Biology subjects

Lu, J.

Publications and source records attributed to Lu, J..

At least 19 recordsLinked to original sources

bioRxiv2018

Identifying Emerging Phenomenon in Plant Long Temporal Phenotyping Experiments

The rapid improvement of phenotyping capability, accuracy, and throughput have greatly increased the volume and diversity of phenomics data. A remaining challenge is an efficient way to identify phenotypic patterns to improve our understanding of the quantitative variation of complex phenotypes, and to attribute gene functions. To address this challenge, we developed a new algorithm to identify emerging phenomena from large-scale temporal plant phenotyping experiments. An emerging phenomenon is defined as a group of genotypes who exhibit a coherent phenotype pattern during a relatively short time. Emerging phenomena are highly transient and diverse, and are dependent in complex ways on both environmental conditions and development. Identifying emerging phenomena may help biologists to examine potential relationships among phenotypes and genotypes in a genetically diverse population and to associate such relationships with the change of environments or development. We present an emerging phenomenon identification tool called Temporal Emerging Phenomenon Finder (TEP-Finder). Using large-scale longitudinal phenomics data as input, TEP-Finder first encodes the complicated phenotypic patterns into a dynamic phenotype network. Then, emerging phenomena in different temporal scales are identified from dynamic phenotype network using a maximal clique based approach. Meanwhile, a directed acyclic network of emerging phenomena is composed to model the relationships among the emerging phenomena. The experiment that compares TEP-Finder with two state-of-art algorithms shows that the emerging phenomena identified by TEP-Finder are more functionally specific, robust, and biologically significant. The source code, manual, and sample data of TEP-Finder are all available at: http://phenomics.uky.edu/TEP-Finder/.

bioinformatics↗

bioRxiv2018

HiAlc Klebsiella pneumonia, one of potential chief culprits of non-alcoholic fatty liver disease: through generation of endogenous ethanol

Non-alcoholic fatty liver disease (NAFLD), a prelude of cirrhosis and hepatocellular carcinoma, is the most common chronic liver disease worldwide. NAFLD has been considerated to be associated with the composition of gut microbiota. However, causal relationship between change of gut microbiome and NAFLD remains unclear. Here we show that Klebsiella pneumoniae was significantly associated with NAFLD through inducing generation of endogenous ethanol. A strain of high alcohol-producing Klebsiella pneumoniae (HiAlc Kpn) was initially isolated from fecal samples of patient with non-alcoholic steatohepatitis (NASH) accompanied with auto-brewery syndrome (ABS). Gavage of HiAlc Kpn was capable of inducing murine model of fatty liver disease (FLD) in which had typical pathological changes of hepatic steatosis and similar liver gene expression profiles to those of alcohol intake in mice. Data derived from germ-free mice by gnotobiotic gavage further demonstrated that the HiAlc Kpn is the major cause of the changes in FLD mice. Furthermore, using proteomic and metabolitic analysis, we found that HiAlc Kpn induced generation of endogenous alcohol through the 2,3-butanediol fermentation pathway. More interestingly, the blood alcohol concentration was elevated in FLD mice induced by HiAlc Kpn after glucose intake. Clinical analysis showed that HiAlc Kpn were observed in up to 60% of patients with NAFLD. Our results suggested that HiAlc Kpn make important contribution to NAFLD, possibly through generation of the endogenous alcohol. Thus, targeting these bacteria might provide a novel therapeutic for clinical treatment of NAFLD.\n\nIn BriefFatty liver disease induced by high alcohol-producing Klebsiella pneumoniae\n\nCompeting Financial Interest StatementThe authors declare no conflicts of interest.

microbiology↗

bioRxiv2018

Novel diamond shuttle to deliver flexible bioelectronics with reduced tissue compression

The ability to deliver flexible biosensors through the toughest membranes of the central and peripheral nervous system is an important challenge in neuroscience and neural engineering. Bioelectronic devices implanted through dura mater and thick epineurium would ideally create minimal compression and acute damage as they reach the neurons of interest. We demonstrate that a three-dimensional diamond shuttle can be easily made with a vertical support to deliver ultra-compliant polymer microelectrodes (4.5 m thick) in-vivo through dura mater and thick epineurium. The diamond shuttle has 54% less cross-sectional area than an equivalently stiff silicon shuttle, which we simulated will result in a 37% reduction in blood vessel damage. We also discovered that higher frequency oscillation of the shuttle (200 Hz) significantly reduced tissue compression regardless of the insertion speed, while slow speeds also independently reduced tissue compression. Insertion and recording performance are demonstrated in rat and feline models, but the large design space of these tools are suitable for research in a variety of animal models and nervous system targets.

