Biology subjects

Jeong, K.

Publications and source records attributed to Jeong, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Inhaled black carbon induces depressive-like behavior and enhances stress-related blood-brain molecular vulnerability in mice

Black carbon (BC), a combustion-derived component of fine particulate matter, has been linked to depressive symptoms, but controlled experimental evidence remains limited. We established a controlled BC inhalation model combined with chronic restraint stress (CRS) to determine whether inhaled BC alone induces depressive-like behavior and whether concurrent stress enhances behavioral and molecular vulnerability. Male C57BL/6J mice were assigned to Control, CRS, BC, or BC+CRS groups and exposed for 21 consecutive days, followed by behavioral testing and molecular analyses of plasma-depleted whole blood and stress-related brain regions. BC exposure alone induced depressive-like behavior, and the combined BC+CRS condition showed the most pronounced phenotype. These findings indicate that inhaled BC is sufficient to influence stress-relevant behavior and may heighten vulnerability under chronic stress. At the molecular level, BC shifted peripheral responses toward a stress- and inflammation-associated state with reduced plasticity-related signaling, whereas CRS preferentially engaged glucocorticoid-responsive regulation. Combined BC+CRS exposure further altered plasticity- and transcription-related regulatory programs in blood and stress-related brain regions, with prominent changes in the nucleus accumbens. These condition-dependent molecular patterns suggest that BC engages blood-brain stress-related pathways in a context- and region-specific manner. Together, these findings identify inhaled BC as a neurobehaviorally relevant environmental hazard.

neuroscience↗

bioRxiv2026

Metabolic signals regulate resuscitation speed of antibiotic persister bacteria during infection

All living organisms adjust their metabolism in response to environmental changes. Under unfavorable conditions, organisms enter a state of dormancy by halting metabolism, enabling survival. Dormant bacteria become highly tolerant to antibiotics-a phenomenon called persistence. Here, we demonstrate that selective metabolic reprogramming controls the resuscitation speed of persister after antibiotic exposure. Using multi-omics and in silico modeling, we found that dormant bacteria reprogram metabolic pathways to modulate persister awakening. Accumulation of L-serine and reduction of arginine drive rapid resuscitation. L-serine promotes cysteine biosynthesis and motility while reducing energy metabolism to facilitate rapid resuscitation. In contrast, arginine slows regrowth from dormancy by enhancing ethanol-aldehyde and energy metabolism. L-serine and arginine can, respectively, promote or inhibit the regrowth of antibiotic persister cells in macrophages and mouse models, and regulate the awakening speed of Salmonella, E. coli, and methicillin-resistant Staphylococcus aureus (MRSA). These findings suggest new strategies to target chronic bacterial infections. TeaserL-serine speeds and arginine slows the awakening of antibiotic persisters, revealing targets for chronic infection.

microbiology↗

bioRxiv2026

Lymph Node Dissection and Radiation in the Rat Popliteal Region Leads to Progressive Lymphatic Pump Failure and Lymphedema

BackgroundLymphedema, a chronic and incurable condition with limited therapeutic options, has limited options to quantitatively assess functional changes during its development; as a result, a deeper understanding of its pathophysiology remains hindered. To characterize lymphatic alterations and their association with disease pathology in a clinically relevant model in the rat, we developed a longitudinal iPhone-based volumetry method combined with non-invasive NIR analysis of lymphatic function. Material and methodsSecondary lymphedema was induced by surgery and single-dose irradiation. iPhone volumetry provided longitudinal measurements of hindlimb volume, while NIR imaging quantified the pumping function of major lymphatic vessels in the popliteal area. ResultsAmong 30 rats, lymphedema developed in 80%, defined as interlimb volume differences exceeding 5% and persisting through 14 days. In all rats with lymphedema, disease persisted until the end of the study at postoperative day 42 (P = 0.0015). NIR imaging revealed lymphatic dilation, dye extravasation, and lymphangiogenesis in affected limbs. Lymphatics in limbs with lymphedema exhibited increased contraction frequency, reduced amplitude, and diminished transport compared to baseline and contralateral controls (all P < 0.05). In contrast, rats that did no develop lymphedema showed no postoperative functional changes, although at baseline they displayed higher frequency and lower amplitude and transport compared with LE rats (all P < 0.001). Baseline transport values correlated negatively with swelling (r = -0.44, P = 0.002), as determined by ROC analysis, which yielded an AUC of 0.83, a sensitivity of 83.3%, and a specificity of 82.6%. Histopathology at day 42 confirmed significant dermal thickening and fat deposition in LE limbs (P < 0.001 and P = 0.002, respectively). ConclusionLongitudinal volumetry and NIR imaging applied to a clinically relevant animal model suggest a strong association between swelling and lymphatic function, which could provide deeper insight into lymphedema pathophysiology and represent valuable tools for future research and therapeutic development.

