Publications
2007
[24] Improved methods for template-matching in electron-density maps using spherical harmonics.
Frank DiMaio, Ameet Soni, George N. Phillips Jr. and Jude W. Shavlik.
In IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 258–265, . Invited for journal publication. [code/data]
[bibtex] [pdf]
[23] Creating protein models from electron-density maps using particle-filtering methods.
Frank DiMaio, Kondrashov, Dmitry A., Bitto, Eduard, Ameet Soni, Craig A. Bingman, George N. Phillips Jr. and Jude W. Shavlik.
In Bioinformatics, Oxford Univ Press, vol. 23, no. 21, pp. 2851–2858, . PMCID: PMC2567142
[bibtex] [pdf] [doi]
2008
[22] Machine learning in structural biology: Interpreting 3D protein images.
Frank DiMaio, Ameet Soni and Jude W. Shavlik.
Chapter in Introduction to Machine Learning and Bioinformatics (S. Mitra, S. Datta, T. Perkins, G. Michailidis, eds.), CRC Press, pp. 237–276, .
[bibtex] [pdf]
2009
[21] Spherical-harmonic decomposition for molecular recognition in electron-density maps.
Frank DiMaio P, Ameet Soni, George N. Phillips Jr. and Jude W. Shavlik.
In International Journal of Data Mining and Bioinformatics, Inderscience Publishers, vol. 3, no. 2, pp. 205–227, . (PDF links to pre-print version) NIHMSID: NIHMS68171. PMCID: PMC2696052.
[bibtex] [pdf] [doi]
2010
[20] Guiding belief propagation using domain knowledge for protein-structure determination.
Ameet Soni, Craig A. Bingman and Jude W. Shavlik.
In Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB), pp. 285–294, . Best Paper Award. [slides] [cached]
[bibtex] [url]
2011
[19] Probabilistic ensembles for improved inference in protein-structure determination.
Ameet Soni and Jude W. Shavlik.
In Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB), pp. 264–273, . Invited for journal publication. [slides] [cached]
[bibtex] [url]
[18] Techniques for Improved Probabilistic Inference in Protein-Structure Determination Via X-Ray Crystallography.
Ameet Soni.
PhD thesis, University of Wisconsin at Madison, . (Also appears as Technical report CS-TR-11-1703) [slides]
[bibtex] [pdf]
2012
[17] Structural characterization of human UCH37.
E. Sethe Burgie, Craig A. Bingman, Ameet Soni and George N. Phillips Jr..
In Proteins: Structure, Function, and Bioinformatics, Wiley Online Library, vol. 80, no. 2, pp. 649–654, .
[bibtex] [url] [doi]
[16] Probabilistic ensembles for improved inference in protein-structure determination.
Ameet and Jude W. Shavlik.
In Journal of Bioinformatics and Computational Biology, vol. 10, no. 01, pp. 1240009, . (By invitation; PMID: 22809310)
[bibtex] [url] [doi]
2013
[15] Conditional random fields for brain tissue segmentation.
*Chris S. Magnano*, Ameet Soni, Sriraam Natarajan and Kunapuli, Gautam.
In Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI) at NIPS, . [poster]
[bibtex] [pdf]
2014
[14] A graphical model approach to ATLAS-free mining of MRI images.
*Chris S. Magnano*, Ameet Soni, Sriraam Natarajan and Kunapuli, Gautam.
In Proceedings of the 2014 SIAM International Conference on Data Mining (SDM), pp. 974–982, . [poster]
[bibtex] [pdf]
[13] A support program for introductory CS courses that improves student performance and retains students from underrepresented groups.
Newhall, Tia, Meeden, Lisa, Danner, Andrew, Ameet Soni, Ruiz, Frances and Wicentowski, Richard.
In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE), pp. 433–438, .
[bibtex] [pdf]
2015
[12] A comprehensive analysis of classification algorithms for cancer prediction from gene expression.
*Raehoon Jeong* and Ameet Soni.
In Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), pp. 525–526, . [poster]
[bibtex] [pdf]
[11] Relational learning with expert advice.
Dileep Viswanathan, Wazalwar, Anurag, Ameet Soni, Jude W. Shavlik and Sriraam Natarajan.
In Proceedings of Text Analysis Conference (TAC) Workshop, .
[bibtex] [pdf]
2016
[10] Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction.
Sriraam Natarajan, Ameet Soni, Wazalwar, Anurag, Dileep Viswanathan and Kersting, Kristian.
Chapter in Solving Large Scale Learning Tasks. Challenges and Algorithms, Springer International Publishing, pp. 331–345, .
[bibtex] [url]
[9] A Comparison of weak supervision methods for knowledge base construction.
Ameet Soni, Dileep Viswanathan, Pachaiyappan, Niranjan and Sriraam Natarajan.
In 5th Workshop on Automated Knowledge Base Construction (AKBC) at NAACL, . [poster]
[bibtex] [pdf]
[8] Learning relational dependency networks for relation extraction.
Ameet Soni, Dileep Viswanathan, Jude W. Shavlik and Sriraam Natarajan.
In Proceedings of the 26th International Conference on Inductive Logic Programming (ILP), . [slides]
[bibtex] [pdf]
[7] Learning relational dependency networks for relation extraction.
Dileep Viswanathan, Ameet Soni, Jude W. Shavlik and Sriraam Natarajan.
In International Workshop on Statistical Relational AI (STARAI) at IJCAI, . (arXiv:1607.00424[cs.AI]) [cached]
[bibtex] [url]
2017
[6] Identifying Parkinson’s Patients: A Functional Gradient Boosting Approach.
Devendra Singh Dhami, Ameet Soni, David Page and Sriraam Natarajan.
In Artificial Intelligence in Medicine (AIME), .
[bibtex] [pdf]
[5] Deep Residual Nets for Improved Alzheimer’s Diagnosis.
*Aly Valliani* and Ameet Soni.
In Proceedings of the 8th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), . [poster]
[bibtex] [pdf]
[4] ACM-SIGBIO Undergraduate Research Highlight.
Mason, Stephanie, Jagodzinski, Filip, Chen, Brian, Nissenson, Michael, Si, Dong, Valliani, Ameet Soni, Fang, Xiaowen, Qiao, Wanli and Shehu, Amarda.
In ACM SIGBioinformatics Rec., ACM, vol. 7, no. 2, pp. 2:1–2:3, .
[bibtex] [url] [doi]
2019
[3] Lab Practicum For Bias In Algorithms.
Ameet Soni and Krista Karbowski Thomason.
.
[bibtex] [url] [doi]
2020
[2] Dugesia japonica is the best suited of three planarian species for high-throughput toxicology screening.
Danielle Ireland, Veronica Bochenek, *Daniel Chaiken*, Christina Rabeler, *Sumi Onoe*, Ameet Soni and Eva-Maria S. Collins.
In Chemosphere, vol. 253, pp. 126718, . [cached]
[bibtex] [url]
[1] A Module for Introducing Ethics in AI: Detecting Bias in Language Models.
Ameet Soni and Krista Karbowski Thomason.
In Proceedings of the 10th Symposium on Educational Advances in Artificial Intelligence (EAAI), . [slides]
[bibtex] [url]
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