Biology subjects

Cai, Y.

Publications and source records attributed to Cai, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Biosynthetic additive manufacturing through mycelium-bacteria consortia

Lignocellulosic biomass is the most abundant renewable raw material on Earth, yet its structural and carbon-storage potential remains unrealized: microbial decomposition returns stored carbon to the atmosphere before it can be harnessed as a durable material. Distinct microbial processes, such as biosynthesis and biomineralization, offer a natural counterpoint, converting organic carbon into mechanically robust, persistent materials such as polymers and minerals. Here, we establish a biosynthetic additive manufacturing strategy through mycelium-bacteria consortia, by coupling fungal self-assembly with bacterial biomineralization inside fabricated three-dimensional scaffolds derived from lignocellulosic biomass. Trametes versicolor forms a continuous living mycelial network that serves as both a structural template and a transport pathway, guiding the spatial colonization of Sporosarcina pasteurii and enabling volumetric calcium carbonate deposition throughout the scaffold interior, overcoming the surface-limited mineralization of conventional microbial systems. Integration with helicoidal Bouligand architectures translates microscale mineral reinforcement into macroscale performance, increasing compressive Young's modulus by 7-14-fold and ultimate strength by 5-fold relative to unmineralized conventional mycelium-based living composites. The living mycelial network also enables autonomous self-healing and modular self-assembly through hyphal bridging without external adhesives or energy input. This work establishes a scalable route for converting and upcycling transient biomass carbon into durable living structural materials for sustainable construction.

bioengineering↗

bioRxiv2026

Brain state locks silent memories in a trained fly connectome

Complete connectomes now exist for insect nervous systems, but whether a fixed wiring diagram can learn, and what its memories consist of, is unknown. Here, we trained a spiking model of the whole male Drosophila central nervous system, 167,106 neurons with fixed wiring, to plan moves and to remember a visual cue. Spikes write the cue into neuronal adaptation, which holds it silently until the next input reads it out. Cells that hold the trace are enriched for transcripts of a calcium-activated potassium channel in fly cell atlases. The learned readout recalls the trace only in the brain state of learning: the same trace evokes a different response at another delay, and a disease-like loss of potassium current rewrites the trace and changes how it is read. Learning in the new state is spared. Memory failure can arise from a change of state rather than a loss of storage.

neuroscience↗

bioRxiv2026

Agentic Discovery Transfer Enables Cross-Cancer Discovery at Scale

Cancer research generates tens of thousands of studies each year, yet whether a published finding holds in another cancer type or patient population is rarely tested, because doing so is labor-intensive and difficult to scale. We define this task as discovery transfer and present SMART, a multi-agent large language model framework for discovery transfer in single-cell RNA-sequencing (scRNA-seq) studies. Given a source manuscript and a target scRNA-seq dataset, SMART extracts major clinical and mechanistic findings, generates and executes analyses for the testable findings, and reports which findings transfer and suggests follow-up. Applied to 121 studies across six cancer types, SMART identified findings that transfer across cancers, including a lung cancer prognostic signature that we confirmed to be associated with survival in liver cancer, pancreatic cancer and pleural mesothelioma. SMART also generated new mechanistic hypotheses, demonstrating how agentic discovery transfer can extend published findings beyond their original setting.

bioinformatics↗

bioRxiv2026

The Sensitivity of 13C-Metabolic Flux Analysis to Biomass Composition Underscores the Need for Accurate Biomass Formulation in Escherichia coli

Quantifying intracellular fluxes through 13C-metabolic flux analysis (13C-MFA) provides a detailed view of cellular metabolism. While model formulation, including biomass synthesis reactions, is known to influence flux estimations, the degree to which biomass composition affects 13C-MFA outcomes in Escherichia coli remains debated. Here, we reconstructed a genome-scale 13C-MFA model of E. coli incorporating explicit nucleotide biosynthesis and a modular biomass formulation that separates protein, RNA, and other components. Using isotopic labeling experiments and systematic perturbations of biomass composition, we demonstrate that 13C-MFA can robustly differentiate subtle shifts in the protein/RNA ratio, with deviations as small as 2-3% producing statistically significant but biologically interpretable changes in model fit. Reaction-level analyses revealed consistent flux adjustments across amino acid and nucleotide biosynthesis, while pathways in one-carbon metabolism, particularly serine, glycine, and threonine interconversions, exhibited the strongest responses. Collectively, these results highlight the robustness and discriminative power of 13C-MFA and also demonstrate the importance of accurate biomass composition measurement in E. coli 13C-MFA, given the intrinsic sensitivity of the method to macromolecular stoichiometry.

