplay between oncogenic drivers and genetic background in shaping the genomic and transcriptional landscapes of metastatic lesions.

cancer biology↗

bioRxiv2024

WNT-mediating TCF/LEF transcription factor gene expression in early human pluripotency and cell lineages differs from the rodent paradigm

Embryonic stem cell research has uncovered different requirements for WNT/{beta}-catenin signalling in human naive pluripotent cells compared to the mouse paradigm. It is therefore important to study WNT/{beta}-catenin signalling directly in models of early human development. Since TCF/LEF factors mediate the regulation of target genes downstream of WNT/{beta}-catenin signalling, we studied the expression and protein localisation of the four TCF/LEF genes by analysing in vitro "snapshots" of human development, leveraging naive and primed pluripotent cells as well as extraembryonic and early embryonic cell lineages. Strikingly, we comprehensively confirm clear differences between mouse and human pluripotent stem cells, suggesting species-specific requirements for WNT signalling that may reflect differences in states of pluripotency. Human naive ES cells express very low TCF7L1, unlike their mouse counterparts. TCF7L2 is robustly expressed in human naive ES-derived trophectoderm cells. In human primed pluripotent stem cells, activation of WNT/{beta}-Catenin signalling is required to induce expression of both TCF7 and LEF1, concomitant with hallmark gastrulation markers. This expression of human TCF/LEF genes benchmarks differential requirements for WNT/{beta}-catenin signalling throughout early human embryo development that requires further investigation.

developmental biology↗

bioRxiv2024

Robust Bayesian analysis of animal networks subject to biases in sampling intensity and censoring

Data collection biases are a persistent issue for studies of social networks. This issue has been particularly important in Animal Social Network Analysis (ASNA), where data are unevenly sampled and such biases may potentially lead to incorrect inferences about animal social behavior. Here, we address the issue by developing a Bayesian generative model, which not only estimates network structure, but also explicitly accounts for sampling and censoring biases. Using a set of simulation experiments designed to reflect various sampling and observational biases encountered in real-world scenarios, we systematically validate our model and evaluate its performance relative to other common ASNA methodologies. By accounting for differences in node-level censoring (i.e., the probability of missing an individual interaction.), our model permits the recovery of true latent social connections, even under a wide range of conditions where some key individuals are intermittently unobserved. Our model outperformed all other existing approaches and accurately captured network structure, as well as individual-level and dyad-level effects. Antithetically, permutation-based and simple linear regression aprroaches performed the worst across many conditions. These results highlight the advantages of generative network models for ASNA, as they offer greater flexibility, robustness, and adaptability to real-world data complexities. Our findings underscore the importance of generative models that jointly estimate network structure and adjust for measurement biases typical in empirical studies of animal social behaviour.

animal behavior and cognition↗

bioRxiv2024

Comparative lifespan and healthspan of nonhuman primate species common to biomedical research

There is a critical need to generate age- and sex-specific survival curves to characterize chronological aging consistently across nonhuman primates (NHP) used in biomedical research. Sex-specific Kaplan-Meier survival curves were computed in 12 translational aging models: baboon, bonnet macaque, chimpanzee, common marmoset, coppery titi monkey, cotton-top tamarin, cynomolgus macaque, Japanese macaque, pigtail macaque, rhesus macaque, squirrel monkey, and vervet/African green. After employing strict inclusion criteria, primary results are based on 12,269 NHP that survived to adulthood and died of natural/health-related causes. A secondary analysis was completed for 32,616 NHP that died of any cause. Results show a pattern of reduced male survival among catarrhines (African and Asian primates), especially macaques, but not platyrrhines (Central and South American primates). For many species, median lifespans were lower than previously reported. An important consideration is that these analyses may offer a better reflection of healthspan than lifespan since research NHP are typically euthanized for humane welfare reasons before their natural end of life. This resource represents the most comprehensive characterization of sex-specific lifespan and age-at-death distributions for 12 biomedically relevant species, to date. These results clarify relationships among NHP ages and provide a valuable resource for the aging research community, improving human-NHP age equivalencies, informing investigators of expected survival rates, providing a metric for comparisons in future studies, and contributing to understanding of factors driving lifespan differences within and among species.

