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Unified tests for fine-scale mapping and identifying sparse high-dimensional sequence associations
2015
Bioinformatics
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Method: We here propose a unified marker wise test (uFineMap) to accurately localize causal loci and a unified high-dimensional set based test (uHDSet) to identify high-dimensional sparse associations ...
Motivation: In searching for genetic variants for complex diseases with deep sequencing data, genomic marker sets of high-dimensional genotypic data and sparse functional variants are quite common. ...
The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute NHLBI in collaboration with Boston University (Contract no. N01-HC-25195). ...
doi:10.1093/bioinformatics/btv586
pmid:26458888
pmcid:PMC5006306
fatcat:pnyubgbw4ffo7dzayy3mr3fto4
Unified tests for fine scale mapping and identifying sparse high-dimensional sequence associations
2015
Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics - BCB '15
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Method: We here propose a unified marker wise test (uFineMap) to accurately localize causal loci and a unified high-dimensional set based test (uHDSet) to identify high-dimensional sparse associations ...
Motivation: In searching for genetic variants for complex diseases with deep sequencing data, genomic marker sets of high-dimensional genotypic data and sparse functional variants are quite common. ...
The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute NHLBI in collaboration with Boston University (Contract no. N01-HC-25195). ...
doi:10.1145/2808719.2808744
dblp:conf/bcb/CaoQGDW15
fatcat:6p56ige4gbbrbfr4dwvggxwzaq
Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network
2021
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
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This re-ranking stage leads to further improvements in performance and demonstrates the effectiveness of entity re-ranking for KG completion. ...
We curate two KG datasets that include biomedical and encyclopedic knowledge and use an existing commonsense KG dataset to explore KG completion in the more realistic setting where dense connectivity is ...
Acknowledgments This work was supported by the National Science Foundation grant IIS 1917955 and the National Library Medicine of the National Institutes of Health under award number T15 LM007059. ...
doi:10.18653/v1/2021.acl-long.82
pmid:35821978
pmcid:PMC9272461
fatcat:7kzzkogxnzg2fnmv77hgtw4oee
Biomedical Interpretable Entity Representations
[article]
2021
arXiv
pre-print
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From this mapping we derive Biomedical Interpretable Entity Representations(BIERs), in which dimensions correspond to fine-grained entity types, and values are predicted probabilities that a given entity ...
We propose a novel method that exploits BIER's final sparse and intermediate dense representations to facilitate model and entity type debugging. ...
on
and we place their mention values into a set Z.
a Likert scale from 1 (low) to 5 (high) for accuracy. ...
arXiv:2106.09502v1
fatcat:irdxjdgzb5bxvd232urlithh7u
Multi-scale Genomic Inference using Biologically Annotated Neural Networks
[article]
2020
bioRxiv
pre-print
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The BANN software uses scalable variational inference to provide fully interpretable posterior summaries which allow researchers to simultaneously perform (i) fine-mapping with SNPs and (ii) enrichment ...
With the emergence of large-scale genomic datasets, there is a unique opportunity to integrate machine learning approaches as standard tools within genome-wide association (GWA) studies. ...
Acknowledgements This research was conducted in part using computational resources and services at the Center for Com- ...
doi:10.1101/2020.07.02.184465
fatcat:3nvsvz4pvrhnffmcia2oznzbnu
Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment
2017
PLoS Computational Biology
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Acknowledgments We thank Ben Callahan for help with DADA2 processing and computational tools and the reviewers for providing very constructive suggestions for improvement. ...
RSV identifier mapping table. Identifiers for RSV numbers used in text and figures and the taxonomic information for these RSVs. ...
Both sparse LDA and sCCA induce sparsity through ℓ 1 regularization, reducing variance and improving interpretability in the high-dimensional regime. ...
doi:10.1371/journal.pcbi.1005706
pmid:28821012
pmcid:PMC5576755
fatcat:qelirwp455hn3b7ydwaj7dzohi
SparsePro: an efficient genome-wide fine-mapping method integrating summary statistics and functional annotations
[article]
2021
bioRxiv
pre-print
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However, classical fine-mapping methods have a high computational cost, particularly when the underlying genetic architecture and LD patterns are complex. ...
Our method enjoys two major innovations: First, by creating a sparse low-dimensional projection of the high-dimensional genotype, we enable a linear search of causal variants instead of an exponential ...
Introduction Establishment of large biobanks and advances in genotyping and sequencing technologies have enabled large-scale genome-wide association studies (GWASs) [1] [2] [3] . ...
doi:10.1101/2021.10.04.463133
fatcat:ocdtk7idjvcnrftqhn6vztupwi
Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments
[article]
2024
arXiv
pre-print
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This paper presents a novel model, called UMF (standing for Unifying Local and Global Multimodal Features) that 1) leverages multi-modality by cross-attention blocks between vision and LiDAR features, ...
