bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive survey of the approaches for pathway analysis using multi-omics data integration
Authors: Maghsoudi Zeynab , Nguyen Ha , Tavakkoli Alireza , Nguyen Tin 
Published: October 2022

AbstractPathway analysis has been widely used to detect pathways and functions associated with complex disease phenotypes. The proliferation of this approach is due to better interpretability of its results and its higher statistical power compared with the gene-level statistics. A plethora of pathway analysis methods that utilize multi-omics setup, rather than just transcriptomics or proteomics, have recently been developed to discover novel pathways and biomarkers. Since multi-omics gives multiple views into the same problem, different approaches are employed in aggregating these views into a comprehensive biological context. As a result, a variety of novel hypotheses regarding disease ideation and treatment targets can be formulated. In this article, we review 32 such pathway analysis methods developed for multi-omics and multi-cohort data. We discuss their availability and implementation, assumptions, supported omics types and databases, pathway analysis techniques and integration strategies. A comprehensive assessment of each method’s practicality, and a thorough discussion of the strengths and drawbacks of each technique will be provided. The main objective of this survey is to provide a thorough examination of existing methods to assist potential users and researchers in selecting suitable tools for their data and analysis purposes, while highlighting outstanding challenges in the field that remain to be addressed for future development.
Multi-modal chemical information reconstruction from images and texts for exploring the near-drug space
Authors: Wang Jie , Shen Zihao , Liao Yichen , Yuan Zhen , Li Shiliang , He Gaoqi , Lan Man , Qian Xuhong , Zhang Kai , Li Honglin 
Published: October 2022

Abstract
Identification of new chemical compounds with desired structural diversity and biological properties plays an essential role in drug discovery, yet the construction of such a potential space with elements of ‘near-drug’ properties is still a challenging task. In this work, we proposed a multimodal chemical information reconstruction system to automatically process, extract and align heterogeneous information from the text descriptions and structural images of chemical patents. Our key innovation lies in a heterogeneous data generator that produces cross-modality training data in the form of text descriptions and Markush structure images, from which a two-branch model with image- and text-processing units can then learn to both recognize heterogeneous chemical entities and simultaneously capture their correspondence. In particular, we have collected chemical structures from ChEMBL database and chemical patents from the European Patent Office and the US Patent and Trademark Office using keywords ‘A61P, compound, structure’ in the years from 2010 to 2020, and generated heterogeneous chemical information datasets with 210K structural images and 7818 annotated text snippets. Based on the reconstructed results and substituent replacement rules, structural libraries of a huge number of near-drug compounds can be generated automatically. In quantitative evaluations, our model can correctly reconstruct 97% of the molecular images into structured format and achieve an F1-score around 97–98% in the recognition of chemical entities, which demonstrated the effectiveness of our model in automatic information extraction from chemical patents, and hopefully transforming them to a user-friendly, structured molecular database enriching the near-drug space to realize the intelligent retrieval technology of chemical knowledge.
CoxMKF: a knockoff filter for high-dimensional mediation analysis with a survival outcome in epigenetic studies
Authors: Tian Peixin , Yao Minhao , Huang Tao , Liu Zhonghua 
Published: October 2022

AbstractMotivationIt is of scientific interest to identify DNA methylation CpG sites that might mediate the effect of an environmental exposure on a survival outcome in high-dimensional mediation analysis. However, there is a lack of powerful statistical methods that can provide a guarantee of false discovery rate (FDR) control in finite-sample settings.ResultsIn this article, we propose a novel method called CoxMKF, which applies aggregation of multiple knockoffs to a Cox proportional hazards model for a survival outcome with high-dimensional mediators. The proposed CoxMKF can achieve FDR control even in finite-sample settings, which is particularly advantageous when the sample size is not large. Moreover, our proposed CoxMKF can overcome the randomness of the unstable model-X knockoffs. Our simulation results show that CoxMKF controls FDR well in finite samples. We further apply CoxMKF to a lung cancer dataset from The Cancer Genome Atlas (TCGA) project with 754 subjects and 365 306 DNA methylation CpG sites, and identify four DNA methylation CpG sites that might mediate the effect of smoking on the overall survival among lung cancer patients.Availability and implementationThe R package CoxMKF is publicly available at https://github.com/MinhaoYaooo/CoxMKF.Supplementary informationSupplementary data are available at Bioinformatics online.
Predictive and prognostic value of different cardiac troponin assays: a nationwide register-based cohort study
Authors: Hasselbalch Rasmus B , Schultz Martin , Schytz Philip A , Kristensen Jonas H , Strandkjær Nina , Pries-Heje Mia , Carlson Nicholas , Schou Morten , Bundgaard Henning , Torp-Pedersen Christian , Iversen Kasper K 
Published: October 2022