systems biology↗

bioRxiv2026

Short-Term Plasticity of Contrast Surround Suppression During Repeated Psychophysical Measurement

Perceptual surround suppression is commonly treated as stable within a testing session, but recent evidence for normalization reweighting suggests that suppressive interactions can be modified by recent visual input. Here, we asked whether surround suppression changes over minutes of repeated measurement and whether such change varies with stimulus and sampling conditions. Across four psychophysical experiments, we tracked contrast and motion surround suppression while varying center-surround orientation and stimulus spatiotemporal properties. With static gratings, contrast surround suppression increased early and then approached a plateau, with no evidence that this change depended on center-surround orientation. With dynamic gratings, an increase emerged only under finer temporal sampling and more sustained stimulation, and model-based analyses suggested a faster increase than with static stimulation. Motion surround suppression measured with drifting gratings showed no systematic change. Together, these findings show that contrast surround suppression can change within a single psychophysical session without a separate adaptation phase, and that its measured time course varies with stimulus and sampling conditions. The results are consistent with rapid, experience-dependent reweighting of contextual normalization.

neuroscience↗

bioRxiv2026

A unified framework for quantitative splicing and transcript prediction

RNA splicing is frequently disrupted by genetic variation, contributing to a wide range of human diseases. Identifying the variants responsible for altered splicing is therefore crucial but has long been challenging. Deep learning models that predict splicing from genomic sequence have substantially advanced their detection, but accurately resolving their quantitative effects on splicing and the resulting transcripts remains an unmet need. Here we introduce SpliceAI2, a deep learning model trained end-to-end on splice site, splice junction, and transcript usage across multiple mammalian species. SpliceAI2 reconstructs complete transcripts directly from genomic sequence and considerably improves identification of splice-altering variants and quantification of their effects in diverse benchmarks spanning cryptic splicing, splicing quantitative trait loci, and massively parallel reporter assays. Human population datasets provide independent validation of these predicted functional effects through evidence of natural selection and associated changes in plasma protein abundance. Application to a rare disease cohort reveals that predicted splice-altering variants are highly enriched in disease-associated genes and account for 15% of the excess genetic burden, with approximately half residing in deep intronic regions likely missed by exome sequencing. Together, these findings establish SpliceAI2 as a major step forward in interpreting splice-altering variants across the human genome.

genomics↗

bioRxiv2026

Exchange of metabolic pathway intermediates as the origin for metabolite cross-feeding interactions in E. coli auxotrophic co-cultures

A large fraction of microbes in natural environments are auxotrophs that rely on metabolite exchange for growth. The Black Queen hypothesis and related frameworks explain gene loss and reliance on shared metabolites. Yet it is not fully understood how metabolite cross-feeding emerges and gives rise to experimentally observable community performance. Here, we propose that exchange of biosynthetic pathway intermediates provides a mechanistic route for the emergence of metabolite cross-feeding. Building on prior work demonstrating intermediate exchange in E. coli auxotrophs, we investigated co-cultures between a methionine auxotroph ({Delta}metA) and a panel of histidine auxotrophs. Among these, only {Delta}hisD exhibited efficient co-culture growth with {Delta}metA, suggesting a unique role for the final step of histidine biosynthesis, which converts histidinol to histidine. We found that {Delta}metA-{Delta}hisD co-cultures accumulated high levels of extracellular histidinol (>200 M), suggesting a mechanism for metabolite exchange. Spent media from these co-cultures supported growth of all histidine auxotrophs except {Delta}hisD, confirming that histidinol, rather than histidine, was the dominant exchanged metabolite. Furthermore, we observed that {Delta}metA efficiently converted histidinol to histidine only under methionine-limited conditions, suggesting that nutrient limitation promoted overflow of converted histidine to the extracellular environment. To quantitatively assess whether histidinol exchange could account for the observed co-culture behavior, we constructed a mechanistic model that links extracellular histidinol dynamics to co-culture growth through independently measured conversion capacity of the {Delta}metA strain. Rather than fitting growth empirically, we used experimentally derived parameters to predict co-culture growth from the measured histidinol-to-histidine conversion flux. The model accurately recapitulated the timing and magnitude of growth and population dynamics, supporting the idea that accumulation of histidinol enabled the conversion-driven supply of histidine that sustained {Delta}hisD, while coupling growth between the two strains. Taken together, these results suggest that metabolite cross-feeding in syntrophic co-cultures can emerge from the accumulation of pathway intermediates and their conditional conversion under nutrient limitation, providing a plausible mechanism for the rapid establishment of mutualistic interactions.