bioengineering↗

bioRxiv2018

Central carbon metabolism is an intrinsic factor for optimal replication of a norovirus

The metabolic pathways of central carbon metabolism, glycolysis and oxidative phosphorylation (OXPHOS), are important host factors that determine the outcome of viral infections and can therefore be manipulated by some viruses to favor infection. However, mechanisms of metabolic modulation and their effects on viral replication vary widely. Herein, we present the first metabolomics profile of norovirus-infected cells, which revealed increases in glycolysis, OXPHOS, and the pentose phosphate pathway (PPP) during murine norovirus infection. Inhibiting glycolysis with 2-deoxyglucose (2DG) in transformed and primary macrophages revealed that host cell metabolism is an important factor for optimal murine norovirus (MNV) infection. 2DG affected an early stage in the viral life cycle after viral uptake and capsid uncoating, leading to decreased levels of viral protein translation and viral RNA replication. The requirement of central carbon metabolism was specific for MNV (but not astrovirus) infection, independent of the Type I interferon antiviral response, and unlikely to be due to a lack of host cell nucleotide synthesis. MNV infection increased activation of the protein kinase Akt, but not AMPK, two master regulators of cellular metabolism, suggesting Akt signaling may play a role in upregulating central carbon metabolism during norovirus infection. In conclusion, our findings suggest that the metabolic state of target cells is an intrinsic host factor that determines the extent of norovirus replication and implicates metabolism as a virulence determinant. They further implicate cellular metabolism as a novel therapeutic target for norovirus infections and improvements of current human norovirus culture systems.\n\nIMPORTANCEViruses depend on the host cells they infect to provide the machinery and substrates for replication. Host cells are highly dynamic systems that can alter their intracellular environment and metabolic behavior, which may be helpful or inhibitory for an infecting virus. In this study, we show that macrophages, a target cell of murine norovirus (MNV), increase central carbon metabolism upon viral infection, which is important for early steps in MNV infection. Human noroviruses (hNoV) are a major cause of gastroenteritis globally, causing enormous morbidity and economic burden. Currently, no effective antivirals or vaccines exist for hNoV, mainly due to the lack of high efficiency in vitro culture models for their study. Thus, insights gained from the MNV model may reveal aspects of host cell metabolism that can be targeted for improving hNoV cell culture systems and for developing effective antiviral therapies.

microbiology↗

bioRxiv2018

Single-cell microRNA/mRNA co-sequencing reveals non-genetic heterogeneity and novel regulatory mechanisms

Co-measurement of multiple omic profiles from the same single cells opens up the opportunity to decode molecular regulation that underlie intercellular heterogeneity in development and disease. Here, we present co-sequencing of microRNAs and mRNAs in the same single cells using a half-cell genomics approach. This method demonstrates good robustness (~95% success rate) and reproducibility (R2=0.93 for both miRNAs and mRNAs), and yields paired half-cell miRNA and mRNA profiles that could be independently validated. Linking the level of miRNAs to the expression of predicted target mRNAs across 19 single cells that are phenotypically identical, we observe that the predicted targets are significantly anti-correlated with the variation of abundantly expressed miRNAs, suggesting that miRNA expression variability alone may lead to non-genetic cell-to-cell heterogeneity. Genome-scale analysis of paired miRNA-mRNA co-profiles further allows us to derive and validate new regulatory relationships of cellular pathways controlling miRNA expression and variability.

systems biology↗

bioRxiv2018

Uric acid lowering treatment alleviates perivascular carotid collar placement induced neointimal lesions in Uricase knockout mice