bioinformatics↗

bioRxiv2026

scUnify: A Unified Framework for Zero-shot Inference of Single-Cell Foundation Models

Single-cell foundation models (scFMs) differ in software requirements and performance across downstream tasks and adaptation strategies, complicating comparison and reuse. We present scUnify, a framework that preserves each backbone's required processing while separating model-specific trainers, downstream tasks, and adaptation strategies as reusable components. Across five scFMs, scUnify reproduced original inference and training workflows, extended model-native tasks with multiple parameter-efficient fine-tuning methods, and demonstrated extensibility by connecting a newly implemented custom trainable task to multiple backbones and adaptation strategies. Together, these capabilities enable researchers to systematically compare these combinations and extend custom tasks across heterogeneous scFMs within a common workflow.

bioinformatics↗

bioRxiv2025

MdBRC1 and MdFT2 Interaction Fine-Tunes Bud Break Regulation in Apple

Winter bud dormancy is a critical adaptive process in temperate fruit trees, safeguarding meristems from freezing temperatures and aligning growth with seasonal cues. Dormancy encompasses two primary phases: endodormancy, where internal signals, particularly elevated abscisic acid (ABA), block growth and necessitate chilling for release; and ecodormancy, where buds regain growth competence but remain quiescent until external conditions are favourable. In apple (Malus domestica), we demonstrated that BRANCHED1 (MdBRC1) serves as a central inhibitor of bud growth specifically during ecodormancy. In many plant species, BRC1-like transcription factors integrate environmental and hormonal signals, activating gene networks linked to growth repression, notably those involved in ABA biosynthesis and signalling. Gain-of-function studies in poplar confirmed that MdBRC1 robustly suppresses shoot growth in trees. Our comparative transcriptomic analyses revealed that MdBRC1 directly regulates a suite of dormancy-associated genes, reinforcing its role as a molecular brake on bud break. Importantly, we show that the apple gene FLOWERING LOCUS T2 (MdFT2) is transcriptionally upregulated after dormancy and might act as a key inducer of bud break. Our data reveal that MdFT2 physically interacts with MdBRC1, reducing MdBRC1 activity during ecodormancy. This antagonistic interaction acts as a molecular switch, facilitating the transition from ecodormancy to active bud growth as spring approaches. Together, these findings uncover a regulatory module that finely tunes bud break timing in apple trees and provide a foundation for breeding strategies to enhance fruit tree resilience and adaptability in the context of climate change.

plant biology↗

bioRxiv2025

Disturbed Flow Induces Reprogramming of Endothelial Cells to Immune-like and Foam Cells under Hypercholesterolemia during Atherogenesis

