Matches in SemOpenAlex for { <https://semopenalex.org/work/W2996937995> ?p ?o ?g. }
- W2996937995 endingPage "2521" @default.
- W2996937995 startingPage "2515" @default.
- W2996937995 abstract "Abstract Motivation Complex diseases involve perturbation in multiple pathways and a major challenge in clinical genomics is characterizing pathway perturbations in individual samples. This can lead to patient-specific identification of the underlying mechanism of disease thereby improving diagnosis and personalizing treatment. Existing methods rely on external databases to quantify pathway activity scores. This ignores the data dependencies and that pathways are incomplete or condition-specific. Results ssNPA is a new approach for subtyping samples based on deregulation of their gene networks. ssNPA learns a causal graph directly from control data. Sample-specific network neighborhood deregulation is quantified via the error incurred in predicting the expression of each gene from its Markov blanket. We evaluate the performance of ssNPA on liver development single-cell RNA-seq data, where the correct cell timing is recovered; and two TCGA datasets, where ssNPA patient clusters have significant survival differences. In all analyses ssNPA consistently outperforms alternative methods, highlighting the advantage of network-based approaches. Availability and implementation http://www.benoslab.pitt.edu/Software/ssnpa/. Supplementary information Supplementary data are available at Bioinformatics online." @default.
- W2996937995 created "2020-01-10" @default.
- W2996937995 creator A5034705320 @default.
- W2996937995 creator A5042618575 @default.
- W2996937995 creator A5071831267 @default.
- W2996937995 date "2019-12-24" @default.
- W2996937995 modified "2023-10-15" @default.
- W2996937995 title "Causal network perturbations for instance-specific analysis of single cell and disease samples" @default.
- W2996937995 cites W1512489780 @default.
- W2996937995 cites W1854769545 @default.
- W2996937995 cites W1884291487 @default.
- W2996937995 cites W1964079962 @default.
- W2996937995 cites W1965842819 @default.
- W2996937995 cites W1977822330 @default.
- W2996937995 cites W1978012795 @default.
- W2996937995 cites W1984689597 @default.
- W2996937995 cites W1998137759 @default.
- W2996937995 cites W2008495749 @default.
- W2996937995 cites W2011417152 @default.
- W2996937995 cites W2053631236 @default.
- W2996937995 cites W2064955782 @default.
- W2996937995 cites W2072177644 @default.
- W2996937995 cites W2073015226 @default.
- W2996937995 cites W2073307618 @default.
- W2996937995 cites W2096283457 @default.
- W2996937995 cites W2114104545 @default.
- W2996937995 cites W2123879591 @default.
- W2996937995 cites W2125631472 @default.
- W2996937995 cites W2130410032 @default.
- W2996937995 cites W2146512944 @default.
- W2996937995 cites W2158384363 @default.
- W2996937995 cites W2159707944 @default.
- W2996937995 cites W2161098391 @default.
- W2996937995 cites W2234357922 @default.
- W2996937995 cites W2270020113 @default.
- W2996937995 cites W2275877493 @default.
- W2996937995 cites W2417388301 @default.
- W2996937995 cites W2531327699 @default.
- W2996937995 cites W2551668581 @default.
- W2996937995 cites W2556538645 @default.
- W2996937995 cites W2557632452 @default.
- W2996937995 cites W2558182048 @default.
- W2996937995 cites W2559931140 @default.
- W2996937995 cites W2582415638 @default.
- W2996937995 cites W2605810679 @default.
- W2996937995 cites W2619474479 @default.
- W2996937995 cites W2727913218 @default.
- W2996937995 cites W2771365419 @default.
- W2996937995 cites W2776999167 @default.
- W2996937995 cites W2791842758 @default.
- W2996937995 cites W2794480084 @default.
- W2996937995 cites W2801401400 @default.
- W2996937995 cites W2806548928 @default.
- W2996937995 cites W2809667147 @default.
- W2996937995 cites W2887103892 @default.
- W2996937995 cites W2949444664 @default.
- W2996937995 cites W2950545834 @default.
- W2996937995 cites W2951118605 @default.
- W2996937995 cites W2969698477 @default.
- W2996937995 cites W4294216483 @default.
- W2996937995 cites W4294541781 @default.
- W2996937995 cites W2557366952 @default.
- W2996937995 doi "https://doi.org/10.1093/bioinformatics/btz949" @default.
- W2996937995 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7178399" @default.
- W2996937995 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31873725" @default.
- W2996937995 hasPublicationYear "2019" @default.
- W2996937995 type Work @default.
- W2996937995 sameAs 2996937995 @default.
- W2996937995 citedByCount "12" @default.
- W2996937995 countsByYear W29969379952020 @default.
- W2996937995 countsByYear W29969379952021 @default.
- W2996937995 countsByYear W29969379952022 @default.
- W2996937995 countsByYear W29969379952023 @default.
- W2996937995 crossrefType "journal-article" @default.
- W2996937995 hasAuthorship W2996937995A5034705320 @default.
- W2996937995 hasAuthorship W2996937995A5042618575 @default.
- W2996937995 hasAuthorship W2996937995A5071831267 @default.
- W2996937995 hasBestOaLocation W29969379951 @default.
- W2996937995 hasConcept C116834253 @default.
- W2996937995 hasConcept C119857082 @default.
- W2996937995 hasConcept C123867240 @default.
- W2996937995 hasConcept C124101348 @default.
- W2996937995 hasConcept C163836022 @default.
- W2996937995 hasConcept C189973286 @default.
- W2996937995 hasConcept C199360897 @default.
- W2996937995 hasConcept C2777904410 @default.
- W2996937995 hasConcept C41008148 @default.
- W2996937995 hasConcept C59822182 @default.
- W2996937995 hasConcept C70721500 @default.
- W2996937995 hasConcept C83852419 @default.
- W2996937995 hasConcept C86803240 @default.
- W2996937995 hasConcept C98763669 @default.
- W2996937995 hasConceptScore W2996937995C116834253 @default.
- W2996937995 hasConceptScore W2996937995C119857082 @default.
- W2996937995 hasConceptScore W2996937995C123867240 @default.
- W2996937995 hasConceptScore W2996937995C124101348 @default.
- W2996937995 hasConceptScore W2996937995C163836022 @default.
- W2996937995 hasConceptScore W2996937995C189973286 @default.