Hyperuricemia (HU) is a cause of gout. Clinical studies show a link between HU and cardiovascular disease. However, the role of soluble serum urate on atherosclerosis development remains elusive. We aimed to use a new HU mouse model (Uricase/Uox knockout (KO)) to further investigate the relationship between HU and atherosclerosis. Mouse model of induced carotid atherosclerosis was established in the novel spontaneous HU Uox-KO mouse and their wild type littermates (C57BL/6J background). Mice were implanted with a perivascular collar placement around the right carotid artery in combination with a western-type diet. To investigate urate-lowering treatment (ULT) effects on intima, the mice were gavaged daily from the age of 6 weeks with allopurinol. Human umbilical vein endothelial cells (HUVECs) were co-incubated with soluble urate, with and without probenecid, to study the mechanism of urate-related atherosclerosis. The Uox-KO mice had significantly elevated serum urate levels combined with higher blood urea nitrogen and serum creatinine. Western blot analysis showed enhanced levels of atherosclerosis inflammatory response proteins. However, there were no other risk indicators for the pathogenesis of atherosclerosis, including increased fasting glucose, altered lipid and atherosclerosis characterized cardiovascular and histological manifestations. In contrast, collar placement Uox-KO mice showed severe neointimal changes in histology staining consistent with increases in intimal area and increases in proliferating cell nuclear antigen (PCNA) - and F4/80-positive cells. Allopurinol reduced neointimal areas induced by the perivascular collar in hyperuricemic mice accompanied by decreased expression of PCNA- and F4/80-positive cells (P< 0.05). ULT alleviated atherosclerosis inflammatory response factors and reactive oxygen species intensities in both collar placement Uox-KO mice and urate-stimulated HUVECs. In vitro results using HUVECs showed ROS was induced by urate and ROS induction was abrogated using antioxidants. These data demonstrate that urate per se does not trigger atherosclerosis intima lesions in mice. Urate worsens carotid neointimal lesions induced by the perivascular collar and urate-lowering therapy partially abrogates the effects. The current study warrants the further human based study on the possible benefits of urate-lowering therapy in atherosclerosis patients with HU.\n\nSummary statementWe generated a carotid collar placement atherosclerosis model in the novel spontaneous HU Uox-KO mouse and demonstrate that urate plays a contributing rather than a causal role in the carotid neointimal lesions, while urate-lowering treatment may bring additional benefits in this HU mouse model.

physiology↗

bioRxiv2018

Delayed differentiation of vaginal and uterine microbiomes in dairy cows developing postpartum endometritis

Bacterial infection of the uterus is a normal event after parturition. While the healthy cow achieves uterine clearance early postpartum, cows unable to control the infection within 21 days after calving develop postpartum endometritis. Studies on the Microbial Ecology of the bovine reproductive tract have focused on either vaginal or uterine microbiomes. This is the first study that compares both microbiomes in the same animals. Terminal Restriction Fragment Length Polymorphism of the 16S rRNA gene showed that despite large differences associated to individuals, a shared community exist in vagina and uterus during the postpartum period. The largest changes associated with development of endometritis were observed at 7 days postpartum, a time when vaginal and uterine microbiomes were most similar. 16S rRNA Pyrosequencing of the vaginal microbiome at 7 days postpartum showed at least three different microbiome types that were associated with postpartum endometritis. All three microbiome types featured reduced bacterial diversity. Taken together, the above findings support a scenario where disruption of the compartmentalization of the reproductive tract during parturition results in the dispersal and mixing of the vaginal and uterine microbiomes, which subsequently are subject to differentiation. This microbial succession is likely associated to early clearance in the healthy cow. In contrast, loss of bacterial diversity and dominance of the microbiome by few bacterial taxa were related to a delayed succession in cows developing endometritis at 7 DPP.

microbiology↗

bioRxiv2018

Inference of Chromosome-length Haplotypes Using Genomic Data of Three to Five Single Gametes

Knowledge of chromosome-length haplotypes will not only advance our understanding of the relationship between DNA and phenotypes, but also promote a variety of genetic applications. Here we present Hapi, an innovative method for chromosomal haplotype inference using only 3 to 5 gametes. Hapi outperformed all existing haploid-based phasing methods in terms of accuracy, reliability, and cost efficiency in both simulated and real gamete datasets. This highly cost-effective phasing method will make large-scale haplotype studies feasible to facilitate human disease studies and plant/animal breeding. In addition, Hapi can detect meiotic crossovers in gametes, which has promise in the diagnosis of abnormal recombination activity in human reproductive cells.

bioinformatics↗

bioRxiv2018

Dual RNAseq of human leprosy lesions identifies bacterial determinants linked to host immune response