BackgroundAtherosclerosis occurs preferentially in the arteries exposed to disturbed flow (d-flow), while the stable flow (s-flow) regions are protected even under hypercholesterolemic conditions. We recently showed that d-flow alone initiates flow-induced reprogramming of endothelial cells (FIRE), including the novel concept of partial endothelial-to-immune-cell-like transition (partial EndIT), but was not validated using a genetic lineage-tracing model. Here, we tested and validated the two-hit hypothesis that d-flow is an initial instigator of partial FIRE but requires hypercholesterolemia to induce a full-blown FIRE and atherosclerotic plaque development. MethodsMice were treated with adeno-associated virus expressing proprotein convertase subtilisin/kexin type 9 and a Western diet to induce hypercholesterolemia and/or partial carotid ligation (PCL) surgery to expose the left common carotid artery (LCA) to d-flow. Single-cell RNA sequencing (scRNA-seq) analysis was performed using cells obtained from the intima and leftover LCAs and the control right common carotid arteries at 2 and 4 weeks post-PCL. Comprehensive immunohistochemical staining was performed on EC-specific confetti mice treated with PCL and hypercholesterolemic conditions at 4 weeks post-PCL to validate endothelial reprogramming. ResultsAtherosclerotic plaques developed by d-flow under hypercholesterolemia at 2 and 4 weeks post-PCL, but not by d-flow or hypercholesterolemia alone, as expected. The scRNA-seq results of 98,553 single cells from 95 mice revealed 25 cell clusters; 5 EC, 3 vascular smooth muscle cell (SMC), 5 macrophage (M{Phi}), and additional fibroblast, T cell, natural killer cell, dendritic cell, neutrophil, and B cell clusters. Our scRNA-seq analyses showed that d-flow under hypercholesterolemia transitioned healthy ECs to full immune-like (EndIT) and, more surprisingly, foam cells (EndFT), in addition to inflammatory and mesenchymal cells (EndMT). Further, EC-derived foam cells shared remarkably similar transcriptomic profiles with foam cells derived from SMCs and M{Phi}s. Comprehensive lineage-tracing studies using immunohistochemical staining of canonical protein and lipid markers in the EC-specific confetti mice clearly demonstrated direct evidence supporting the novel FIRE hypothesis, including EndIT and EndFT, when d-flow was combined with hypercholesterolemia. Further, reanalysis of the publicly available human carotid plaque scRNA-seq and Perturb-seq datasets supported the FIRE hypothesis and a potential mechanistic link between the genes and FIRE. ConclusionWe provide evidence supporting the two-hit hypothesis: ECs in d-flow regions, such as the branching points, are partially reprogrammed, while hypercholesterolemia alone has minimal endothelial reprogramming effects. Under hypercholesterolemia, d-flow fully reprograms arterial ECs, including the novel EndIT and EndFT, in addition to inflammation and EndMT, during atherogenesis. This single-cell atlas provides a crucial roadmap for developing novel mechanistic understanding and therapeutics targeting flow-sensitive genes, proteins, and pathways of atherosclerosis.

cell biology↗

bioRxiv2025

scMILD: Single-cell Multiple Instance Learning for Sample Classification and Associated Subpopulation Discovery

Linking cellular states to clinical phenotypes is a major challenge in single-cell analysis. Here, we present scMILD, a weakly supervised Multiple Instance Learning framework that robustly identifies condition-associated cells using only sample-level labels. After systematically validating scMILDs accuracy through controlled simulations, we applied it to diverse disease datasets, confirming its ability to retrieve known biological signatures. Building on this, our sample-informed analysis of scMILD-identified monocytes in COVID-19 revealed a temporal transition from an early antiviral to a late stress-response state. Furthermore, in a novel cross-disease application, a model trained on COVID-19 successfully stratified Lupus patients and distinguished shared inflammatory states from disease-specific ones. scMILD thus provides a validated and versatile strategy to dissect cellular heterogeneity, bridging single-cell observations with high-level phenotypes.

bioinformatics↗

bioRxiv2024

FAK activity exacerbates disturbed flow-mediated atherosclerosis via VEGFR2-Cbl-NF-κB signaling.

Atherosclerosis develops at predictable sites in the vasculature where branch points and curvatures create non-laminar disturbed flow. This disturbed flow causes vascular inflammation by increased endothelial cell (EC) barrier permeability and the expression of inflammatory genes such as vascular cell adhesion molecule-1 (VCAM-1). Vascular endothelial growth factor receptor 2 (VEGFR2) is important for flow-induced EC inflammation; however, there are still some gaps in the signaling pathway. Focal adhesion kinase (FAK) is a protein tyrosine kinase whose expression has been implicated in flow-mediated signaling in ECs. However, the link between FAK and VEGFR2 in flow-mediated inflammation signaling has remained unelucidated. Here we found that priming of VEGFR2 with VEGF was critical for flow-mediated activation of FAK and NF-kB. Mechanistically, FAK activation triggers tyrosine phosphorylation of Casitas B-lineage lymphoma (CBL; an E3 ubiquitin ligase) that interacts with VEGFR2 under flow conditions. Further, Apoe-/- mice fed a western diet (WD) exhibited increased FAK activity within the atheroprone disturbed flow region of the inner aortic arch compared to the outer arch. Disturbed flow-induced FAK activation is associated with elevated VEGFR2 on the surface of ECs of the inner aortic arch, but not in the outer arch. Taken together, these data suggest that suppression of augmented FAK activity under disturbed flow may prove beneficial in reducing pro-inflammatory signaling of the endothelial layer.

