Drug-target prediction utilizing heterogeneous bio-linked network embeddings. Zong N, Wong RSN, Yu Y, Wen A, Huang M, Li N. Brief Bioinform. 2019 Dec 27. pii: bbz147. doi: 10.1093/bib/bbz147. [Epub ahead of print] PMID: 31885036
A network embedding model for pathogenic genes prediction by multi-path random walking on heterogeneous network.
Xu B, Liu Y, Yu S, Wang L, Dong J, Lin H, Yang Z, Wang J, Xia F.
BMC Med Genomics. 2019 Dec 23;12(Suppl 10):188. doi: 10.1186/s12920-019-0627-z.
PMID: 31865919
Presentation:
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Finding prognostic gene pairs for cancer from patient-specific gene networks. Park B, Lee W, Park I, Han K. BMC Med Genomics. 2019 Dec 20;12(Suppl 8):179. doi: 10.1186/s12920-019-0634-0. PMID: 31856825
Evaluation of knowledge graph embedding approaches for drug-drug interaction prediction in realistic settings. Celebi R, Uyar H, Yasar E, Gumus O, Dikenelli O, Dumontier M. BMC Bioinformatics. 2019 Dec 18;20(1):726. doi: 10.1186/s12859-019-3284-5. PMID: 31852427
Time-resolved evaluation of compound repositioning predictions on a text-mined knowledge network. Mayers M, Li TS, Queralt-Rosinach N, Su AI. BMC Bioinformatics. 2019 Dec 11;20(1):653. doi: 10.1186/s12859-019-3297-0. PMID: 31829175
Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches. Güvenç Paltun B, Mamitsuka H, Kaski S. Brief Bioinform. 2019 Dec 15. pii: bbz153. doi: 10.1093/bib/bbz153. [Epub ahead of print] PMID: 31838491
Predicting effective drug combinations using gradient tree boosting based on features extracted from drug-protein heterogeneous network. Liu H, Zhang W, Nie L, Ding X, Luo J, Zou L. BMC Bioinformatics. 2019 Dec 9;20(1):645. doi: 10.1186/s12859-019-3288-1. PMID: 31818267
Network-Based Matching of Patients and Targeted Therapies for Precision Oncology. Liu Q, Ha MJ, Bhattacharyya R, Garmire L, Baladandayuthapani V. Pac Symp Biocomput. 2020;25:623-634. PMID: 31797633
Pathway and network embedding methods for prioritizing psychiatric drugs.
Pershad Y, Guo M, Altman RB.
Pac Symp Biocomput. 2020;25:671-682.
PMID: 31797637
Code: https://github.com/ypershad/pathway-network-psych-drugs
Presentation:
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A Literature-Based Knowledge Graph Embedding Method for Identifying Drug Repurposing Opportunities in Rare Diseases. Sosa DN, Derry A, Guo M, Wei E, Brinton C, Altman RB. Pac Symp Biocomput. 2020;25:463-474. PMID: 31797619
Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph.
Chen IY, Agrawal M, Horng S, Sontag D.
Pac Symp Biocomput. 2020;25:19-30.
PMID: 31797583
Presentation:
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Network-Based Selection of Candidate Markers and Assays to Assess the Impact of Oral Immune Interventions on Gut Functions. Meijerink M, van den Broek TJ, Dulos R, Garthoff J, Knippels L, Knipping K, Harthoorn L, Houben G, Verschuren L, van Bilsen J. Front Immunol. 2019 Nov 13;10:2672. doi: 10.3389/fimmu.2019.02672. PMID: 31798593
Network Modeling Approaches and Applications to Unravelling Non-Alcoholic Fatty Liver Disease. Blencowe M, Karunanayake T, Wier J, Hsu N, Yang X. Genes (Basel). 2019 Nov 24;10(12). pii: E966. doi: 10.3390/genes10120966. Review. PMID: 31771247
Discovery of disease- and drug-specific pathways through community structures of a literature network.