microbiology↗

bioRxiv2026

KRAS-driven metabolic reprogramming of enhanced MFSD2A-mediated lysophosphatidylcholine scavenging promotes survival and progression of pancreatic ductal adenocarcinoma

Oncogenic KRAS drives lipid reprogramming in pancreatic ductal adenocarcinoma (PDAC) to promote disease progression, and these changes are manifest in circulation. Using mass spectrometry, we performed lipidomic analyses on plasmas from a cohort of 93 newly-diagnosed resectable PDAC cases, 43 patients with chronic pancreatitis, and 93 age- and sex-matched healthy controls, the results of which revealed pronounced reductions in circulating lysophosphatidylcholines (LysoPC) as a prominent feature associated with PDAC. Using stable-isotope resolved lipidomics, we further found that PDAC cells exhibit a lipid scavenging phenotype characterized by preferential uptake of extracellular unsaturated LysoPCs to sustain pro-growth signals. Restricting bioavailability of extracellular unsaturated LysoPCs shifted the metabolic phenotype of PDAC cells towards enhanced de novo lipogenesis and autophagy, which was accompanied by suppression of AKT signaling activities and increased susceptibility to apoptosis. Using bulk, single-cell, and spatial transcriptomic datasets together with functional experiments, we identified oncogenic KRAS-mediated upregulation of major facilitator superfamily domain-containing protein 2a (MFSD2A) as a key mediator that facilitates extracellular uptake of LysoPCs in PDAC cells. Loss of MFSD2A expression mimicked LysoPC restriction and resulted in inhibition of AKT signaling and increased propensity of PDAC cells to undergo apoptosis in vitro and suppressed tumor growth in vivo. Therapeutic targeting of the KRAS-MFSD2A-LysoPC axis via repurposing of the synthetic alkyl-lysophospholipid edelfosine promoted potent anti-cancer effects in vitro that were mechanistically attributed to reduced extracellular uptake of LysoPCs, and attenuation of AKT signaling. Collectively, our findings describe a previously unrecognized onco-metabolic program of enhanced LysoPC scavenging mediated by MFSD2A that promotes PDAC progression and that is therapeutically targetable via repurposing edelfosine.

cancer biology↗

bioRxiv2026

Gap-free telomere-to-telomere haplotypes assembly of the hybrid grouper 'Yushuban' (Cromileptes altivelis female x Epinephelus fuscoguttatus male)

The hybrid grouper 'Yushuban' (Cromileptes altivelis [female] x Epinephelus fuscoguttatus [male]) has shown promising performance in aquaculture trials, yet no complete reference genome has been available for this hybrid. We generated two gapless, telomere-to-telomere (T2T) haplotype-resolved genome assemblies of a single individual by integrating short-read, PacBio HiFi, Oxford Nanopore ultralong-read and Hi-C data. The maternal (Yushu_Calti_1.0) and paternal (Yushu_Efusc_1.0) haplotypes are 1,077.33 Mb and 1,083.36 Mb in length, with N50 values of 45.46 Mb and 45.55 Mb, respectively. Across all platforms, over 99.4% of reads mapped to each assembly, and Merqury-based quality values reached 57.7413 and 59.2068 (PacBio). BUSCO recovered 99.78% and 99.75% of complete core genes. We predicted 27,248 and 27,566 protein-coding genes, of which 98.52% and 99.23% were functionally annotated, and annotated telomeric motifs and repetitive elements (46.12% and 47.18% of each genome). These assemblies fill a gap in grouper genomic resources and provide a foundation for genetic dissection, parental genome comparison and molecular breeding of this hybrid.

genomics↗

bioRxiv2026

Genetically-encoded discovery and development of peptide-macrocycle imaging agents for PD-L1