To understand how the interaction between an intracellular bacterium and the host immune system contributes to outcome at the site of infection, we studied leprosy, a disease that forms a clinical spectrum, in which progressive infection by the intracellular bacterium Mycobacterium leprae is characterized by the production of type | IFNs and antibody production. We performed dual RNAseq on patient lesions, identifying a continuum of distinct bacterial states that are linked to the host immune response. The bacterial burden, represented by the fraction of bacterial transcripts, correlates with a host type | IFN gene signature, known to inhibit antimicrobial responses. Second, the bacterial transcriptional activity, defined by the bacterial mRNA/rRNA ratio, links bacterial heat shock proteins with the BAFF-BCMA host antibody response pathway. Our findings provide a platform for interrogation of host and pathogen transcriptomes at the site of infection, allowing insight into mechanisms of inflammation in human disease.

microbiology↗

bioRxiv2018

Enterovirus 71 structural viral protein 1 promotes mouse Schwann cell autophagy via endoplasmic reticulum stress-mediated peripheral myelin protein 22 upregulation

Enterovirus 71 (EV71) accounts for the majority of hand, foot and mouth disease-related deaths due to fatal neurological complications. The clinical observations and animal models found the early invasion of nervous system, and the demyelinating phenomenon was observed. As one of the receptors of EV71 structural viral protein 1 (VP1), SCARB2 mainly exists on the myelin sheath. EV71 VP1 can promote viral replication through inducing autophagy in neuron cells. This study aims to investigate the role and mechanism of VP1 in autophagy of mouse Schwann cells (MSCs). An EV71 VP1-expressing vector (pEGFP-C3-VP1) was generated and transfected into MSCs. Transmission electron microscopy (TEM) and Western blot analysis of the autophagy marker microtubule-associated proteins 1A/1B light chain 3B (LC3B) were used to assess autophagy in the cells. Real-time PCR and immunofluorescent staining were performed to determine the expression of PMP22. Small interfering RNA against PMP22 was employed to investigate the role of PMP22 in MSCs autophagy. Selective endoplasmic reticulum (ER) stress inhibitor salubrinal (SAL) was employed to determine whether PMP22 is mediated by ER stress. Our results demonstrated that VP1 played a promotive role in MSC autophagy. Overexpression of VP1 upregulated PMP22. PMP22 deficiency downregulated LC3B and thus inhibited autophagy. Furthermore, PMP22 expression was significantly suppressed by SAL. VP1 promotes MSC autophagy through upregulating ER stress-mediated PMP22 expression. VP1/ER stress/ PMP22 axis in autophagy may be a potential therapeutic target for EV71 infection-induced fatal neuronal damage.

cell biology↗

bioRxiv2018

Response to \"No evidence of functional co-adaptation between clustered microRNAs\"

microRNAs (miRNAs) are a class of endogenously expressed small non-coding RNAs that regulate target genes at the post-transcriptional level. One significant feature of miRNA is that their genomic locations are often clustered together in the genome. In a previous study (Wang, et al. 2016), we proposed a \"functional co-adaptation\" model to explain how clustering helps new miRNAs survive and develop functions during long-term evolution. In a manuscript recently posted at bioRxiv (doi:10.1101/274811), Marco claimed that he re-analyzed our data and came to a different conclusion. However, we found his analyses were conducted in an inappropriate approach. He also claimed that the absence of substitution in highly conserved miRNAs does not support the \"functional co-adaption\" model based on the misunderstanding of our model. In summary, the analyses and claims of Marco, which are flawed, do not refute our model.

evolutionary biology↗

bioRxiv2018

A genetically-encoded fluorescent acetylcholine indicator

Acetylcholine (ACh) regulates a diverse array of physiological processes throughout the body, yet cholinergic transmission in the majority of tissues/organs remains poorly understood due primarily to the limitations of available ACh-monitoring techniques. We developed a family of G-protein-coupled receptor activation-based ACh sensors (GACh) with sensitivity, specificity, signal-to-noise ratio, kinetics and photostability suitable for monitoring ACh signals in vitro and in vivo. GACh sensors were validated with transfection, viral and/or transgenic expression in a dozen types of neuronal and non-neuronal cells prepared from several animal species. In all preparations, GACh sensors selectively responded to exogenous and/or endogenous ACh with robust fluorescence signals that were captured by epifluorescent, confocal and/or two-photon microscopy. Moreover, analysis of endogenous ACh release revealed firing pattern-dependent release and restricted volume transmission, resolving two long-standing questions about central cholinergic transmission. Thus, GACh sensors provide a user-friendly, broadly applicable toolbox for monitoring cholinergic transmission underlying diverse biological processes.