Perceptual aliasing and weak textures pose significant challenges to the task of place recognition, hindering the performance of Simultaneous Localization and Mapping (SLAM) systems. ...
, facilitating the construction of large-scale, dense, high-resolution, and consistent 3D maps. ...
arXiv:2403.13395v1
fatcat:sdphbxqqs5ee3bzjv6as4cjiwa
Autoencoder-based Unsupervised Intrusion Detection using Multi-Scale Convolutional Recurrent Networks
[article]
2022
arXiv
pre-print
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To address this, we propose a unified Autoencoder based on combining multi-scale convolutional neural network and long short-term memory (MSCNN-LSTM-AE) for anomaly detection in network traffic. ...
These solutions often require high computational cost, manual support in fine-tuning intrusion detection models, and labeling of data that limit real-time processing of network traffic. ...
Acknowledgment This research is supported by the Cyber Security Research Programme-Artificial Intelligence for Automating Response to Threats from the Ministry of Business, Innovation, and Employment ( ...
arXiv:2204.03779v1
fatcat:rvxxtx5mmjdhvifwojwbqojhkm
Multimodal Low Resolution Face and Frontal Gait Recognition from Surveillance Video
2021
Electronics
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Second, it uses a low-resolution face recognition approach which can be trained and tested using low-resolution face information. ...
Experiments conducted on the Face and Ocular Challenge Series (FOCS) dataset resulted in a 93.5% Rank-1 for frontal gait recognition and 82.92% Rank-1 for low-resoluti [...] ...
Second, the sparse coefficients obtained from the LR dictionary for the LR test image patches are passed into the high-resolution dictionary for reconstructing the high-resolution patches. ...
doi:10.3390/electronics10091013
doaj:46769ed6fbf842c8ac68ffb373934346
fatcat:bebdizpu3jcl3odzsw3zcgeaym
Sparse Instrumental Variables (SPIV) for Genome-Wide Studies
2010
Neural Information Processing Systems
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Where the biomarkers are gene transcripts, the method can be used for fine mapping of quantitative trait loci (QTLs) detected in genetic linkage studies. ...
The framework builds on sparse linear methods developed for regression and modified here for inferring causal structures of richer networks with latent variables. ...
The dimensionality of the latent factors |z| is fixed at a moderately high value (extraneous dimensions will tend to be pruned under the sparse prior). ...
dblp:conf/nips/AgakovMKS10
fatcat:epkj3zpa7zhkliofwxa67ppl4u
Exploring Neighborhoods in the Metagenome Universe
2014
International Journal of Molecular Sciences
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We have studied efficient sequence-based methods for large-scale identification of similar metagenomes within a database retrieval context. ...
The visualization method shows a similarly high accuracy in the reduced space as compared with the high-dimensional profile space. ...
Acknowledgments We would like to thank two anonymous reviewers for their comments. This work was partially funded by a DFG grant (ME 3138) to P.M. ...
doi:10.3390/ijms150712364
pmid:25026170
pmcid:PMC4139848
fatcat:stwxzbdz6vgrpbrcxec7bjyhji
Deep learning for drug repurposing: methods, databases, and applications
[article]
2022
arXiv
pre-print
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Next, we discuss recently developed sequence-based and graph-based representation approaches as well as state-of-the-art deep learning-based methods. ...
We first summarized the commonly used bioinformatics and pharmacogenomics databases for drug repurposing. ...
(a) One-hot representation of amino acids sequences. (b) Contact map was a kind of two-dimensional (2D) representation of the protein. ...
arXiv:2202.05145v1
fatcat:5oqujy2daffdpa33b4cbrg6hqy
A high-resolution map of coastal vegetation for two Arctic Alaskan parklands: An object-oriented approach with point training data
2022
PLoS ONE
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We classified the map segments using Random Forest because of its high accuracy, computational speed, and ability to incorporate non-normal, high-dimensional data. ...
We present a high-resolution coastal vegetation map to serve as a baseline for potential spill response, restoration, and change detection. ...
Rachel Post and Thea Garrett for field assistance, Nick Bywater for data form design, and Carolyn Parker for specimen identification. ...
doi:10.1371/journal.pone.0273893
pmid:36044528
pmcid:PMC9432696
fatcat:kfnz2up23rbrjocd4vclnxmudq
Dimension reduction techniques for the integrative analysis of multi-omics data
2016
Briefings in Bioinformatics
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State-of-the-art next-generation sequencing, transcriptomics, proteomics and other high-throughput 'omics' technologies enable the efficient generation of large experimental data sets. ...
We explore dimension reduction techniques as one of the emerging approaches for data integration, and how these can be applied to increase our understanding of biological systems in normal physiological ...
John Platig and Marieke Kuijjer for reading the manuscript and for their comments. ...
doi:10.1093/bib/bbv108
pmid:26969681
pmcid:PMC4945831
fatcat:32bp5nbkwjhlzicdbidv3fk7gy
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