Search Results - "Adhikari, Badri"

A fully open-source framework for deep learning protein real-valued distances by Adhikari, Badri

“…As deep learning algorithms drive the progress in protein structure prediction, a lot remains to be studied at this merging superhighway of deep learning and…”
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DeepSF: deep convolutional neural network for mapping protein sequences to folds by Hou, Jie, Adhikari, Badri, Cheng, Jianlin

“…Abstract Motivation Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence…”
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CONFOLD2: improved contact-driven ab initio protein structure modeling by Adhikari, Badri, Cheng, Jianlin

“…Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction…”
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Thinking beyond Chatbots’ Threat to Education: Visualizations to Elucidate the Writing or Coding Process by Adhikari, Badri

“…Despite overwhelming evidence to the contrary, educational practices continue to be predominantly centered around outcome-oriented approaches. These practices…”
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Analysis of several key factors influencing deep learning-based inter-residue contact prediction by Wu, Tianqi, Hou, Jie, Adhikari, Badri, Cheng, Jianlin

“…Abstract Motivation Deep learning has become the dominant technology for protein contact prediction. However, the factors that affect the performance of deep…”
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Improved protein structure reconstruction using secondary structures, contacts at higher distance thresholds, and non-contacts by Adhikari, Badri, Cheng, Jianlin

“…Residue-residue contacts are key features for accurate de novo protein structure prediction. For the optimal utilization of these predicted contacts in folding…”
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Deep Learning-Based Advances in Protein Structure Prediction by Pakhrin, Subash C., Shrestha, Bikash, Adhikari, Badri, KC, Dukka B.

“…Obtaining an accurate description of protein structure is a fundamental step toward understanding the underpinning of biology. Although recent advances in…”
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Deep learning methods for protein torsion angle prediction by Li, Haiou, Hou, Jie, Adhikari, Badri, Lyu, Qiang, Cheng, Jianlin

“…Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was…”
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DISTEVAL: a web server for evaluating predicted protein distances by Adhikari, Badri, Shrestha, Bikash, Bernardini, Matthew, Hou, Jie, Lea, Jamie

“…Protein inter-residue contact and distance prediction are two key intermediate steps essential to accurate protein structure prediction. Distance prediction…”
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Identification and localization of Tospovirus genus-wide conserved residues in 3D models of the nucleocapsid and the silencing suppressor proteins by Olaya, Cristian, Adhikari, Badri, Raikhy, Gaurav, Cheng, Jianlin, Pappu, Hanu R

“…Tospoviruses (genus Tospovirus, family Peribunyaviridae, order Bunyavirales) cause significant losses to a wide range of agronomic and horticultural crops…”
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A Novel Variant in CMAH Is Associated with Blood Type AB in Ragdoll Cats by Gandolfi, Barbara, Grahn, Robert A, Gustafson, Nicholas A, Proverbio, Daniela, Spada, Eva, Adhikari, Badri, Cheng, Janling, Andrews, Gordon, Lyons, Leslie A, Helps, Chris R

“…The enzyme cytidine monophospho-N-acetylneuraminic acid hydroxylase is associated with the production of sialic acids on cat red blood cells. The cat has one…”
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DEEPCON: protein contact prediction using dilated convolutional neural networks with dropout by Adhikari, Badri

“…Abstract Motivation Exciting new opportunities have arisen to solve the protein contact prediction problem from the progress in neural networks and the…”
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An Improved Integration of Template-Based and Template-Free Protein Structure Modeling Methods and its Assessment in CASP11 by Li, Jilong, Adhikari, Badri, Cheng, Jianlin

“…Most computational protein structure prediction methods are designed for either template based or template-free (ab initio) structure prediction. The…”
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Correction: A Novel Variant in CMAH Is Associated with Blood Type AB in Ragdoll Cats by Gandolfi, Barbara, Grahn, Robert A, Gustafson, Nicholas A, Proverbio, Daniela, Spada, Eva, Adhikari, Badri, Cheng, Janling, Andrews, Gordon, Lyons, Leslie A, Helps, Chris R

“…[This corrects the article DOI: 10.1371/journal.pone.0154973.]…”
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DNCON2: improved protein contact prediction using two-level deep convolutional neural networks by Adhikari, Badri, Hou, Jie, Cheng, Jianlin

“…Abstract Motivation Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted…”
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Scoring protein sequence alignments using deep learning by Shrestha, Bikash, Adhikari, Badri

“…Abstract Motivation A high-quality sequence alignment (SA) is the most important input feature for accurate protein structure prediction. For a protein…”
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New Labeling Methods for Deep Learning Real-Valued Inter-Residue Distance Prediction by Barger, Jacob, Adhikari, Badri

“…Background. Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction-a binary classification…”
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CONFOLD: Residue-residue contact-guided ab initio protein folding by Adhikari, Badri, Bhattacharya, Debswapna, Cao, Renzhi, Cheng, Jianlin

“…ABSTRACT Predicted protein residue–residue contacts can be used to build three‐dimensional models and consequently to predict protein folds from scratch. A…”
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Protein Residue Contacts and Prediction Methods by Adhikari, Badri, Cheng, Jianlin

“…In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein…”
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QAcon: single model quality assessment using protein structural and contact information with machine learning techniques by Cao, Renzhi, Adhikari, Badri, Bhattacharya, Debswapna, Sun, Miao, Hou, Jie, Cheng, Jianlin

“…Protein model quality assessment (QA) plays a very important role in protein structure prediction. It can be divided into two groups of methods: single model…”
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