neuroscience↗

bioRxiv2018

MIN1PIPE: A Miniscope 1-photon-based Calcium Imaging Signal Extraction Pipeline

In vivo calcium imaging using 1-photon based miniscope and microendoscopic lens enables studies of neural activities in freely behaving animals. However, the high and fluctuating background, the inevitable movements and distortions of imaging field, and the extensive spatial overlaps of fluorescent signals emitted from imaged neurons inherent in this 1-photon imaging method present major challenges for extracting neuronal signals reliably and automatically from the raw imaging data. Here we develop a unifying algorithm called MINiscope 1-photon imaging PIPEline (MIN1PIPE) that contains several standalone modules and can handle a wide range of imaging conditions and qualities with minimal parameter tuning, and automatically and accurately isolate spatially localized neural signals. We quantitatively compare MIN1PIPE with other existing partial methods using both synthetic and real datasets obtained from different animal models, and show that MIN1PIPE has a superior performance both in terms of efficiency and precision in analyzing noisy miniscope calcium imaging data.

neuroscience↗

bioRxiv2018

MDM4 is an essential disease driver targeted by 1q gain in Burkitt lymphoma

Oncogenic MYC activation promotes cellular proliferation in Burkitt lymphoma (BL), but also induces cell cycle arrest and apoptosis mediated by TP53, a tumor suppressor gene that is mutated in 40% of BL cases. To identify therapeutic targets in BL, we investigated molecular dependencies in BL cell lines using RNAi-based, loss-of-function screening. By integrating genotypic and RNAi data, we identified a number of genotype-specific dependencies including the dependence of TCF3/ID3 mutant cell lines on TCF3 and of MYD88 mutant cell lines on TLR signaling. TP53 wild-type (TP53wt) BL were dependent on MDM4, a negative regulator of TP53. In BL cell lines, MDM4 knockdown induced cell cycle arrest and decreased tumor growth in a xenograft model in a p53-dependent manner, while small molecule inhibition of the MDM4-p53 interaction restored p53 activity resulting in cell cycle arrest. Consistent with the pathogenic effect of MDM4 upregulation in BL, we found that TP53wt BL samples were enriched for gain of chromosome 1q which includes the MDM4 locus. 1q gain was also enriched across non-BL cancer cell lines (n=789) without TP53 mutation (23% in TP53wt and 12% in TP53mut, p<0.001). In a set of 216 cell lines representing 19 cancer entities from the Achilles project, MDM4 was the strongest genetic dependency in TP53wt cell lines (p<0.001).\n\nOur findings show that in TP53wt BL, MDM4-mediated inhibition of p53 is a mechanism to evade cell cycle arrest. The data highlight the critical role of p53 as a tumor suppressor in BL, and identifies MDM4 as a key functional target of 1q gain in a wide range of cancers, which is therapeutically targetable.

cancer biology↗

bioRxiv2018

Minimizing Structural Bias in Single-Molecule Super-Resolution Microscopy

Single-molecule localization microscopy (SMLM) depends on sequential detection and localization of individual molecular blinking events. Due to the stochasticity of single-molecule blinking and the desire to improve SMLMs temporal resolution, algorithms capable of analyzing frames with a high density (HD) of active molecules, or molecules whose images overlap, are a prerequisite for accurate location measurements. Thus far, HD algorithms are evaluated using scalar metrics, such as root-mean-square error, that fail to quantify the structure of errors caused by the structure of the sample. Here, we show that the spatial distribution of localization errors within super-resolved images of biological structures are vectorial in nature, leading to systematic structural biases that severely degrade image resolution. We further demonstrate that the shape of the microscopes point-spread function (PSF) fundamentally affects the characteristics of imaging artifacts. We built a Robust Statistical Estimation algorithm (RoSE) to minimize these biases for arbitrary structures and PSFs. RoSE accomplishes this minimization by estimating the likelihood of blinking events to localize molecules more accurately and eliminate false localizations. Using RoSE, we measure the distance between crossing microtubules, quantify the morphology of and separation between vesicles, and obtain robust recovery using diverse 3D PSFs with unmatched accuracy compared to state-of-the-art algorithms.