Abstract

Aims
Guidelines do not differentiate between the available assays of cardiac troponin (cTn). We compared the prognostic and predictive ability of cTn assays.

Methods and results
This was a nationwide cohort study of patients with acute coronary syndrome (ACS) and ≥ 2 cTn measurements of one of four assays: Roche high-sensitivity cTnT (hs-cTnT), Abbott high sensitivity cTnI (hs-cTnI), Siemens Vista cTnI, and Siemens cTnI Ultra. Data were collected from Danish registries from 2009–18. Peak cTn concentration normalized to the 99th percentile was used. Outcomes were myocardial infarction (MI) during admission, one-year all-cause-, cardiovascular-, and non-cardiovascular mortality. Receiver operating characteristics and logistic regression calculating odds ratios (OR) were used. A total of 90 705 patients were included, of which 20 550 (23%) had MI. Siemens Vista cTnI was the strongest predictor of MI, Area under the curve (auc) 0.93 (95% CI 0.93–0.93). In 1 year 9012 (9.9%) of patients had died. An inverted U-shape relationship was observed between concentration of cTn and all-cause mortality. Hs-cTnT OR 21.3 (95% CI 18.4–24.8) at 2–5 times the 99th percentile and 12.1 (95% CI 10.3–14.1) for concentrations &gt;100 times the 99th percentile. The inverted U-shape relationship was only present for non-cardiovascular mortality. The strongest predictor of cardiovascular mortality was hs-cTnT, OR 11.3 (95% CI 6.4–21.8) at 1–2 times the 99th percentile and 88.8 (95% CI 53.2–163.0) for concentrations &gt;100 times the 99th percentile.

Conclusion
Siemens Vista cTnI was the strongest predictor of MI and hs-cTnT was the strongest predictor of mortality. An inverted U-shape relationship was observed between cTn concentration and non-cardiovascular mortality.
Dynamic trophic shifts in bacterial and eukaryotic communities during the first 30 years of microbial succession following retreat of an Antarctic glacier
Authors: Vimercati Lara , Bueno de Mesquita Clifton P , Johnson Ben W , Mineart Dana , DeForce Emelia , Vimercati Molano Ylenia , Ducklow Hugh , Schmidt Steven K 
Published: October 2022

Abstract
We examined microbial succession along a glacier forefront in the Antarctic Peninsula representing ∼30 years of deglaciation to contrast bacterial and eukaryotic successional dynamics and abiotic drivers of community assembly using sequencing and soil properties. Microbial communities changed most rapidly early along the chronosequence, and co-occurrence network analysis showed the most complex topology at the earliest stage. Initial microbial communities were dominated by microorganisms derived from the glacial environment, whereas later stages hosted a mixed community of taxa associated with soils. Eukaryotes became increasingly dominated by Cercozoa, particularly Vampyrellidae, indicating a previously unappreciated role for cercozoan predators during early stages of primary succession. Chlorophytes and Charophytes (rather than cyanobacteria) were the dominant primary producers and there was a spatio-temporal sequence in which major groups became abundant succeeding from simple ice Chlorophytes to Ochrophytes and Bryophytes. Time since deglaciation and pH were the main abiotic drivers structuring both bacterial and eukaryotic communities. Determinism was the dominant assembly mechanism for Bacteria, while the balance between stochastic/deterministic processes in eukaryotes varied along the distance from the glacier front. This study provides new insights into the unexpected dynamic changes and interactions across multiple trophic groups during primary succession in a rapidly changing polar ecosystem.
Discovery of malathion resistance QTL in Drosophila melanogaster using a bulked phenotyping approach
Authors: Macdonald Stuart J , Long Anthony D 
Published: October 2022