cell biology↗

bioRxiv2024

FAK inhibition suppresses breast cancer progression via DNA methylation-mediated DAB2 gene reactivation

Epigenetic silencing of tumor suppressor genes is one of the main drivers of tumor progression. Without these tumor suppressors to reduce proliferation, tumor cells proliferate unchecked. Focal adhesion kinase (FAK) is a tyrosine kinase which is often upregulated in various tumors and promotes cell proliferation and migration. Recent studies have demonstrated that pharmacological or genetic FAK inhibition can reduce suppressive DNA methylation in vascular cells. Mechanistically, this is through nuclear FAK-mediated ubiquitination and proteasomal degradation of DNA methyltransferase 3A (DNMT3A). Treatment of breast cancer cell lines with FAK inhibitor (FAK-I) was able to reduce both FAK activity and DNMT3A protein expression. Further, global DNA methylation was reduced in breast cancer cell lines treated with FAK-I. This decrease in DNA methylation was correlated with decreased cell proliferation. We further showed that FAK-I reduced DNMT3A expression in breast cancer cells and that treatment with the proteasome inhibitor MG132 prevented loss of DNTM3A protein stability. To identify how FAK-I and DNMT3A loss could reduce breast cancer cell growth we compared RNA sequencing data from breast cancer cells treated with or without FAK-I or in shRNA DNMT3A knockdown. We have identified a potential tumor suppressor, DAB2, as being regulated by the nuclear FAK-DNMT3A axis. DAB2 is often downregulated in cancers and has been shown to play a vital role in switching TGF{beta} signaling from proliferative to apoptotic by altering TGF{beta}RI binding partners. Immunoblotting and immunostaining indeed revealed that FAK-I and shDNMT3A could induce DAB2 protein expression. Further, FAK-I treatment showed efficacy in reducing tumor growth in vivo using the murine 4T1 tumor model. Immunostaining of 4T1 tumors showed FAK-I decreased DNMT3A, DNA methylation (5-methylcytosine, 5-mC), and increased DAB2 expression. Taken together, these data suggest that nuclear FAK-mediated regulation of DNMT3A can alter the epigenetic landscape and induce tumor suppressor gene expression.

cancer biology↗

bioRxiv2024

Analysis of the dynamics of a complex, multipathway reaction: Insulin dimer dissociation

The protein hormone insulin forms a homodimer that must dissociate to bind to its receptor. Understanding the kinetics and mechanism of dissociation is essential for rational design of therapeutic analogs. In addition to its physiological importance, this dissociation process serves as a paradigm for coupled (un)folding and (un)binding. Based on previous free energy simulations, insulin dissociation is thought to involve multiple pathways with comparable free energy barriers. Here, we analyze the mechanism of insulin dimer dissociation using a recently developed computational framework for estimating kinetic statistics from short-trajectory data. These statistics indicate that the likelihood of dissociation (the committor) closely tracks the decrease in the number of (native and nonnative) intermonomer contacts and the increase in the number of water contacts at the dimer interface; the transition state with equal likelihood of association and dissociation corresponds to an encounter complex with relatively few native contacts and many nonnative contacts. We identify four pathways out of the dimer state and quantify their contributions to the rate, as well as their exchange, by computing reactive fluxes. We show that both the pathways and their extents of exchange can be understood in terms of rotations around three axes of the dimer structure. Our results provide insights into the kinetics of insulin analogues and, more generally, how to characterize complex, multipathway processes.