physiology↗

bioRxiv2022

Cell projection plots: a novel visualization of bone marrow aspirate cytology

Deep models for cell detection have demonstrated utility in bone marrow cytology, showing impressive results in terms of accuracy and computational efficiency. However, these models have yet to be implemented in the clinical diagnostic workflow. Additionally, the metrics used to evaluate cell detection models are not necessarily aligned with clinical goals and targets. In order to address these issues, we introduce cell projection plots (CPPs), which are novel, automatically generated visual summaries of bone marrow aspirate specimens. CPPs provide a compact summary of bone marrow aspirate cytology, and encompass relevant biological patterns such as neutrophil maturation. To gauge clinical relevance, CPPs were shown to three hematopathologists, who decided whether shown diagnostic synopses matched with generated CPPs. Pathologists were able to match CPPs to the correct synopsis with 85% accuracy. Our finding suggests CPPs can compactly represent clinically relevant information from bone marrow aspirate specimens, and may be used to efficiently summarize bone marrow cytology to pathologists. CPP could be a step toward human-centered implementation of artificial intelligence (AI) in hematopathology, and a basis for a diagnostic support tool for digital pathology workflows.

pathology↗

bioRxiv2022

Plakoglobin is a mechanoresponsive regulator of naïve pluripotency

Biomechanical cues are instrumental in guiding embryonic development and cell differentiation. Understanding how these physical stimuli translate into transcriptional programs could provide insight into mechanisms underlying mammalian pre-implantation development. Here, we explore this by exerting microenvironmental control over mouse embryonic stem cells (ESCs). Microfluidic encapsulation of ESCs in agarose microgels stabilized the naive pluripotency network and specifically induced expression of Plakoglobin (Jup), a vertebrate homologue of {beta}-catenin. Indeed, overexpression of Plakoglobin was sufficient to fully re-establish the naive pluripotency gene regulatory network under metastable pluripotency conditions, as confirmed by single-cell transcriptome profiling. Finally, we found that in the epiblast, Plakoglobin was exclusively expressed at the blastocyst stage in human and mouse embryos - further strengthening the link between Plakoglobin and naive pluripotency in vivo. Our work reveals Plakoglobin as a mechanosensitive regulator of naive pluripotency and provides a paradigm to interrogate the effects of volumetric confinement on cell-fate transitions. HighlightsO_LI3D agarose spheres stabilize the naive pluripotency network in mouse ESCs. C_LIO_LIVolumetric confinement induces expression of Plakoglobin, a vertebrate homologue of {beta}-catenin. C_LIO_LIPlakoglobin expression in the epiblast is specific to pre-implantation human and mouse embryos. C_LIO_LIPlakoglobin overexpression maintains naive pluripotency independently of {beta}-catenin. C_LI

developmental biology↗

bioRxiv2022

Mutation Rate Evolution Drives Immune Escape In Mismatch Repair-Deficient Cancer

Mutation rate optimisation drives evolution and immune evasion of bacteria and lentiviral strains, including HIV. Whether evolving cancer lineages similarly adapt mutation rates to increase tumour cell fitness is unknown. Here, by mapping the clonal topography of mismatch repair-deficient (MMRd) colorectal cancer, we show that genomic MMRd mutability co-evolves with neoantigen selection to drive intratumour diversification and immune escape. Mechanistically, we find that microsatellite instability modulates subclonal DNA repair by toggling two hypermutable mononucleotide homopolymer runs in the mismatch repair genes MSH6 and MSH3 (C8 and A8, respectively) through stochastic frameshift switching. Spontaneous mutation and reversion at these evolvability switches modulates subclonal mutation rate, mutation bias, and clonal HLA diversity during MMRd cancer evolution. Combined experimental and simulation studies demonstrate that subclonal immune selection favours incremental MMR mutations. MMRd cancers thus fuel intratumour heterogeneity by adapting subclonal mutation rate and mutation bias to immune selection, revealing a conserved co-evolutionary arms race between neoantigen selection and adaptive genomic mutability. Our work reveals layers of mutational complexity and microsatellite biology in MMRd cancer evolution previously hidden in bulk analyses.

cancer biology↗

bioRxiv2021

Crowdsourcing biocuration: the Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about known gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a ten-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills. Significance StatementThe primary scientific literature catalogs the results from publicly funded scientific research about gene function in human-readable format. Information captured from those studies in a widely adopted, machine-readable standard format comes in the form of Gene Ontology annotations about gene functions from all domains of life. Manual annotations based on inferences directly from the scientific literature, including the evidence used to make such inferences, represents the best return on investment by improving data accessibility across the biological sciences. To supplement professional curation, our CACAO project enabled annotation of the scientific literature by community annotators, in this case undergraduates, which resulted in contribution of thousands of validated entries to public resources. These annotations are now being used by scientists worldwide.

bioinformatics↗