bioinformatics↗

bioRxiv2018

Development of a joint evolutionary model for the genome and the epigenome

BackgroundInterspecies epigenome comparisons yielded functional information that cannot be revealed by genome comparison alone, begging for theoretical advances that enable principled analysis approaches. Whereas probabilistic genome evolution models provided theoretical foundation to comparative genomics studies, it remains challenging to extend DNA evolution models to epigenomes.\n\nResultsWe present an effort to develop ab initio evolution models for epigenomes, by explicitly expressing the joint probability of multispecies DNA sequences and histone modifications on homologous genomic regions. This joint probability is modeled as a mixture of four components representing four evolutionary hypotheses, namely dependence and independence of interspecies epigenomic variations to sequence mutations and to sequence insertions and deletions (indels). For model fitting, we implemented a maximum likelihood method by coupling downhill simplex algorithm with dynamic programming. Based on likelihood comparisons, the model can be used to infer whether interspecies epigenomic variations depend on mutation or indels in local genomic sequences. We applied this model to analyze DNase hypersensitive regions and spermatid H3K4me3 ChIP-seq data from human and rhesus macaque. Approximately 5.5% of homologous regions in the genomes exhibited H3K4me3 modification in either species, among which approximately 67% homologous regions exhibited sequence-dependent interspecies H3K4me3 variations. Mutations accounted for less sequence-dependent H3K4me3 variations than indels. Among transposon-mediated indels, ERV1 insertions and L1 insertions were most strongly associated with H3K4me3 gains and losses, respectively.\n\nConclusionThis work initiates a class of probabilistic evolution models that jointly model the genomes and the epigenomes, thus helps to bring evolutionary principles to comparative epigenomic studies.

bioinformatics↗

bioRxiv2018

Non-antibiotic antimicrobial triclosan induces multiple antibiotic resistance through genetic mutation

Antibiotic resistance poses a major threat to public health. Overuse and misuse of antibiotics are generally recognised as the key factors contributing to antibiotic resistance. However, whether non-antibiotic, anti-microbial (NAAM) chemicals can directly induce antibiotic resistance is unclear. We aim to investigate whether the exposure to a NAAM chemical triclosan (TCS) has an impact on inducing antibiotic resistance on Escherichia coli. Here, we report that at a concentration of 0.2 mg/L TCS induces multi-drug resistance in wild-type Escherichia coli after 30-day TCS exposure. The oxidative stress induced by TCS caused genetic mutations in genes such as fabI, frdD, marR, acrR and soxR, and subsequent up-regulation of the transcription of genes encoding beta-lactamase and multi-drug efflux pump, together with down-regulation of genes related to membrane permeability. The findings advance our understanding of the potential role of NAAM chemicals in the dissemination of antibiotic resistance in microbes, and highlights the need for controlling biocide applications.

microbiology↗

bioRxiv2018

A Convenient Non-harm Cervical Spondylosis Intelligent Identity method based on Machine Learning

Cervical spondylosis(CS), a most common orthopedic diseases, is mainly identified by the doctors judgment from the clinical symptoms and cervical change provided by expensive instruments in hospital. Owing to the development of the surface electromyography(sEMG) technique and artificial intelligence, we proposed a convenient non-harm CS intelligent identify method EasiCNCSII, including the sEMG data acquisition and the CS identification. For the convenience and efficiency of data acquisition with the limited testable muscles provided by the sEMG technology, we proposed a data acquisition method based on the relationship between muscle activity pattern, the tendons theory and CS etiology. It is easily performed in less than 20 minutes, even outside the hospital. Faced with the challenge of high-dimension and the weak availability, the 3-tier model EasiAI is developed to intelligently identify CS. The common features and new features are extracted from raw sEMG data in first tier. The EasiRF is proposed in second tier to further reduce the data dimension and improve the performance. With the limited and weakly available data, the gradient boosted regression tree is developed in third tier to effectively identify CS. The EasiAI achieve the best performance with 91.02% in accuracy, 97.14% in sensitivity, and 81.43% in specificity compared with 4 common machine learning classification model, validating the EasiCNCSII effectiveness.

bioinformatics↗