biophysics↗

bioRxiv2024

Lymphatic endothelial cell-targeting lipid nanoparticles delivering VEGFC mRNA improve lymphatic function after injury

Dysfunction of the lymphatic system following injury, disease, or cancer treatment can lead to lymphedema, a debilitating condition with no cure. Advances in targeted therapy have shown promise for treating diseases where conventional therapies have been ineffective and lymphatic vessels have recently emerged as a new therapeutic target. Lipid nanoparticles (LNPs) have emerged as a promising strategy for tissue specific delivery of nucleic acids. Currently, there are no approaches to target LNPs to lymphatic endothelial cells, although it is well established that intradermal (ID) injection of nanoparticles will drain to lymphatics with remarkable efficiency. To design an LNP that would effectively deliver mRNA to LEC after ID delivery, we screened a library of 150 LNPs loaded with a reporter mRNA, for both self-assembly and delivery in vivo to lymphatic endothelial cells (LECs). We identified and validated several LNP formulations optimized for high LEC uptake when administered ID and compared their efficacy for delivery of functional mRNA with that of free mRNA and mRNA delivered with a commercially available MC3-based LNP (Onpattro). The lead LEC-specific LNP was then loaded with VEGFC mRNA to test the therapeutic advantage of the LEC-specific LNP (namely, LNP7) for treating a mouse tail lymphatic injury model. A single dose of VEGFC mRNA delivered via LNP7 resulted in enhanced LEC proliferation at the site of injury, and an increase in lymphatic function up to 14-days post-surgery. Our results suggest a therapeutic potential of VEGFC mRNA lymphatic-specific targeted delivery in alleviating lymphatic dysfunction observed during lymphatic injury and could provide a promising approach for targeted, transient lymphangiogenic therapy. One Sentence SummaryDevelopment of a novel lymphatic endothelial cell-targeting lipid nanoparticle via in vivo screening for mRNA delivery improves lymphatic regeneration and function after injury.

bioengineering↗

bioRxiv2023

DHCR24-mediated sterol homeostasis during spermatogenesis is required for sperm mitochondrial sheath formation and impacts male fertility over time

Desmosterol and cholesterol are essential lipid components of the sperm plasma membrane. Cholesterol efflux is required for capacitation, a process through which sperm acquire fertilizing ability. In this study, using a transgenic mouse model overexpressing 24-dehydrocholesterol reductase (DHCR24), an enzyme in the sterol biosynthesis pathway responsible for the conversion of desmosterol to cholesterol, we show that disruption of sterol homeostasis during spermatogenesis led to defective sperm morphology characterized by incomplete mitochondrial packing in the midpiece, reduced sperm count and motility, and a decline in male fertility with increasing paternal age, without changes in body fat composition. Sperm depleted of desmosterol exhibit inefficiency in the acrosome reaction, metabolic dysfunction, and an inability to fertilize the egg. These findings provide molecular insights into sterol homeostasis for sperm capacitation and its impact on male fertility.

cell biology↗

bioRxiv2023

A mouse model of ZTTK syndrome reveals indispensable SON functions in organ development and hematopoiesis

Rare diseases are underrepresented in biomedical research, leading to insufficient awareness. Zhu-Tokita-Takenouchi-Kim (ZTTK) syndrome is a rare disease caused by genetic alterations that result in heterozygous loss-of-function of SON. While ZTTK syndrome patients suffer from numerous symptoms, the lack of model organisms hamper our understanding of both SON and this complex syndrome. Here, we developed Son haploinsufficiency (Son+/-) mice as a model of ZTTK syndrome and identified the indispensable roles of Son in organ development and hematopoiesis. Son+/- mice recapitulated clinical symptoms of ZTTK syndrome, including growth retardation, cognitive impairment, skeletal abnormalities, and kidney agenesis. Furthermore, we identified hematopoietic abnormalities in Son+/- mice, similar to those observed in human patients. Surface marker analyses and single-cell transcriptome profiling of hematopoietic stem and progenitor cells revealed that Son haploinsufficiency inclines cell fate toward the myeloid lineage but compromises lymphoid lineage development by reducing key genes required for lymphoid and B cell lineage specification. Additionally, Son haploinsufficiency causes inappropriate activation of erythroid genes and impaired erythroid maturation. These findings highlight the importance of the full gene dosage of Son in organ development and hematopoiesis. Our model serves as an invaluable research tool for this rare disease and related disorders associated with SON dysfunction.

