Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Bioinformatics
Title: X-A-BiLSTM: a Deep Learning Approach for Depression Detection in Imbalanced Data
Abstract: An increasing number of people suffering from mental health conditions resort to online resources (specialized websites, social media, etc.) to share their feelings. Early depression detection using social media data through deep learning models can help to change life trajectories and save lives. But the accuracy of these models was not satisfying due to the real-world imbalanced data distributions. To tackle this problem, we propose a deep learning model (X-A-BiLSTM) for depression detection in imbalanced social media data. The X-A-BiLSTM model consists of two essential components: the first one is XGBoost, which is used to reduce data imbalance; and the second one is an Attention-BiLSTM neural network, which enhances classification capacity. The Reddit Self-reported Depression Diagnosis (RSDD) dataset was chosen, which included approximately 9,000 users who claimed to have been diagnosed with depression (”diagnosed users and approximately 107,000 matched control users. Results demonstrate that our approach significantly outperforms the previous state-of-the-art models on the RSDD dataset.
Extracted statement — Used models: LSTM
Research field: Bioinformatics
Title: MAGERI: Computational pipeline for molecular-barcoded targeted resequencing
Abstract: Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.
Extracted statement — creates: MAGERI
Research field: Bioinformatics
Title: MAGERI: Computational pipeline for molecular-barcoded targeted resequencing
Abstract: Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.
Extracted statement — deposits: MAGERI
Research field: Bioinformatics
Title: MAGPIE: Simplifying access and execution of computational models in the life sciences
Abstract: Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.
Extracted statement — creates: MAGPIE
Research field: Bioinformatics
Title: MAGPIE: Simplifying access and execution of computational models in the life sciences
Abstract: Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.
Extracted statement — deposits: MAGPIE
Research field: Bioinformatics
Title: MAGPIE: Simplifying access and execution of computational models in the life sciences
Abstract: Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.
Extracted statement — uses: MAGPIE
Research field: Bioinformatics
Title: CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data
Abstract: Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
Extracted statement — uses: MATLAB
Research field: Bioinformatics
Title: MedPost: a part-of-speech tagger for bioMedical text
Abstract: SUMMARY We present a part-of-speech tagger that achieves over 97% accuracy on MEDLINE citations. AVAILABILITY Software, documentation and a corpus of 5700 manually tagged sentences are available at ftp://ftp.ncbi.nlm.nih.gov/pub/lsmith/MedPost/medpost.tar.gz
Extracted statement — Other resources: MEDLINE
Research field: Bioinformatics
Title: Tagging gene and protein names in biomedical text
Abstract: MOTIVATION The MEDLINE database of biomedical abstracts contains scientific knowledge about thousands of interacting genes and proteins. Automated text processing can aid in the comprehension and synthesis of this valuable information. The fundamental task of identifying gene and protein names is a necessary first step towards making full use of the information encoded in biomedical text. This remains a challenging task due to the irregularities and ambiguities in gene and protein nomenclature. We propose to approach the detection of gene and protein names in scientific abstracts as part-of-speech tagging, the most basic form of linguistic corpus annotation. RESULTS We present a method for tagging gene and protein names in biomedical text using a combination of statistical and knowledge-based strategies. This method incorporates automatically generated rules from a transformation-based part-of-speech tagger, and manually generated rules from morphological clues, low frequency trigrams, indicator terms, suffixes and part-of-speech information. Results of an experiment on a test corpus of 56K MEDLINE documents demonstrate that our method to extract gene and protein names can be applied to large sets of MEDLINE abstracts, without the need for special conditions or human experts to predetermine relevant subsets. AVAILABILITY The programs are available on request from the authors.
Extracted statement — Other resources: MEDLINE
Research field: Bioinformatics
Title: MEDYAN: Mechanochemical Simulations of Contraction and Polarity Alignment in Actomyosin Networks
Abstract: Active matter systems, and in particular the cell cytoskeleton, exhibit complex mechanochemical dynamics that are still not well understood. While prior computational models of cytoskeletal dynamics have lead to many conceptual insights, an important niche still needs to be filled with a high-resolution structural modeling framework, which includes a minimally-complete set of cytoskeletal chemistries, stochastically treats reaction and diffusion processes in three spatial dimensions, accurately and efficiently describes mechanical deformations of the filamentous network under stresses generated by molecular motors, and deeply couples mechanics and chemistry at high spatial resolution. To address this need, we propose a novel reactive coarse-grained force field, as well as a publicly available software package, named the Mechanochemical Dynamics of Active Networks (MEDYAN), for simulating active network evolution and dynamics (available at www.medyan.org). This model can be used to study the non-linear, far from equilibrium processes in active matter systems, in particular, comprised of interacting semi-flexible polymers embedded in a solution with complex reaction-diffusion processes. In this work, we applied MEDYAN to investigate a contractile actomyosin network consisting of actin filaments, alpha-actinin cross-linking proteins, and non-muscle myosin IIA mini-filaments. We found that these systems undergo a switch-like transition in simulations from a random network to ordered, bundled structures when cross-linker concentration is increased above a threshold value, inducing contraction driven by myosin II mini-filaments. Our simulations also show how myosin II mini-filaments, in tandem with cross-linkers, can produce a range of actin filament polarity distributions and alignment, which is crucially dependent on the rate of actin filament turnover and the actin filament’s resulting super-diffusive behavior in the actomyosin-cross-linker system. We discuss the biological implications of these findings for the arc formation in lamellipodium-to-lamellum architectural remodeling. Lastly, our simulations produce force-dependent accumulation of myosin II, which is thought to be responsible for their mechanosensation ability, also spontaneously generating myosin II concentration gradients in the solution phase of the simulation volume.