Pham M, Wilson S, Govindarajan H, Lin CH, Lichtarge O.
Bioinformatics. 2019 Nov 18. pii: btz857. doi: 10.1093/bioinformatics/btz857. [Epub ahead of print]
PMID: 31738408
Website (download etc.):
http://meteor.lichtargelab.org/
Enriching Human Interactome with Functional Mutations to Detect High-Impact Network Modules Underlying Complex Diseases. Cui H, Srinivasan S, Korkin D. Genes (Basel). 2019 Nov 15;10(11). pii: E933. doi: 10.3390/genes10110933. PMID: 31731769
An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies. Marín M, Esteban FJ, Ramírez-Rodrigo H, Ros E, Sáez-Lara MJ. BMC Bioinformatics. 2019 Nov 12;20(1):565. doi: 10.1186/s12859-019-3162-1. PMID: 31718537
A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction models. Mihaylov I, Kańduła M, Krachunov M, Vassilev D. Biol Direct. 2019 Nov 21;14(1):22. doi: 10.1186/s13062-019-0249-6. PMID: 31752974
MIRKB: a myocardial infarction risk knowledge base.
Zhan C, Shi M, Wu R, He H, Liu X, Shen B.
Database (Oxford). 2019 Jan 1;2019. pii: baz125. doi: 10.1093/database/baz125.
PMID: 31688939
Database: http://sysbio.org.cn/MIRKB/
Network-based method for drug target discovery at the isoform level. Ma J, Wang J, Ghoraie LS, Men X, Liu L, Dai P. Sci Rep. 2019 Sep 25;9(1):13868. doi: 10.1038/s41598-019-50224-x. PMID: 31554914
An in Silico Approach for Integrating Phenotypic and Target-Based Approaches in Drug Discovery. Iwata H, Kojima R, Okuno Y. Mol Inform. 2019 Oct 22. doi: 10.1002/minf.201900096. [Epub ahead of print] PMID: 31638744
WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network. Long Y, Luo J. BMC Bioinformatics. 2019 Nov 1;20(1):541. doi: 10.1186/s12859-019-3066-0. PMID: 31675979
PPR-SSM: personalized PageRank and semantic similarity measures for entity linking. Lamurias A, Ruas P, Couto FM. BMC Bioinformatics. 2019 Oct 29;20(1):534. doi: 10.1186/s12859-019-3157-y. PMID: 31664891
PRODIGY: personalized prioritization of driver genes. Dinstag G, Shamir R. Bioinformatics. 2019 Nov 4. pii: btz815. doi: 10.1093/bioinformatics/btz815. [Epub ahead of print] PMID: 31681944
Drug Side-Effect Prediction Via Random Walk on the Signed Heterogeneous Drug Network. Hu B, Wang H, Yu Z. Molecules. 2019 Oct 11;24(20). pii: E3668. doi: 10.3390/molecules24203668. PMID: 31614686
Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations. Yue X, Wang Z, Huang J, Parthasarathy S, Moosavinasab S, Huang Y, Lin SM, Zhang W, Zhang P, Sun H. Bioinformatics. 2019 Oct 4. pii: btz718. doi: 10.1093/bioinformatics/btz718. [Epub ahead of print] PMID: 31584634
Microbiomes as sources of emergent host phenotypes. Lynch JB, Hsiao EY. Science. 2019 Sep 27; Vol. 365, Issue 6460, pp. 1405-1409 DOI: 10.1126/science.aay0240