Abstract
Drosophila melanogaster has proved an effective system with which to understand the evolutionary genetics and molecular mechanisms of insecticide resistance. Insecticide use has left signatures of selection in the fly genome, and both functional and quantitative genetic studies in the system have identified genes and variants associated with resistance. Here, we use D. melanogaster and leverage a bulk phenotyping and pooled sequencing “extreme quantitative trait loci” approach to genetically dissect variation in resistance to malathion, an organophosphate insecticide. We resolve 2 quantitative trait loci, one of which implicates allelic variation at the cytochrome P450 gene Cyp6g1, a strong candidate based on previous work. The second shows no overlap with hits from a previous genome-wide association study for malathion resistance, recapitulating other studies showing that different strategies for complex trait dissection in flies can yield apparently different architectures. Notably, we see no genetic signal at the Ace gene. Ace encodes the target of organophosphate insecticide inhibition, and genome-wide association studies have identified strong Ace-linked associations with resistance in flies. The absence of quantitative trait locus implicating Ace here is most likely because our mapping population does not segregate for several of the known functional polymorphisms impacting resistance at Ace, perhaps because our population is derived from flies collected prior to the widespread use of organophosphate insecticides. Our fundamental approach can be an efficient, powerful strategy to dissect genetic variation in resistance traits. Nonetheless, studies seeking to interrogate contemporary insecticide resistance variation may benefit from deriving mapping populations from more recently collected strains.
Assessing single-locus CRISPR/Cas9-based gene drive variants in the mosquito Aedes aegypti via single-generation crosses and modeling
Authors: Reid William , Williams Adeline E , Sanchez-Vargas Irma , Lin Jingyi , Juncu Rucsanda , Olson Ken E , Franz Alexander W E 
Published: October 2022

Abstract
The yellow fever mosquito Aedes aegypti is a major vector of arthropod-borne viruses, including dengue, chikungunya, and Zika viruses. A novel approach to mitigate arboviral infections is to generate mosquitoes refractory to infection by overexpressing antiviral effector molecules. Such an approach requires a mechanism to spread these antiviral effectors through a population, for example, by using CRISPR/Cas9-based gene drive systems. Critical to the design of a single-locus autonomous gene drive is that the selected genomic locus is amenable to both gene drive and appropriate expression of the antiviral effector. In our study, we used reverse engineering to target 2 intergenic genomic loci, which had previously shown to be highly permissive for antiviral effector gene expression, and we further investigated the use of 3 promoters (nanos, β2-tubulin, or zpg) for Cas9 expression. We then quantified the accrual of insertions or deletions (indels) after single-generation crossings, measured maternal effects, and assessed fitness costs associated with various transgenic lines to model the rate of gene drive fixation. Overall, MGDrivE modeling suggested that when an autonomous gene drive is placed into an intergenic locus, the gene drive system will eventually be blocked by the accrual of gene drive blocking resistance alleles and ultimately be lost in the population. Moreover, while genomic locus and promoter selection were critically important for the initial establishment of the autonomous gene drive, it was the fitness of the gene drive line that most strongly influenced the persistence of the gene drive in the simulated population. As such, we propose that when autonomous CRISPR/Cas9-based gene drive systems are anchored in an intergenic locus, they temporarily result in a strong population replacement effect, but as gene drive-blocking indels accrue, the gene drive becomes exhausted due to the fixation of CRISPR resistance alleles.
Identification of stable QTL controlling multiple yield components in a durum × cultivated emmer wheat population under field and greenhouse conditions
Authors: Peters Haugrud Amanda R , Zhang Qijun , Green Andrew J , Xu Steven S , Faris Justin D 
Published: October 2022

