Publications

Explore the published research enabled by SPOKE

 

Initial set of 20 form Sergio Baranzini (Jan 23, 2018)

Knowledge graph prediction of unknown adverse drug reactions and validation in electronic health records. Bean DM, Wu H, Iqbal E, Dzahini O, Ibrahim ZM, Broadbent M, Stewart R, Dobson RJB. Sci Rep. 2017 Nov 27;7(1):16416. doi: 10.1038/s41598-017-16674-x. PMID: 29180758

Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project. Alghamdi M, Al-Mallah M, Keteyian S, Brawner C, Ehrman J, Sakr S. PLoS One. 2017 Jul 24;12(7):e0179805. doi: 10.1371/journal.pone.0179805. PMID: 28738059

Learning a Health Knowledge Graph from Electronic Medical Records. Rotmensch M, Halpern Y, Tlimat A, Horng S, Sontag D. Sci Rep. 2017 Jul 20;7(1):5994. doi: 10.1038/s41598-017-05778-z. PMID: 28729710

A study of EMR-based medical knowledge network and its applications. Zhao C, Jiang J, Xu Z, Guan Y. Comput Methods Programs Biomed. 2017 May;143:13-23. doi: 10.1016/j.cmpb.2017.02.016. PMID: 28391811

Integrating personalized gene expression profiles into predictive disease-associated gene pools. Menche J, Guney E, Sharma A, Branigan PJ, Loza MJ, Baribaud F, Dobrin R, Barabási AL. NPJ Syst Biol Appl. 2017 Mar 13;3:10. doi: 10.1038/s41540-017-0009-0. PMID: 28649437

Link prediction in drug-target interactions network using similarity indices. Lu Y, Guo Y, Korhonen A. BMC Bioinformatics. 2017 Jan 17;18(1):39. doi: 10.1186/s12859-017-1460-z. PMID: 28095781

Semantic Health Knowledge Graph: Semantic Integration of Heterogeneous Medical Knowledge and Services. Shi L, Li S, Yang X, Qi J, Pan G, Zhou B. Biomed Res Int. 2017;2017:2858423. doi: 10.1155/2017/2858423. PMID: 28299322

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing. Li C, Zhao P, Sheng VS, Xian X, Wu J, Cui Z. Comput Intell Neurosci. 2017;2017:4092135. doi: 10.1155/2017/4092135. PMID: 28588611

From comorbidities of chronic obstructive pulmonary disease to identification of shared molecular mechanisms by data integration. Gomez-Cabrero D, Menche J, Vargas C, Cano I, Maier D, Barabási AL, Tegnér J, Roca J; Synergy-COPD Consortia. BMC Bioinformatics. 2016 Nov 22;17(Suppl 15):441. doi: 10.1186/s12859-016-1291-3. PMID: 28185567

Tissue Specificity of Human Disease Module. Kitsak M, Sharma A, Menche J, Guney E, Ghiassian SD, Loscalzo J, Barabási AL. Sci Rep. 2016 Oct 17;6:35241. doi: 10.1038/srep35241. PMID: 27748412

Leveraging graph topology and semantic context for pharmacovigilance through twitter-streams. Eshleman R, Singh R. BMC Bioinformatics. 2016 Oct 6;17(Suppl 13):335. PMID: 27766937

Scoring multiple features to predict drug disease associations using information fusion and aggregation. Moghadam H, Rahgozar M, Gharaghani S. SAR QSAR Environ Res. 2016 Aug;27(8):609-28. doi: 10.1080/1062936X.2016.1209241. PMID: 27455069

Endophenotype Network Models: Common Core of Complex Diseases. Ghiassian SD, Menche J, Chasman DI, Giulianini F, Wang R, Ricchiuto P, Aikawa M, Iwata H, Müller C, Zeller T, Sharma A, Wild P, Lackner K, Singh S, Ridker PM, Blankenberg S, Barabási AL, Loscalzo J. Sci Rep. 2016 Jun 9;6:27414. doi: 10.1038/srep27414. PMID: 27278246

Network-based in silico drug efficacy screening. Guney E, Menche J, Vidal M, Barábasi AL. Nat Commun. 2016 Feb 1;7:10331. doi: 10.1038/ncomms10331. PMID: 26831545

ARWAR: A network approach for predicting Adverse Drug Reactions. Rahmani H, Weiss G, Méndez-Lucio O, Bender A. Comput Biol Med. 2016 Jan 1;68:101-8. doi: 10.1016/j.compbiomed.2015.11.005. PMID: 26638149

A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma. Sharma A, Menche J, Huang CC, Ort T, Zhou X, Kitsak M, Sahni N, Thibault D, Voung L, Guo F, Ghiassian SD, Gulbahce N, Baribaud F, Tocker J, Dobrin R, Barnathan E, Liu H, Panettieri RA Jr, Tantisira KG, Qiu W, Raby BA, Silverman EK, Vidal M, Weiss ST, Barabási AL. Hum Mol Genet. 2015 Jun 1;24(11):3005-20. doi: 10.1093/hmg/ddv001. PMID: 25586491

A DIseAse MOdule Detection (DIAMOnD) algorithm derived from a systematic analysis of connectivity patterns of disease proteins in the human interactome. Ghiassian SD, Menche J, Barabási AL. PLoS Comput Biol. 2015 Apr 8;11(4):e1004120. doi: 10.1371/journal.pcbi.1004120. PMID: 25853560

Disease networks. Uncovering disease-disease relationships through the incomplete interactome. Menche J, Sharma A, Kitsak M, Ghiassian SD, Vidal M, Loscalzo J, Barabási AL. Science. 2015 Feb 20;347(6224):1257601. doi: 10.1126/science.1257601. PMID: 25700523

 


Update tbd

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


Update Oct 23, 2019

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


Update Aug 14, 2019

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


Update Jul 11, 2019

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


Update Apr 24, 2019

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)

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


Update Mar 6, 2019

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


Update Jan 10, 2019
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: 30518