Unified feature association networks through integration of transcriptomic and proteomic data. McClure RS, Wendler JP, Adkins JN, Swanstrom J, Baric R, Kaiser BLD, Oxford KL, Waters KM, McDermott JE. PLoS Comput Biol. 2019 Sep 17;15(9):e1007241. doi: 10.1371/journal.pcbi.1007241. PMID: 31527878
A precision medicine approach to defining the impact of doxorubicin on the bioenergetic-metabolite interactome in human platelets. Smith MR, Chacko BK, Johnson MS, Benavides GA, Uppal K, Go YM, Jones DP, Darley-Usmar VM. Redox Biol. 2019 Sep 7;28:101311. doi: 10.1016/j.redox.2019.101311. [Epub ahead of print] PMID: 31546171
Challenges in the construction of knowledge bases for human microbiome-disease associations. Badal VD, Wright D, Katsis Y, Kim HC, Swafford AD, Knight R, Hsu CN. Microbiome. 2019 Sep 5;7(1):129. doi: 10.1186/s40168-019-0742-2. Review. PMID: 31488215
Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm. Iwata M, Yuan L, Zhao Q, Tabei Y, Berenger F, Sawada R, Akiyoshi S, Hamano M, Yamanishi Y. Bioinformatics. 2019 Jul 15;35(14):i191-i199. doi: 10.1093/bioinformatics/btz313. PMID: 31510663
Crosstalk between microRNAs, the putative target genes and the lncRNA network in metabolic diseases. Assmann TS, Milagro FI, Martínez JA. Mol Med Rep. 2019 Aug 21. doi: 10.3892/mmr.2019.10595. [Epub ahead of print] PMID: 31485667
Assessment of network module identification across complex diseases. Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, Lamparter D, Lin J, Hescott B, Hu X, Mercer J, Natoli T, Narayan R; DREAM Module Identification Challenge Consortium, Subramanian A, Zhang JD, Stolovitzky G, Kutalik Z, Lage K, Slonim DK, Saez-Rodriguez J, Cowen LJ, Bergmann S, Marbach D. Nat Methods. 2019 Sep;16(9):843-852. doi: 10.1038/s41592-019-0509-5. PMID: 31471613
Benchmarking network propagation methods for disease gene identification. Picart-Armada S, Barrett SJ, Willé DR, Perera-Lluna A, Gutteridge A, Dessailly BH. PLoS Comput Biol. 2019 Sep 3;15(9):e1007276. doi: 10.1371/journal.pcbi.1007276. [Epub ahead of print] PMID: 31479437
HENA, heterogeneous network-based data set for Alzheimer's disease. Sügis E, Dauvillier J, Leontjeva A, Adler P, Hindie V, Moncion T, Collura V, Daudin R, Loe-Mie Y, Herault Y, Lambert JC, Hermjakob H, Pupko T, Rain JC, Xenarios I, Vilo J, Simonneau M, Peterson H. Sci Data. 2019 Aug 14;6(1):151. doi: 10.1038/s41597-019-0152-0. PMID: 31413325
Construction and Comprehensive Analysis of a Molecular Association Network via lncRNA-miRNA -Disease-Drug-Protein Graph. Guo ZH, Yi HC, You ZH. Cells. 2019 Aug 9;8(8). pii: E866. doi: 10.3390/cells8080866. PMID: 31405040
Disbiome database: linking the microbiome to disease.
Janssens Y, Nielandt J, Bronselaer A, Debunne N, Verbeke F, Wynendaele E, Van Immerseel F, Vandewynckel YP, De Tré G, De Spiegeleer B.
BMC Microbiol. 2018 Jun 4;18(1):50. doi: 10.1186/s12866-018-1197-5.