Abstract
Crop yield gains are needed to keep pace with a growing global population and decreasing resources to produce food. Cultivated emmer wheat is a progenitor of durum wheat and a useful source of genetic variation for trait improvement in durum. Here, we evaluated a recombinant inbred line population derived from a cross between the North Dakota durum wheat variety Divide and the cultivated emmer wheat accession PI 272527 consisting of 219 lines. The population was evaluated in 3 field environments and 2 greenhouse experiments to identify quantitative trait locus associated with 11 yield-related traits that were expressed in a consistent manner over multiple environments. We identified 27 quantitative trait locus expressed in at least 2 field environments, 17 of which were also expressed under greenhouse conditions. Seven quantitative trait locus regions on chromosomes 1B, 2A, 2B, 3A, 3B, 6A, and 7B had pleiotropic effects on multiple yield-related traits. The previously cloned genes Q and FT-B1, which are known to be associated with development and morphology, were found to consistently be associated with multiple traits across environments. PI 272527 contributed beneficial alleles for quantitative trait locus associated with multiple traits, especially for seed morphology quantitative trait locus on chromosomes 1B, 2B, and 6A. Three recombinant inbred lines with increased grain size and weight compared to Divide were identified and demonstrated the potential for improvement of durum wheat through deployment of beneficial alleles from the cultivated emmer parent. The findings from this study provide knowledge regarding stable and robust quantitative trait locus that breeders can use for improving yield in durum wheat.
Genetic determinants of polygenic prediction accuracy within a population
Authors: Lu Tianyuan , Forgetta Vincenzo , Richards John Brent , Greenwood Celia M T 
Published: October 2022

Abstract
Genomic risk prediction is on the emerging path toward personalized medicine. However, the accuracy of polygenic prediction varies strongly in different individuals. Based on up to 352,277 European ancestry participants in the UK Biobank, we constructed polygenic risk scores for 15 physiological and biochemical quantitative traits. We identified a total of 185 polygenic prediction variability quantitative trait loci for 11 traits by Levene’s test among 254,376 unrelated individuals. We validated the effects of prediction variability quantitative trait loci using an independent test set of 58,927 individuals. For instance, a score aggregating 51 prediction variability quantitative trait locus variants for triglycerides had the strongest Spearman correlation of 0.185 (P-value &lt;1.0 × 10−300) with the squared prediction errors. We found a strong enrichment of complex genetic effects conferred by prediction variability quantitative trait loci compared to risk loci identified in genome-wide association studies, including 89 prediction variability quantitative trait loci exhibiting dominance effects. Incorporation of dominance effects into polygenic risk scores significantly improved polygenic prediction for triglycerides, low-density lipoprotein cholesterol, vitamin D, and platelet. In conclusion, we have discovered and profiled genetic determinants of polygenic prediction variability for 11 quantitative biomarkers. These findings may assist interpretation of genomic risk prediction in various contexts and encourage novel approaches for constructing polygenic risk scores with complex genetic effects.
High temporal resolution Nanopore sequencing dataset of SARS-CoV-2 and host cell RNAs
Authors: Tombácz Dóra , Dörmő Ákos , Gulyás Gábor , Csabai Zsolt , Prazsák István , Kakuk Balázs , Harangozó Ákos , Jankovics István , Dénes Béla , Boldogkői Zsolt 
Published: October 2022

Abstract

Background
Recent studies have disclosed the genome, transcriptome, and epigenetic compositions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the effect of viral infection on gene expression of the host cells. It has been demonstrated that, besides the major canonical transcripts, the viral genome also codes for noncanonical RNA molecules. While the structural characterizations have revealed a detailed transcriptomic architecture of the virus, the kinetic studies provided poor and often misleading results on the dynamics of both the viral and host transcripts due to the low temporal resolution of the infection event and the low virus/cell ratio (multiplicity of infection [MOI] = 0.1) applied for the infection. It has never been tested whether the alteration in the host gene expressions is caused by aging of the cells or by the viral infection.