Extracted statement — deposits: MEDYAN
Research field: Bioinformatics
Title: Transient Cerebral Ischemia Promotes Brain Mitochondrial Dysfunction and Exacerbates Cognitive Impairments in Young 5xFAD Mice
Abstract: Alzheimer's disease (AD) is heterogeneous and multifactorial neurological disorder; and the risk factors of AD still remain elusive. Recent studies have highlighted the role of vascular factors in promoting the progression of AD and have suggested that ischemic events increase the incidence of AD. However, the detailed mechanisms linking ischemic insult to the progression of AD is still largely undetermined. In this study, we have established a transient cerebral ischemia model on young 5xFAD mice and their non-transgenic (nonTg) littermates by the transient occlusion of bilateral common carotid arteries. We have found that transient cerebral ischemia significantly exacerbates brain mitochondrial dysfunction including mitochondrial respiration deficits, oxidative stress as well as suppressed levels of mitochondrial fusion proteins including optic atrophy 1 (OPA1) and mitofusin 2 (MFN2) in young 5xFAD mice resulting in aggravated spatial learning and memory. Intriguingly, transient cerebral ischemia did not induce elevation in the levels of cortical or mitochondrial Amyloid beta (Aβ)1-40 or 1–42 levels in 5xFAD mice. In addition, the glucose- and oxygen-deprivation-induced apoptotic neuronal death in Aβ-treated neurons was significantly mitigated by mitochondria-targeted antioxidant mitotempo which suppresses mitochondrial superoxide levels. Therefore, the simplest interpretation of our results is that young 5xFAD mice with pre-existing AD-like mitochondrial dysfunction are more susceptible to the effects of transient cerebral ischemia; and ischemic events may exacerbate dementia and worsen the outcome of AD patients by exacerbating mitochondrial dysfunction.
Extracted statement — uses: NIS
Research field: Bioinformatics
Title: PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies
Abstract: The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the ‘missing heritability,’ which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.
Extracted statement — deposits: PEPIS
Research field: Bioinformatics
Title: Copy Number Variation in Subjects with Major Depressive Disorder Who Attempted Suicide
Abstract: Background Suicide is one of the top ten leading causes of death in North America and represents a major public health burden, partcularly for people with Major Depressive disorder (MD). Many studies have suggested that suicidal behavior runs in families, however, identification of genomic loci that drive this efffect remain to be identified. Methodology/Principal Findings Using subjects collected as part of STAR*D, we genotyped 189 subjects with MD with history of a suicide attempt and 1073 subjects with Major Depressive disorder that had never attempted suicide. Copy Number Variants (CNVs) were called in Birdsuite and analyzed in PLINK. We found a set of CNVs present in the suicide attempter group that were not present in in the non-attempter group including in SNTG2 and MACROD2 – two brain expressed genes previously linked to psychopathology; however, these results failed to reach genome-wide signifigance. Conclusions These data suggest potential CNVs to be investigated further in relation to suicide attempts in MD using large sample sizes.
Extracted statement — uses: PLINK
Research field: Bioinformatics
Title: Pain Processing after Social Exclusion and Its Relation to Rejection Sensitivity in Borderline Personality Disorder
Abstract: Objective There is a general agreement that physical pain serves as an alarm signal for the prevention of and reaction to physical harm. It has recently been hypothesized that “social pain,” as induced by social rejection or abandonment, may rely on comparable, phylogenetically old brain structures. As plausible as this theory may sound, scientific evidence for this idea is sparse. This study therefore attempts to link both types of pain directly. We studied patients with borderline personality disorder (BPD) because BPD is characterized by opposing alterations in physical and social pain; hyposensitivity to physical pain is associated with hypersensitivity to social pain, as indicated by an enhanced rejection sensitivity. Method Twenty unmedicated female BPD patients and 20 healthy participants (HC, matched for age and education) played a virtual ball-tossing game (cyberball), with the conditions for exclusion, inclusion, and a control condition with predefined game rules. Each cyberball block was followed by a temperature stimulus (with a subjective pain intensity of 60% in half the cases). The cerebral responses were measured by functional magnetic resonance imaging. The Adult Rejection Sensitivity Questionnaire was used to assess rejection sensitivity. Results Higher temperature heat stimuli had to be applied to BPD patients relative to HCs to reach a comparable subjective experience of painfulness in both groups, which suggested a general hyposensitivity to pain in BPD patients. Social exclusion led to a subjectively reported hypersensitivity to physical pain in both groups that was accompanied by an enhanced activation in the anterior insula and the thalamus. In BPD, physical pain processing after exclusion was additionally linked to enhanced posterior insula activation. After inclusion, BPD patients showed reduced amygdala activation during pain in comparison with HC. In BPD patients, higher rejection sensitivity was associated with lower activation differences during pain processing following social exclusion and inclusion in the insula and in the amygdala. Discussion Despite the similar behavioral effects in both groups, BPD patients differed from HC in their neural processing of physical pain depending on the preceding social situation. Rejection sensitivity further modulated the impact of social exclusion on neural pain processing in BPD, but not in healthy controls.
Extracted statement — uses: PROCESS