PMID: 29866037
Database: https://disbiome.ugent.be/home
A genome-wide positioning systems network algorithm for in silico drug repurposing. Cheng F, Lu W, Liu C, Fang J, Hou Y, Handy DE, Wang R, Zhao Y, Yang Y, Huang J, Hill DE, Vidal M, Eng C, Loscalzo J. Nat Commun. 2019 Aug 2;10(1):3476. doi: 10.1038/s41467-019-10744-6. PMID: 31375661
Network Diffusion Approach to Predict LncRNA Disease Associations Using Multi-Type Biological Networks: LION. Sumathipala M, Maiorino E, Weiss ST, Sharma A. Front Physiol. 2019 Jul 16;10:888. doi: 10.3389/fphys.2019.00888. PMID: 31379598
Drug repurposing with network reinforcement. Nam Y, Kim M, Chang HS, Shin H. BMC Bioinformatics. 2019 Jul 24;20(Suppl 13):383. doi: 10.1186/s12859-019-2858-6. PMID: 31337333
Efficacy of leflunomide combined with ligustrazine in the treatment of rheumatoid arthritis: prediction with network pharmacology and validation in a clinical trial. Zhang C, Guan D, Jiang M, Liang C, Li L, Zhao N, Zha Q, Zhang W, Lu C, Zhang G, Liu J, Lu A. Chin Med. 2019 Aug 2;14:26. doi: 10.1186/s13020-019-0247-8. PMID: 31388350
RWHMDA: Random Walk on Hypergraph for Microbe-Disease Association Prediction. Niu YW, Qu CQ, Wang GH, Yan GY. Front Microbiol. 2019 Jul 10;10:1578. doi: 10.3389/fmicb.2019.01578. PMID: 31354672
Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer. Tang J, Gautam P, Gupta A, He L, Timonen S, Akimov Y, Wang W, Szwajda A, Jaiswal A, Turei D, Yadav B, Kankainen M, Saarela J, Saez-Rodriguez J, Wennerberg K, Aittokallio T. NPJ Syst Biol Appl. 2019 Jul 8;5:20. doi: 10.1038/s41540-019-0098-z. PMID: 31312514
Predicting lncRNA-disease associations using network topological similarity based on deep mining heterogeneous networks.
Zhang H, Liang Y, Peng C, Han S, Du W, Li Y.
Math Biosci. 2019 Jul 16:108229. doi: 10.1016/j.mbs.2019.108229. [Epub ahead of print]
PMID: 31323239
Code and data: https://github.com/Pengeace/lncRNA-disease-link
Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings. Nelson CA, Butte AJ, Baranzini SE. Nat Commun. 2019 Jul 10;10(1):3045. doi: 10.1038/s41467-019-11069-0. PMID: 31292438
HerGePred: Heterogeneous Network Embedding Representation for Disease Gene Prediction. Yang K, Wang R, Liu G, Shu Z, Wang N, Zhang R, Yu J, Chen J, Li X, Zhou X. IEEE J Biomed Health Inform. 2019 Jul;23(4):1805-1815. doi: 10.1109/JBHI.2018.2870728. PMID: 31283472
Relation Prediction of Co-morbid Diseases Using Knowledge Graph Completion. Biswas S, Mitra P, Rao KS. IEEE/ACM Trans Comput Biol Bioinform. 2019 Jul 9. doi: 10.1109/TCBB.2019.2927310. [Epub ahead of print] PMID: 31295118
Fusion of multiple heterogeneous networks for predicting circRNA-disease associations. Deng L, Zhang W, Shi Y, Tang Y. Sci Rep. 2019 Jul 3;9(1):9605. doi: 10.1038/s41598-019-45954-x. PMID: 31270357
HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods. Veselkov K, Gonzalez G, Aljifri S, Galea D, Mirnezami R, Youssef J, Bronstein M, Laponogov I. Sci Rep. 2019 Jul 3;9(1):9237. doi: 10.1038/s41598-019-45349-y. PMID: 31270435
Disease gene prediction for molecularly uncharacterized diseases. Cáceres JJ, Paccanaro A. PLoS Comput Biol. 2019 Jul 5;15(7):e1007078. doi: 10.1371/journal.pcbi.1007078. [Epub ahead of print] PMID: 31276496
Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism. Maini Rekdal V, Bess EN, Bisanz JE, Turnbaugh PJ, Balskus EP. Science. 2019 Jun 14;364(6445). pii: eaau6323. PMID: 31196984
The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism. Spanogiannopoulos P, Bess EN, Carmody RN, Turnbaugh PJ. Nat Rev Microbiol. 2016 Apr;14(5):273-87. Review. PMID: 26972811
Mining heterogeneous network for drug repositioning using phenotypic information extracted from social media and pharmaceutical databases. Yang CC, Zhao M. Artif Intell Med. 2019 May;96:80-92. doi: 10.1016/j.artmed.2019.03.003. PMID: 31164213
Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection. Nikfarjam A, Ransohoff JD, Callahan A, Jones E, Loew B, Kwong BY, Sarin KY, Shah NH. JMIR Public Health Surveill. 2019 Jun 3;5(2):e11264. doi: 10.2196/11264. PMID: 31162134
BioRXiv:
MOBN: an interactive database of multi-omics biological networks.
