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Jesse Eickholt
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2020 – today
- 2022
- [j14]Ming Liu, Qiyu Sun, Dustin E. Brewer
, Thomas M. Gehring, Jesse Eickholt:
An Ornithologist's Guide for Including Machine Learning in a Workflow to Identify a Secretive Focal Species from Recorded Audio. Remote. Sens. 14(15): 3816 (2022) - [c12]Jesse Eickholt, Jennifer L. Weible, Stephanie D. Teasley:
Student-facing Learning Analytics Dashboard: Profiles of Student Use. FIE 2022: 1-9 - 2021
- [j13]Jesse Eickholt
, Matthew R. Johnson
, Patrick Seeling
:
Practical Active Learning Stations to Transform Existing Learning Environments Into Flexible, Active Learning Classrooms. IEEE Trans. Educ. 64(2): 95-102 (2021) - 2020
- [j12]John Smith, Matthew Conover, Natalie Stephenson, Jesse Eickholt, Dong Si, Miao Sun, Renzhi Cao:
TopQA: a topological representation for single-model protein quality assessment with machine learning. Int. J. Comput. Biol. Drug Des. 13(1): 144-153 (2020) - [c11]Jesse Eickholt:
Supporting Instructor Reflection on Employed Teaching Techniques via Multimodal Instructor Analytics. FIE 2020: 1-5 - [c10]Jesse Eickholt, Patrick Seeling:
Pedagogy and Classroom: How Can I Do This in That Space or Does it Even Matter? SIGCSE 2020: 1399
2010 – 2019
- 2019
- [c9]Jesse Eickholt, Lisa Gandy, Patrick Seeling
, Matthew R. Johnson:
Advancing Adoption of Active Learning Pedagogy via New Avenues of Research and Training. FIE 2019: 1-5 - [c8]Patrick Seeling
, Jesse Eickholt, Quentrese Hinton, Matthew R. Johnson:
Low-Cost Active Learning Benefits for Introductory Computer Science Courses. FIE 2019: 1-4 - 2018
- [i1]Jesse Eickholt:
Barriers to Active Learning for Computer Science Faculty. CoRR abs/1808.02426 (2018) - 2017
- [c7]Liling Li, Tyler Danner, Jesse Eickholt, Erin McCann, Kevin Pangle, Nicholas Johnson:
A distributed pipeline for DIDSON data processing. IEEE BigData 2017: 4301-4306 - [c6]Jesse Eickholt, John Roush, Patrick Seeling
, Thiruvarangan Vedantham, Matthew R. Johnson:
Supporting active learning through commodity and open source solutions. FIE 2017: 1-5 - [c5]Patrick Seeling
, Jesse Eickholt:
Levels of active learning in programming skill acquisition: From lecture to active learning rooms. FIE 2017: 1-5 - [c4]Jesse Eickholt, Sharad Shrestha:
Teaching Big Data and Cloud Computing with a Physical Cluster. SIGCSE 2017: 177-181 - [c3]Quentrese Cole, Matthew R. Johnson, Jesse Eickholt:
Creating Economy Active Learning Classrooms for IT Students. SIGITE 2017: 77-82 - 2015
- [j11]Matt Spencer, Jesse Eickholt, Jianlin Cheng
:
A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 12(1): 103-112 (2015) - 2014
- [c2]Jesse Eickholt, Suman Karki:
Adopting the MapReduce framework to pre-train 1-D and 2-D protein structure predictors with large protein datasets. BIBM 2014: 23-29 - 2013
- [j10]Jesse Eickholt, Jianlin Cheng
:
DNdisorder: predicting protein disorder using boosting and deep networks. BMC Bioinform. 14: 88 (2013) - [j9]Jesse Eickholt, Jianlin Cheng
:
A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks. BMC Bioinform. 14(S-14): S12 (2013) - 2012
- [j8]Jesse Eickholt, Jianlin Cheng
:
Predicting protein residue-residue contacts using deep networks and boosting. Bioinform. 28(23): 3066-3072 (2012) - [j7]Jianlin Cheng
, Jilong Li, Zheng Wang, Jesse Eickholt, Xin Deng:
The MULTICOM toolbox for protein structure prediction. BMC Bioinform. 13: 65 (2012) - [j6]Jianlin Cheng
, Jesse Eickholt, Zheng Wang, Xin Deng:
Recursive protein Modeling: a Divide and Conquer Strategy for protein Structure Prediction and its Case Study in CASP9. J. Bioinform. Comput. Biol. 10(3) (2012) - 2011
- [j5]Zheng Wang, Jesse Eickholt, Jianlin Cheng
:
APOLLO: a quality assessment service for single and multiple protein models. Bioinform. 27(12): 1715-1716 (2011) - [j4]Jesse Eickholt, Xin Deng, Jianlin Cheng
:
DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning. BMC Bioinform. 12: 43 (2011) - [c1]Jianlin Cheng
, Zheng Wang, Jesse Eickholt, Xin Deng:
Recursive protein modeling: A divide and conquer strategy for protein structure prediction and its case study in CASP9. BIBM Workshops 2011: 352-357 - 2010
- [j3]Zheng Wang, Jesse Eickholt, Jianlin Cheng
:
MULTICOM: a multi-level combination approach to protein structure prediction and its assessments in CASP8. Bioinform. 26(7): 882-888 (2010)
2000 – 2009
- 2009
- [j2]Xin Deng, Jesse Eickholt, Jianlin Cheng
:
PreDisorder: ab initio sequence-based prediction of protein disordered regions. BMC Bioinform. 10: 436 (2009) - [j1]Allison N. Tegge, Zheng Wang, Jesse Eickholt, Jianlin Cheng
:
NNcon: improved protein contact map prediction using 2D-recursive neural networks. Nucleic Acids Res. 37(Web-Server-Issue): 515-518 (2009)
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