The unique cell surface composition of tumor cells forms the molecular basis for many targeting and cell-based therapies. Here, we describe the development of novel peptide-based targeting agents for programmed death ligand 1 (PD-L1). Molecular imaging by peptide agents, coupled with therapeutic intervention using the same modality, represents a critical advancement in cancer management. Whole-body PET imaging of PD-L1 expression offers a superior alternative to traditional immuno-histochemistry, making PD-L1 radiodiagnostic imaging a highly sought-after modality. PD-L1 targeting modalities developed for clinical imaging to date can be divided into antibodies, protein domains, and small macrocyclic peptides with fewer than 20 amino acids. The latter modalities can address many challenges seen in antibody-based targeting vectors. All potent PD-L1 targeting peptide modalities reported to date rely extensively on non-canonical amino acids (ncAAs). Here, we report a comprehensive structure-activity relationship (SAR) analysis of a family of macrocycles discovered from an Sx2Cx8Cx2 phage-display library composed entirely of natural amino acids (x represents 19 natural amino acids excluding Cys). Using >10,000 variants in ''focused'' phage-display libraries, we optimized these macrocycles to achieve single-digit-nanomolar potency in protein- and cell-based assays. En route to this optimization, the activity of 216 synthetic macrocycles towards PD-L1 was measured in five distinct assays; two leads have been evaluated by imaging in tumor xenografts in mice, and the X-ray structure of one advanced lead in complex with PD-L1 has been determined at 2.78 [A] resolution. This publication demonstrates the development potential of PD-L1-targeting macrocycles that do not require extensive incorporation of ncAAs and the democratization of discovery by mapping the optimization path to single-digit-nanomolar assets for targeted radiopharmaceuticals via canonical phage-display technology.

pharmacology and toxicology↗

bioRxiv2026

Long-timescale dynamics shape visual conscious awareness

Consciousness is mostly studied as if it were composed of independent snapshots, aggregating reports over trials and experimental contexts, disregarding any temporal aspect. However, almost nothing is known about how conscious experience spontaneously fluctuates in time. To shed light on the temporal dynamics of conscious awareness, we evaluated the temporal autocorrelation of subjective visibility/confidence reports and objective performance across 20 datasets (N= 335). Two widely used measures of consciousness dissociate in temporal autocorrelation under full spatial attention: subjective measures followed an exponential decay function with long timescales (> 5s), whereas objective accuracy exhibited a slow linear decay function. But both measures share a common underlying temporal fluctuation dynamics, suggesting that the strong autocorrelation in subjective measures cannot be fully attributed to response bias or criterion shift, but might reflect a genuinely aperiodic fluctuation of conscious awareness. Causal transcranial magnetic stimulation (TMS) suggests that this temporal dependency of subjective measures is read out in the dorsolateral prefrontal cortex (DLPFC), where a similarly long neural timescale has been demonstrated. Together, these findings establish a temporal constraint for neural models of conscious access: candidate mechanisms should explain not only whether a stimulus becomes consciously accessible, but also how the probability of conscious access evolves over time.

neuroscience↗

bioRxiv2026

A patient-centric therapeutic paradigm uncouples prostate cancer suppression from systemic metabolic collapse

The clinical benefits of cancer therapies are often compromised by the tolerable adverse effects that impair systemic organismal health and may evolve into latent life threats. Here, we identified profound abiraterone-induced but androgen-independent metabolic perturbations in prostate cancer patients and developed Lifehug-9892 to balance tumor therapy with systemic metabolic homeostasis. By integrating population cohorts with high-resolution metabolomics, we demonstrate that abiraterone induces profound systemic lipidomic dysregulation, characterized by the massive, pathological accumulation of desmosterol. Abiraterone inhibits but stabilizes DHCR24, leading to a metabolic trap in patients showing elevated levels of both desmosterol and cholesterol. Desmosterol accumulation is highly lipotoxic, potently triggering endothelial cell senescence and necrosis, macrophage foam cell formation, murine atherosclerosis, and hepatic senescence. To mechanistically uncouple and therapeutically rescue this systemic metabolic collapse, Lifehug-9892 was rationally designed to selectively retain on-target CYP17A1 inhibition while completely sparing DHCR24 function. Lifehug-9892 maintains potent tumor-suppressive activity while fully preserving the desmosterol-cholesterol metabolic axis and preventing systemic cardiovascular and hepatic damage. Our study uncovers a critical mechanistic link between drug-induced metabolic dysregulation and organismal health in cancer patients, providing a biochemical framework for developing patient-centric targeted therapies that preserve host homeostasis.