Cheng Zhang, Muhammad Arif, Xiangyu Li, Sunjae Lee, Abdellah Tebani, Wenyu Zhou, Brian D. Piening, Linn Fagerberg, Nathan Price, Leroy Hood, Michael P. Snyder, Jens Nielsen, Mathias Uhlen, Adil Mardinoglu
doi: https://doi.org/10.1101/662502
Database: multiomics.inetmodels.com
Network Medicine In Pathobiology. Yong-Hwa Lee L, Loscalzo J. Am J Pathol. 2019 Apr 20. pii: S0002-9440(19)30093-8. doi: 10.1016/j.ajpath.2019.03.009. [Epub ahead of print] Review. PMID: 31014954
Revealing Drug-Target Interactions with Computational Models and Algorithms. Zhou L, Li Z, Yang J, Tian G, Liu F, Wen H, Peng L, Chen M, Xiang J, Peng L. Molecules. 2019 May 2;24(9). pii: E1714. doi: 10.3390/molecules24091714. Review. PMID: 31052598
GIDB: a knowledge database for the automated curation and multidimensional analysis of molecular signatures in gastrointestinal cancer. Wang Y, Wang Y, Wang S, Tong Y, Jin L, Zong H, Zheng R, Yang J, Zhang Z, Ouyang E, Zhou M, Zhang X. Database (Oxford). 2019 Jan 1;2019. pii: baz051. PMID: 31089686
QAnalysis: a question-answer driven analytic tool on knowledge graphs for leveraging electronic medical records for clinical research.
Ruan T, Huang Y, Liu X, Xia Y, Gao J.
BMC Med Inform Decis Mak. 2019 Apr 1;19(1):82.
PMID: 30935389
ECM: uses Neo4j
Virtual screening of active compounds from Artemisia argyi and potential targets against gastric ulcer based on Network pharmacology. Wang Y, Sun YW, Wang YM, Ju Y, Meng DL. Bioorg Chem. 2019 Apr 13;88:102924. doi: 10.1016/j.bioorg.2019.102924. [Epub ahead of print] PMID: 31005783
Network-based prediction of drug combinations. Cheng F, Kovács IA, Barabási AL. Nat Commun. 2019 Mar 13;10(1):1197. PMID: 30867426
Network-based prediction of protein interactions. Kovács IA, Luck K, Spirohn K, Wang Y, Pollis C, Schlabach S, Bian W, Kim DK, Kishore N, Hao T, Calderwood MA, Vidal M, Barabási AL. Nat Commun. 2019 Mar 18;10(1):1240. PMID: 30886144
Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson. Hatz S, Spangler S, Bender A, Studham M, Haselmayer P, Lacoste AMB, Willis VC, Martin RL, Gurulingappa H, Betz U. PLoS One. 2019 Apr 8;14(4):e0214619. PMID: 30958864
From single drug targets to synergistic network pharmacology in ischemic stroke. Casas AI, Hassan AA, Larsen SJ, Gomez-Rangel V, Elbatreek M, Kleikers PWM, Guney E, Egea J, López MG, Baumbach J, Schmidt HHHW. Proc Natl Acad Sci U S A. 2019 Apr 2;116(14):7129-7136. PMID: 30894481
Hub genes in a pan-cancer co-expression network show potential for predicting drug responses.
Azuaje F, Kaoma T, Jeanty C, Nazarov PV, Muller A, Kim SY, Dittmar G, Golebiewska A, Niclou SP.
