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Items: 20

1.

An Interpretable Algorithm on Post-injury Health Service Utilization Patterns to Predict Injury Outcomes.

Akbarzadeh Khorshidi H, Hassani-Mahmooei B, Haffari G.

J Occup Rehabil. 2019 Oct 16. doi: 10.1007/s10926-019-09863-0. [Epub ahead of print]

PMID:
31620997
2.

Multi-objective semi-supervised clustering to identify health service patterns for injured patients.

Akbarzadeh Khorshidi H, Aickelin U, Haffari G, Hassani-Mahmooei B.

Health Inf Sci Syst. 2019 Aug 29;7(1):18. doi: 10.1007/s13755-019-0080-6. eCollection 2019 Dec.

PMID:
31523422
3.

Closing the Gap in Surveillance and Audit of Invasive Mold Diseases for Antifungal Stewardship Using Machine Learning.

Baggio D, Peel T, Peleg AY, Avery S, Prayaga M, Foo M, Haffari G, Liu M, Bergmeir C, Ananda-Rajah M.

J Clin Med. 2019 Sep 5;8(9). pii: E1390. doi: 10.3390/jcm8091390.

4.

Early Identification of Undesirable Outcomes for Transport Accident Injured Patients Using Semi-Supervised Clustering.

Khorshidi HA, Haffari G, Aickelin U, Hassani-Mahmooei B.

Stud Health Technol Inform. 2019 Aug 8;266:1-6. doi: 10.3233/SHTI190764.

PMID:
31397293
5.

Analyzing Tumor Heterogeneity by Incorporating Long-Range Mutational Influences and Multiple Sample Data into Heterogeneity Factorial Hidden Markov Model.

Rahman MS, Haffari G.

J Comput Biol. 2019 Sep;26(9):985-1002. doi: 10.1089/cmb.2018.0242. Epub 2019 May 23.

PMID:
31120348
6.

Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods.

Li F, Wang Y, Li C, Marquez-Lago TT, Leier A, Rawlings ND, Haffari G, Revote J, Akutsu T, Chou KC, Purcell AW, Pike RN, Webb GI, Ian Smith A, Lithgow T, Daly RJ, Whisstock JC, Song J.

Brief Bioinform. 2018 Aug 29. doi: 10.1093/bib/bby077. [Epub ahead of print]

PMID:
30184176
7.

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

Song J, Li F, Takemoto K, Haffari G, Akutsu T, Chou KC, Webb GI.

J Theor Biol. 2018 Apr 14;443:125-137. doi: 10.1016/j.jtbi.2018.01.023. Epub 2018 Feb 1.

PMID:
29408627
8.

PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.

Song J, Li F, Leier A, Marquez-Lago TT, Akutsu T, Haffari G, Chou KC, Webb GI, Pike RN, Hancock J.

Bioinformatics. 2018 Feb 15;34(4):684-687. doi: 10.1093/bioinformatics/btx670.

9.

HetFHMM: A Novel Approach to Infer Tumor Heterogeneity Using Factorial Hidden Markov Models.

Rahman MS, Nicholson AE, Haffari G.

J Comput Biol. 2018 Feb;25(2):182-193. doi: 10.1089/cmb.2017.0101. Epub 2017 Oct 16.

PMID:
29035575
10.

Melphalan modifies the bone microenvironment by enhancing osteoclast formation.

Chai RC, McDonald MM, Terry RL, Kovačić N, Down JM, Pettitt JA, Mohanty ST, Shah S, Haffari G, Xu J, Gillespie MT, Rogers MJ, Price JT, Croucher PI, Quinn JMW.

Oncotarget. 2017 Jul 10;8(40):68047-68058. doi: 10.18632/oncotarget.19152. eCollection 2017 Sep 15.

11.

HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology.

Shrestha R, Hodzic E, Sauerwald T, Dao P, Wang K, Yeung J, Anderson S, Vandin F, Haffari G, Collins CC, Sahinalp SC.