genetics↗

bioRxiv2023

FLASHQuant: a fast algorithm for proteoform quantification in top-down proteomics

Liquid chromatography-mass spectrometry (LC-MS) based top-down proteomics (TDP) is an essential method for the analysis of intact proteoforms. The accurate quantification of individual proteoforms is a crucial step in identifying proteome-wide alterations in different biological conditions. Label-free quantification (LFQ) is the most common method for proteoform quantification as it requires no additional costly labeling. In TDP, due to frequent co-elution and complex signal structures, overlapping signals deriving from multiple proteoforms complicate accurate quantification. Here, we introduce FLASHQuant for MS1-level LFQ analysis in TDP, which is capable of automatically resolving and quantifying co-eluting proteoforms. FLASHQuant performs highly accurate and reproducible quantification in short runtimes of just a few minutes per LC-MS run. To validate the proteoforms reported by FLASHQuant, we evaluated them with identified proteoforms confirmed by tandem mass spectrometry, which showed high match rates. FLASHQuant is publicly available as platform-independent open-source software at https://openms.org/flashquant/.

bioinformatics↗

bioRxiv2023

MASH Native: A Unified Solution for Native Top-Down Proteomics Data Processing

Native top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking. Herein, we have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a one-stop shop for characterizing both native protein complexes and proteoforms. The MASH Native app, video tutorials, written tutorials and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHNativeSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file.

bioinformatics↗

bioRxiv2022

Expression profiles of hypoxia-related genes of cancers originating from anatomically similar locations using TCGA database analysis

Hypoxia is a well-recognized characteristic of the tumor microenvironment of solid cancers. This study aimed to analyze hypoxia-related genes shared by groups based on tumor location. Nine hypoxia-related pathways from the Kyoto Encyclopedia of Genes and Genomes database or the Reactome database were selected, and 850 hypoxia-related genes were analyzed. Based on their anatomical locations, 14 tumor types were categorized into the following six groups. The group-specific genetic risk score was classified as high or low risk based on mRNA expression, and survival outcomes were evaluated. The risk scores in the Female reproductive group and Lung group were internally and externally validated. In the Female reproductive group, CDKN2A, FN1 and ITGA5, were identified as hub genes associated with poor prognosis, while IL2RB and LEF1 were associated with favorable prognosis. In the Lung group, ITGB1 and LDHA were associated with poor prognosis, and GLS2 was associated with favorable prognosis. Functional enrichment analysis showed that the Female reproductive group was enriched in terms related to cilia and skin, while the Lung group was enriched in terms related to cytokines and defense. This analysis may lead to better understanding of the mechanisms of cancer progression and facilitate establishing new biomarkers for prognosis prediction.

bioinformatics↗

bioRxiv2021

FLASHIda: Intelligent data acquisition for top-down proteomics that doubles proteoform level identification count

Top-down proteomics (TDP) has gained a lot of interest in biomedical application for detailed analysis and structural characterization of proteoforms. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complex signal of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. We present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In analysis in E. coli lysates, FLASHIda increased the number of unique proteoform level identifications from 800 to 1,500, or generated a near-identical number of identifications in [1/3] of instrument time when compared to standard DDA mode. Furthermore, FLASHIda enabled sensitive mapping of post translational modifications and detection of chemical adducts. As an extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates.

bioinformatics↗

bioRxiv2019

FLASHDeconv: Ultrafast, high-quality feature deconvolution for top-down proteomics

Feature deconvolution, the determination of intact proteoform masses, is crucial for top-down proteomics, but currently suffers from long runtimes and quality issues. We present FLASHDeconv, an algorithm based on a simple transformation of mass spectra, which turns deconvolution into the search for constant patterns thus greatly accelerating the process. We show higher deconvolution quality and two to three orders of magnitude faster execution speed than existing approaches.

bioinformatics↗