cancer biology↗

bioRxiv2026

CD3, CD28, TCRαβ expression and IL-2 production in a spontaneous glycosylphosphatidylinositol-deficient Jurkat T cell line

Glycosylphosphatidylinositol (GPI) anchors are involved in the organization of membrane microdomains that support T cell receptor (TCR) signaling. However, their role in regulating expression of TCR-related proteins and downstream functional output remains unclear. This study aimed to characterize the effects of GPI-deficiency on TCR, cluster of differentiation 3 (CD3), and CD28 expression as well as interleukin-2 (IL-2) production using a GPI-deficient Jurkat T cell line (S12). Flow cytometry confirmed the complete loss of GPI anchors and GPI-anchored proteins (GPI-APs) in the S12 cell line. Compared to GPI-producing parental Jurkat, S12 had significantly higher expression of CD3 and TCR{beta} while CD28 had similar expression. IL-2 production by S12 was assessed following stimulation with anti-CD3/anti-CD28 beads and following stimulation with phorbol 12-myristate 13-acetate (PMA) and ionomycin. Neither S12 nor parental Jurkat produced detectable IL-2 in response to anti-CD3/anti-CD28 bead-mediated stimulation. Both parental Jurkat and S12 produced IL-2 following PMA/ionomycin-mediated stimulation. No significant difference in IL-2 production was observed between S12 and parental Jurkat following PMA/ionomycin-mediated stimulation. These findings demonstrate that GPI-deficiency influences surface receptor expression but does not significantly impair downstream IL-2 production under PMA/ionomycin stimulation. This finding suggests that GPI anchors and GPI-APs contribute to proximal signaling organization but are not required for cytokine production when downstream pathways are directly activated.

immunology↗

bioRxiv2026

CWF19L2 couples pre-mRNA alternative splicing with the maternal-to-zygotic transition to safeguard female fertility

The maternal-to-zygotic transition (MZT) requires precise spatiotemporal execution of pre-mRNA alternative splicing (AS), yet the core splicing machinery driving this developmental reprogramming remains incompletely understood. Here, we identify the CWF19-like protein 2 (CWF19L2) as an indispensable pre-mRNA AS regulator that safeguards against oocyte and early embryo competence defects (OECD). While murine germline-specific depletion of Cwf19l2 spares morphological folliculogenesis, oocyte maturation, or fertilization, it induces complete female sterility characterized by profound developmental arrest at the 2-cell stage. Mechanistically, maternal deficiency of CWF19L2 localized to nuclear speckles disrupts transcription-splicing-translation coupling, collapsing AS homeostasis during maternal reserves and zygotic genome activation. We further demonstrate that CWF19L2 orchestrates the pre-mRNA splicing network through directly binding to target transcripts and indirectly modulating via interacting with the core spliceosomal factor PRPF8. Importantly, exogenous Cwf19l2 mRNA partially rescues the embryonic arrest. Together, our findings establish CWF19L2 as an indispensable AS engine during the MZT, providing a mechanistic foundation for OECD and a novel molecular etiology for female infertility.

Cell Biology↗

bioRxiv2026

AutoZyme: An Autonomous Agentic Framework to Optimize Bioinformatics Software

Performance bottlenecks in widely used genomics and bioinformatics software present a substantial and growing burden as biological datasets continue to increase in size and number. Relieving these bottlenecks relies largely on expert manual optimization and therefore remains difficult to scale. Here we present AutoZyme, an agentic framework for scientific software optimization. Given a target function, AutoZyme builds benchmarks, identifies bottlenecks, and iteratively tests code changes, retaining only those that improve runtime while preserving output. We evaluated AutoZyme on 45 functions, improving runtime without substantial memory increases in over 95% of cases considered. Across 38 functions from Seurat, Scanpy and related packages in genomics and bioinformatics, AutoZyme reduced runtime by a median of 8.52-fold, with the largest reductions exceeding 676-fold. The optimized functions are distributed through AutoZyme-Library as drop-in replacements for existing analysis pipelines. We also release AutoZyme as a reusable framework for optimizing additional user-specified packages and functions.

bioinformatics↗

bioRxiv2026

Luminance-corrected Pupillometry for Reliable Effort-tracking in Dynamic Environments