F1000Res. 2018 Dec 7;7:1906.
PMID: 30881689
Rshiny web app: Dr. Paso
(Drug Response Prediction and Analysis System for Oncology)
ECM: this website may not be working
In silico perturbation of drug targets in pan-cancer analysis combining multiple networks and pathways. Cava C, Castiglioni I. Gene. 2019 May 25;698:100-106. PMID: 30840853
Identification of Cancer Hallmarks Based on the Gene Co-expression Networks of Seven Cancers. Yu LH, Huang QW, Zhou XH. Front Genet. 2019 Feb 19;10:99. PMID: 30838028
A Computational Platform and Guide for Acceleration of Novel Medicines and Personalized Medicine. Melas IN, Sakellaropoulos T, Hur J, Messinis D, Guo EY, Alexopoulos LG, Bai JPF. Methods Mol Biol. 2019;1939:181-198. PMID: 30848462
Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes. Regan-Fendt KE, Xu J, DiVincenzo M, Duggan MC, Shakya R, Na R, Carson WE 3rd, Payne PRO, Li F. NPJ Syst Biol Appl. 2019 Feb 26;5:6. PMID: 30820351
Disease comorbidity-guided drug repositioning: a case study in schizophrenia.
Wang Q, Xu R.
AMIA Annu Symp Proc. 2018 Dec 5;2018:1300-1309.
PMID: 30815174
disease-comorbidity edges and weights: http://nlp.case.edu/public/data/dCombKB
drug-disease edges: http://nlp.case.edu/public/data/treatKB
See also Alzheimer disease comorbidity data
Modeling Antibacterial Activity with Machine Learning and Fusion of Chemical Structure Information with Microorganism Metabolic Networks. Nocedo-Mena D, Cornelio C, Camacho-Corona MDR, Garza-Gonzalez E, Waksman NH, Arrasate S, Sotomayor N, Lete E, González-Díaz H. J Chem Inf Model. 2019 Feb 25. [Epub ahead of print] PMID: 30802402
A Data Integration Multi-Omics Approach to Study Calorie Restriction-Induced Changes in Insulin Sensitivity. Dao MC, Sokolovska N, Brazeilles R, Affeldt S, Pelloux V, Prifti E, Chilloux J, Verger EO, Kayser BD, Aron-Wisnewsky J, Ichou F, Pujos-Guillot E, Hoyles L, Juste C, Doré J, Dumas ME, Rizkalla SW, Holmes BA, Zucker JD, Clément K; MICRO-Obes Consortium. Front Physiol. 2019 Feb 5;9:1958. PMID: 30804813
Driver Network as a Biomarker: Systematic integration and network modeling of multi-omics data to derive driver signaling pathways for drug combination prediction.
Huang L, Brunell D, Stephan C, Mancuso J, He B, Thompson TC, Zinner R, Kim J, Davies P, Wong STC.
Bioinformatics. 2019 Feb 15. pii: btz109. [Epub ahead of print]
PMID: 30768150
DrugComboExplorer:
https://github.com/Roosevelt-PKU/drugcombinationprediction
Network-guided prediction of aromatase inhibitor response in breast cancer. Ruffalo M, Thomas R, Chen J, Lee AV, Oesterreich S, Bar-Joseph Z. PLoS Comput Biol. 2019 Feb 11;15(2):e1006730. PMID: 30742607
Conserved Disease Modules Extracted From Multilayer Heterogeneous Disease and Gene Networks for Understanding Disease Mechanisms and Predicting Disease Treatments. Yu L, Yao S, Gao L, Zha Y. Front Genet. 2019 Jan 18;9:745. PMID: 30713550
Predicting drug response of tumors from integrated genomic profiles by deep neural networks.
Chiu YC, Chen HH, Zhang T, Zhang S, Gorthi A, Wang LJ, Huang Y, Chen Y.
BMC Med Genomics. 2019 Jan 31;12(Suppl 1):18.