Findings
In this study, we used Oxford Nanopore's direct cDNA and direct RNA sequencing methods for the generation of a high-coverage, high temporal resolution transcriptomic dataset of SARS-CoV-2 and of the primate host cells, using a high infection titer (MOI = 5). Sixteen sampling time points ranging from 1 to 96 hours with a varying time resolution and 3 biological replicates were used in the experiment. In addition, for each infected sample, corresponding noninfected samples were employed. The raw reads were mapped to the viral and to the host reference genomes, resulting in 49,661,499 mapped reads (54,62 Gbs). The genome of the viral isolate was also sequenced and phylogenetically classified.

Conclusions
This dataset can serve as a valuable resource for profiling the SARS-CoV-2 transcriptome dynamics, the virus–host interactions, and the RNA base modifications. Comparison of expression profiles of the host gene in the virally infected and in noninfected cells at different time points allows making a distinction between the effect of the aging of cells in culture and the viral infection. These data can provide useful information for potential novel gene annotations and can also be used for studying the currently available bioinformatics pipelines.
Feature extraction for margin lines using region growing with a dynamic weight function in a one-point bidirectional path search
Authors: Shin Hyoung-Sub , Li Zhi , Kim Jay J 
Published: October 2022

Abstract
A margin line, defined as the boundary curve of the contact area between a prepared tooth and a dental restoration, considerably influences the end shape of the dental restoration design. Most studies that have extracted margin lines from mesh models representing prepared teeth have faced convergence problems in the path search and therefore pose the inconvenience of specifying multiple input points as intermediate goal points. To overcome these problems, in this study, we propose a bidirectional path-search algorithm using a single input point. First, the algorithm classifies all nodes in a mesh model into a margin or fuzzy region to increase search efficiency. Then, the search starts from one point and proceeds on two paths in opposite directions, using the current node of the opposite path as the temporary goal of the currently searched path. During the search, a dynamic evaluation function that varies weights according to the region type is employed to improve the path convergence. Finally, to increase the practicality of the algorithm, the jagged initial margin line is converted into a smooth spline curve using an energy-minimization function specialized for margin lines. To evaluate the proposed algorithm, margin lines extracted from various types of prepared teeth are demonstrated and compared with those created using some relevant previous works and a commercial dental computer-aided design (CAD) system. The comparison verified that accurate margin lines could be calculated with only one input point using the proposed algorithm. Moreover, the proposed algorithm showed better performance for crown and inlay/only experimental models compared with a commercial dental CAD system under the same conditions.
An improved ant-tracking workflow based on divided-frequency data for fracture detection
Authors: Xie Qinghui , Zhao Chunduan , Rui Zhifeng , Guan Shoujun , Zheng Wenting , Fan Hongche 
Published: October 2022

Abstract
The conventional ant-tracking technique often results in weak transverse continuity or unobvious plane fracture patterns. It also has limited ability to identify small-scale natural fractures. To improve the image quality of fractures, a spectrum decomposition technique has been used in ant-tracking. Although it has achieved good results, it also brings a high workload and judgment difficulty. To solve these issues, we proposed an improved ant-tracking workflow based on frequency filtering to improve the accuracy of fracture detection, in which the tracking was performed on low-, medium- and high-frequency cubes. The workflow was applied in the H area of the Sichuan Basin with good results: (i) more continuous, sharper and more small-scale fractures were detected by the proposed workflow than the ones with the full-band seismic data. (ii) Compared to the ant-tracking methods based on a series of single-frequency data cubes, this not only requires less computation time, but is also easier to distinguish the differences between the three divided-frequency cubes. (iii) Comparing the ant-tracking effect, the results of medium- and high- frequency cubes are much better than the low- frequency. (iv) Compared with the traditional methods, the time of automatic fracture extraction is obviously shortened. This provided a solid data foundation for subsequent reservoir production prediction and well deployment.