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Full-Text Articles in Computational Biology
Dugesia Japonica Is The Best Suited Of Three Planarian Species For High-Throughput Toxicology Screening, D. Ireland, Veronica Bochenek , '22, Daniel Chaiken , '20, C. Rabeler, Sumi Onoe , '21, Ameet Soni, Eva-Maria S. Collins
Dugesia Japonica Is The Best Suited Of Three Planarian Species For High-Throughput Toxicology Screening, D. Ireland, Veronica Bochenek , '22, Daniel Chaiken , '20, C. Rabeler, Sumi Onoe , '21, Ameet Soni, Eva-Maria S. Collins
Biology Faculty Works
High-throughput screening (HTS) using new approach methods is revolutionizing toxicology. Asexual freshwater planarians are a promising invertebrate model for neurotoxicity HTS because their diverse behaviors can be used as quantitative readouts of neuronal function. Currently, three planarian species are commonly used in toxicology research: Dugesia japonica, Schmidtea mediterranea, and Girardia tigrina. However, only D. japonica has been demonstrated to be suitable for HTS. Here, we assess the two other species for HTS suitability by direct comparison with D. japonica. Through quantitative assessments of morphology and multiple behaviors, we assayed the effects of 4 common solvents (DMSO, …
Lab Practicum For Bias In Algorithms, Ameet Soni, Krista Karbowski Thomason
Lab Practicum For Bias In Algorithms, Ameet Soni, Krista Karbowski Thomason
Digital Humanities Curricular Development
This is a course assignment to demonstrate potential biases encoded in algorithms (this can be linked more specifically to natural language processing, machine learning, or artificial intelligence) using the Word Embedding Association Test. In lab, students will work with programs that demonstrate the usefulness of word embedding algorithms in finding relationships between words. Then, students will use an implementation of the algorithm in "Semantics derived automatically from language corpora contain human-like biases" by Caliskan et al. to detect gender and racial bias encoded in word embeddings. The assignment has students design and run an experiment using the WEAT algorithm to …
Fys: Ethics And Technology (Phil 07/Cpsc 15) Syllabus, Ameet Soni, Krista Karbowski Thomason
Fys: Ethics And Technology (Phil 07/Cpsc 15) Syllabus, Ameet Soni, Krista Karbowski Thomason
Digital Humanities Curricular Development
There has been an accelerated shift in the influence of computing technology and the use of algorithms in our daily lives. With this technology comes serious ethical questions. Philosophers are often well-equipped to wrestle with ethical questions, but less well-equipped to wrestle with questions of technology itself. Computer scientists are well-equipped to deal with the problems and challenges of technology, but less well-equipped to deal with the ethical problems and challenges that technology can pose. In this co-taught course, we bring together the two fields to address ethical questions involving social media, data mining, self-driving cars, artificial intelligence, and other …
Identifying Parkinson’S Patients: A Functional Gradient Boosting Approach, D. S. Dhami, Ameet Soni, D. Page, S. Natarajan
Identifying Parkinson’S Patients: A Functional Gradient Boosting Approach, D. S. Dhami, Ameet Soni, D. Page, S. Natarajan
Computer Science Faculty Works
Parkinson’s, a progressive neural disorder, is difficult to identify due to the hidden nature of the symptoms associated. We present a machine learning approach that uses a definite set of features obtained from the Parkinson’s Progression Markers Initiative (PPMI) study as input and classifies them into one of two classes: PD (Parkinson’s disease) and HC (Healthy Control). As far as we know this is the first work in applying machine learning algorithms for classifying patients with Parkinson’s disease with the involvement of domain expert during the feature selection process. We evaluate our approach on 1194 patients acquired from Parkinson’s Progression …
Structural Characterization Of Human Uch37, E. S. Burgie, C. Bingman, Ameet Soni, G. N. Phillips Jr.
Structural Characterization Of Human Uch37, E. S. Burgie, C. Bingman, Ameet Soni, G. N. Phillips Jr.
Computer Science Faculty Works
Uch37 is a de-ubiquitylating enzyme that is functionally linked with the 26S proteasome via Rpn13, and is essential for metazoan development. Here, we report the X-ray crystal structure of full-length human Uch37 at 2.95 Å resolution. Uch37's catalytic domain is similar to those of all UCH enzymes characterized to date. The C-terminal extension is elongated, predominantly helical and contains coiled coil interactions. Additionally, we provide an initial characterization of Uch37's oligomeric state and identify a systematic error in previous analyses of Uch37 activity. Taken together, these data provide a strong foundation for further analysis of Uch37's several functions.
Probabilistic Ensembles For Improved Inference In Protein-Structure Determination, Ameet Soni, J. Shavlik
Probabilistic Ensembles For Improved Inference In Protein-Structure Determination, Ameet Soni, J. Shavlik
Computer Science Faculty Works
Protein X-ray crystallography — the most popular method for determining protein structures — remains a laborious process requiring a great deal of manual crystallographer effort to interpret low-quality protein images. Automating this process is critical in creating a high-throughput protein-structure determination pipeline. Previously, our group developed ACMI, a probabilistic framework for producing protein-structure models from electron-density maps produced via X-ray crystallography. ACMI uses a Markov Random Field to model the three-dimensional (3D) location of each non-hydrogen atom in a protein. Calculating the best structure in this model is intractable, so ACMI uses approximate inference methods to estimate the optimal structure. …