PMID: 30704458
(Note: I screen out most neural-network papers but thought this might be
of some interest)
Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model. Wei D, Liu C, Zheng X, Li Y. BMC Bioinformatics. 2019 Jan 22;20(1):44. PMID: 30670007
PANOPLY: Omics-Guided Drug Prioritization Method Tailored to an Individual Patient.
Kalari KR, Sinnwell JP, Thompson KJ, Tang X, Carlson EE, Yu J, Vedell PT, Ingle JN, Weinshilboum RM, Boughey JC, Wang L, Goetz MP, Suman V.
JCO Clin Cancer Inform. 2018 Dec;(2):1-11.
PMID: 30652605
Software: http://kalarikrlab.org/Software/Panoply.html and
https://github.com/sinnweja/panoply
Human-Disease Phenotype Map Derived from PheWAS across 38,682 Individuals.
Verma A, Bang L, Miller JE, Zhang Y, Lee MTM, Zhang Y, Byrska-Bishop M, Carey DJ, Ritchie MD, Pendergrass SA, Kim D; DiscovEHR Collaboration.
Am J Hum Genet. 2019 Jan 3;104(1):55-64.
PMID: 30598166
Software: https://www.biomedinfolab.com/software
Network visualization tool:
http://biomedinfolab.com.s3-website-us-east-1.amazonaws.com/
Novel disease syndromes unveiled by integrative multiscale network analysis of diseases sharing molecular effectors and comorbidities. Li H, Fan J, Vitali F, Berghout J, Aberasturi D, Li J, Wilson L, Chiu W, Pumarejo M, Han J, Kenost C, Koripella PC, Pouladi N, Billheimer D, Bedrick EJ, Lussier YA. BMC Med Genomics. 2018 Dec 31;11(Suppl 6):112. PMID: 30598089
Identifying communities from multiplex biological networks by randomized optimization of modularity.
Didier G, Valdeolivas A, Baudot A.
Version 2. F1000Res. 2018 Jul 10 [revised 2018 Jan 1];7:1042.
PMID: 30210790
Software: https://github.com/gilles-didier/MolTi-DREAM
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method. Cui Z, Gao YL, Liu JX, Wang J, Shang J, Dai LY. BMC Bioinformatics. 2019 Jan 5;20(1):5. PMID: 30611214
Large-scale mining disease comorbidity relationships from post-market drug adverse events surveillance data. Zheng C, Xu R. BMC Bioinformatics. 2018 Dec 28;19(Suppl 17):500. PMID: 30591027
From Matrices to Knowledge: Using Semantic Networks to Annotate the Connectome. Kopetzky SJ, Butz-Ostendorf M. Front Neuroanat. 2018 Dec 7;12:111. PMID: 30581382
NeoDTI: neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions.
Wan F, Hong L, Xiao A, Jiang T, Zeng J.
Bioinformatics. 2019 Jan 1;35(1):104-111.
PMID: 30561548
Code: https://github.com/FangpingWan/NeoDTI
Integrating Biological Networks for Drug Target Prediction and Prioritization. Ji X, Freudenberg JM, Agarwal P. Methods Mol Biol. 2019;1903:203-218. PMID: 30547444
Transcriptomic Data Mining and Repurposing for Computational Drug Discovery. Wang Y, Yella J, Jegga AG. Methods Mol Biol. 2019;1903:73-95. PMID: 30547437
Integrating molecular networks with genetic variant interpretation for precision medicine. Capriotti E, Ozturk K, Carter H. Wiley Interdiscip Rev Syst Biol Med. 2018 Dec 12:e1443. [Epub ahead of print] Review. PMID: 30548534
In Silico Target Prediction for Small Molecules. Byrne R, Schneider G. Methods Mol Biol. 2019;1888:273-309. PMID: 30519953
Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach. Hu B, Wang H, Wang L, Yuan W. Molecules. 2018 Dec 4;23(12). pii: E3193. PMID: 30518099