Genome Res. 2017 Sep;27(9):1573-1588. doi: 10.1101/gr.221218.117. Epub 2017 Jul 18.

12.

Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.

Kocbek S, Cavedon L, Martinez D, Bain C, Manus CM, Haffari G, Zukerman I, Verspoor K.

J Biomed Inform. 2016 Dec;64:158-167. doi: 10.1016/j.jbi.2016.10.008. Epub 2016 Oct 11.

13.

A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer.

Vollan HK, Rueda OM, Chin SF, Curtis C, Turashvili G, Shah S, Lingjærde OC, Yuan Y, Ng CK, Dunning MJ, Dicks E, Provenzano E, Sammut S, McKinney S, Ellis IO, Pinder S, Purushotham A, Murphy LC, Kristensen VN; METABRIC Group, Brenton JD, Pharoah PD, Børresen-Dale AL, Aparicio S, Caldas C.

Mol Oncol. 2015 Jan;9(1):115-27. doi: 10.1016/j.molonc.2014.07.019. Epub 2014 Aug 8.

14.

An efficient algorithm for upper bound on the partition function of nucleic acids.

Chitsaz H, Forouzmand E, Haffari G.

J Comput Biol. 2013 Jul;20(7):486-94. doi: 10.1089/cmb.2013.0003. Epub 2013 Apr 15.

PMID:
23829650
15.

Scoring relevancy of features based on combinatorial analysis of Lasso with application to lymphoma diagnosis.

Zare H, Haffari G, Gupta A, Brinkman RR.

BMC Genomics. 2013;14 Suppl 1:S14. doi: 10.1186/1471-2164-14-S1-S14. Epub 2013 Jan 21.

16.

DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.

Bashashati A, Haffari G, Ding J, Ha G, Lui K, Rosner J, Huntsman DG, Caldas C, Aparicio SA, Shah SP.

Genome Biol. 2012 Dec 22;13(12):R124. doi: 10.1186/gb-2012-13-12-r124.

17.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Gräf S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S; METABRIC Group, Langerød A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Børresen-Dale AL, Brenton JD, Tavaré S, Caldas C, Aparicio S.

Nature. 2012 Apr 18;486(7403):346-52. doi: 10.1038/nature10983.

18.

The clonal and mutational evolution spectrum of primary triple-negative breast cancers.

Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, Bashashati A, Prentice LM, Khattra J, Burleigh A, Yap D, Bernard V, McPherson A, Shumansky K, Crisan A, Giuliany R, Heravi-Moussavi A, Rosner J, Lai D, Birol I, Varhol R, Tam A, Dhalla N, Zeng T, Ma K, Chan SK, Griffith M, Moradian A, Cheng SW, Morin GB, Watson P, Gelmon K, Chia S, Chin SF, Curtis C, Rueda OM, Pharoah PD, Damaraju S, Mackey J, Hoon K, Harkins T, Tadigotla V, Sigaroudinia M, Gascard P, Tlsty T, Costello JF, Meyer IM, Eaves CJ, Wasserman WW, Jones S, Huntsman D, Hirst M, Caldas C, Marra MA, Aparicio S.

Nature. 2012 Apr 4;486(7403):395-9. doi: 10.1038/nature10933.

19.

Automated analysis of multidimensional flow cytometry data improves diagnostic accuracy between mantle cell lymphoma and small lymphocytic lymphoma.

Zare H, Bashashati A, Kridel R, Aghaeepour N, Haffari G, Connors JM, Gascoyne RD, Gupta A, Brinkman RR, Weng AP.

Am J Clin Pathol. 2012 Jan;137(1):75-85. doi: 10.1309/AJCPMMLQ67YOMGEW.

20.

Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data.

Ding J, Bashashati A, Roth A, Oloumi A, Tse K, Zeng T, Haffari G, Hirst M, Marra MA, Condon A, Aparicio S, Shah SP.

Bioinformatics. 2012 Jan 15;28(2):167-75. doi: 10.1093/bioinformatics/btr629. Epub 2011 Nov 13.

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