Pupillometry provides an objective way to index effort across domains. However, pupil size is strongly affected by luminance changes, which can obscure effort-related effects, and limit its use in most applied scenarios with dynamic visual input. We here introduce and validate a method to overcome this problem. To this end, participants performed an auditory n-back task of differing difficulty while viewing either constant visual input or dynamic driving movie clips. Effort was assessed physiologically (pupil size), behaviorally (accuracy), and subjectively (NASA-TLX). Accuracy, questionnaire scores, and pupil size were analyzed at the session level, while pupillometry additionally provided continuous time-resolved information. As expected, pupillometry tracked differences in effort, but its discriminability was substantially reduced under dynamic visual input. Correcting for the effects of overall luminance and moment-to-moment luminance changes using a dynamic, explainable, and open-source modeling procedure (Open-DPSM) considerably improved effort discriminability on both aggregate and time-resolved levels. At the aggregate level, luminance-corrected pupillometry slightly outperformed accuracy and NASA-TLX. Combining all three measures yielded the highest classification performance (AUC = 0.98), supporting the view that effort is multifaceted and best captured multimodally. These findings establish a practical basis for fine-grained physiological tracking of effort and arousal in both fundamental and applied research using complex, dynamic stimuli. A tutorial section guides researchers in applying luminance correction to their own pupillometric data in dynamic viewing environments using the here validated approach.

neuroscience↗

bioRxiv2026

SOX8-USP7-PGC-1α axis enhances thermogenesis in brown adipocytes

Obesity is one of the most prevalent diseases worldwide. Increasing thermogenesis to enhance energy expenditure has emerged as a promising therapeutic strategy. In an effort to identify new regulatory targets in thermogenic adipocytes, we found that SOX8 is correlated with obesity and serves as a novel marker of classical brown adipocytes in both humans and mice, upregulating during acute cold exposure. Functional studies further demonstrated that adipocyte-specific knockdown of SOX8 leads to obesity and metabolic dysfunction in mice. Mechanistically, SOX8 directly interacts with USP7 and stabilizes PGC-1 by reducing its K48-linked polyubiquitination. AAV-Rec2-mediated SOX8 overexpression initially enhanced energy expenditure, improved insulin sensitivity, and alleviated metabolic dysfunction in HFD-fed mice. However, prolonged SOX8 overexpression induced compensatory metabolic maladaptation, characterized by reduced energy expenditure, impaired glucose homeostasis, and mitochondrial structural disruption. These findings reveal a novel SOX8-USP7-PGC-1 regulatory axis in brown adipocytes, and reveal a previously unrecognized time-dependent effect of sustained thermogenic activation, highlighting SOX8 as a promising therapeutic target for obesity and metabolic syndrome.

cell biology↗

bioRxiv2026

Joint enzyme-reaction retrieval and catalytic optima prediction via multimodal fusion

MotivationEnzyme-reaction retrieval is increasingly used to prioritize candidate biocatalysts for experimental follow-up, where useful recommendations should indicate not only whether an enzyme can catalyze a target reaction but also under which pH and temperature conditions it should be tested. Existing retrieval models optimize catalytic matching scores, whereas catalytic optima predictors are typically developed as enzyme-level regressors because public pH and temperature annotations are sparse and often available only at the enzyme or EC-associated record level. This separation leaves a practical gap: high-ranking enzyme-reaction pairs are not evaluated for condition suitability, and enzyme-level optima predictions do not use the reaction context being retrieved. ResultsWe present GERO, a multimodal fusion framework that uses feature-gated cross-modal fusion to integrate global enzyme sequence semantics, sequence-derived pocket geometry, and molecular reaction representations for condition-aware enzyme-reaction retrieval and catalytic optima estimation with reaction context. To evaluate this setting, we define the tolerance-restricted hit rate (Hit@k-TR), which requires both top-k retrieval of the correct candidate and condition prediction within predefined tolerances. Across enzyme- and reaction-similarity splits, GERO improves Hit@k-TR over two-stage retrieval-then-prediction baselines. Representative benchmark examples and an iodinin biosynthesis case study further illustrate GEROs ability to provide candidate rankings together with plausible assay-condition estimates for downstream experimental prioritization. Availability and implementationSource code is available at https://github.com/ykxhs/GERO. Contactliujuan@whu.edu.cn Supplementary informationSupplementary data are available at XXXX online.

bioinformatics↗