scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/bioinformatics/RichardsMSCRL10 |
P356 | DOI | 10.1093/BIOINFORMATICS/BTQ203 |
P932 | PMC publication ID | 2881388 |
P698 | PubMed publication ID | 20529941 |
P5875 | ResearchGate publication ID | 44655694 |
P2093 | author name string | Xinghua Lu | |
L Ashley Cowart | |||
Adam J Richards | |||
Brian Muller | |||
Matthew Shotwell | |||
Bäerbel Rohrer | |||
P2860 | cites work | Semantic similarity in biomedical ontologies | Q21145359 |
Gene ontology: tool for the unification of biology | Q23781406 | ||
From genomics to chemical genomics: new developments in KEGG | Q24538628 | ||
Cluster analysis and display of genome-wide expression patterns | Q24644463 | ||
Network biology: understanding the cell's functional organization | Q27861027 | ||
Knowledge-based analysis of microarray gene expression data by using support vector machines | Q27939386 | ||
Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists | Q28131785 | ||
Systematic determination of genetic network architecture | Q28138580 | ||
Semantic similarity measures as tools for exploring the gene ontology | Q28211764 | ||
Thy-1 is critical for normal retinal development | Q28594633 | ||
On Estimating Regression | Q29303512 | ||
Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons | Q30745866 | ||
Ontological analysis of gene expression data: current tools, limitations, and open problems | Q30993399 | ||
Improved scoring of functional groups from gene expression data by decorrelating GO graph structure | Q31036410 | ||
A multivariate approach for integrating genome-wide expression data and biological knowledge | Q31050518 | ||
GOGrapher: A Python library for GO graph representation and analysis | Q33479340 | ||
Improving detection of differentially expressed gene sets by applying cluster enrichment analysis to Gene Ontology | Q33490282 | ||
Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. | Q34363246 | ||
The genomics of yeast responses to environmental stress and starvation | Q34794209 | ||
Novel metrics for evaluating the functional coherence of protein groups via protein semantic network | Q36570652 | ||
Neural reprogramming in retinal degeneration. | Q36692268 | ||
A literature-based method for assessing the functional coherence of a gene group | Q37160519 | ||
GS2: an efficiently computable measure of GO-based similarity of gene sets | Q37168032 | ||
Multidestructive pathways triggered in photoreceptor cell death of the rd mouse as determined through gene expression profiling | Q38339652 | ||
A new method to measure the semantic similarity of GO terms | Q38398724 | ||
Multiple testing on the directed acyclic graph of gene ontology. | Q38514569 | ||
Total ancestry measure: quantifying the similarity in tree-like classification, with genomic applications | Q38516098 | ||
A graph-theoretic modeling on GO space for biological interpretation of gene clusters | Q38522164 | ||
Gene expression profiles of mouse retinas during the second and third postnatal weeks | Q40315875 | ||
From mice to men: the cyclic GMP phosphodiesterase gene in vision and disease. The Proctor Lecture. | Q40584439 | ||
Transcriptional regulation and function during the human cell cycle | Q43515454 | ||
Dopamine has a critical role in photoreceptor degeneration in the rd mouse | Q44038221 | ||
POWER_SAGE: comparing statistical tests for SAGE experiments | Q52068990 | ||
The Structure and Function of Complex Networks | Q55879008 | ||
An analysis of variance test for normality (complete samples) | Q57253423 | ||
Silhouettes: A graphical aid to the interpretation and validation of cluster analysis | Q57380611 | ||
P433 | issue | 12 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | ontology | Q324254 |
Gene Ontology | Q135085 | ||
P304 | page(s) | i79-87 | |
P577 | publication date | 2010-06-01 | |
P1433 | published in | Bioinformatics | Q4914910 |
P1476 | title | Assessing the functional coherence of gene sets with metrics based on the Gene Ontology graph | |
P478 | volume | 26 |
Q33911818 | Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis |
Q35101877 | Conceptualization of molecular findings by mining gene annotations |
Q30620822 | From Data towards Knowledge: Revealing the Architecture of Signaling Systems by Unifying Knowledge Mining and Data Mining of Systematic Perturbation Data |
Q27321393 | Functional coherence metrics in protein families |
Q34008003 | GO-based functional dissimilarity of gene sets |
Q51511475 | GSGS: A Computational Approach to Reconstruct Signaling Pathway Structures from Gene Sets |
Q40855428 | Gaining confidence in cross-species annotation transfer: from simple molecular function to complex phenotypic traits. |
Q30874969 | Graphical algorithm for integration of genetic and biological data: proof of principle using psoriasis as a model |
Q34149135 | Identifying informative subsets of the Gene Ontology with information bottleneck methods |
Q30531263 | Literature aided determination of data quality and statistical significance threshold for gene expression studies |
Q33817492 | RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis |
Q34530741 | Revealing functionally coherent subsets using a spectral clustering and an information integration approach |
Q38385125 | Semantic Similarity in the Gene Ontology |
Q28685216 | The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation |
Search more.