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Tod D. Romo

dblp:15/4119 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2007
0000-0003-3513-8248ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3Applied, interdisciplinary, general and emerging computing · 2Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%
Human-computer interaction and pervasive computing
1 paper
User interface design and tools · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
structural biology
0.112007
Crystallographic protein model-building on the web · Bioinform. 2007
Bioinformatics and computational biology › structural biology
protein crystallography
0.112005
TEXTAL™: Automated Crystallographic Protein Structure Determination · AAAI 2005
Bioinformatics and computational biology › structural bioinformatics
protein structure determination
0.112005
TEXTAL™: Automated Crystallographic Protein Structure Determination · AAAI 2005

Methods — techniques the papers use, named apart from their topics

automated electron density map interpretation · 0.1
YearPublicationVenuePosition
2007 Crystallographic protein model-building on the web
abstract
UNLABELLED: X-ray crystallography is the most widely used method to determine the 3D structure of protein molecules. One of the most difficult steps in protein crystallography is model-building, which consists of constructing a backbone and then amino acid side chains into an electron density map. Interpretation of electron density maps represents a major bottleneck in protein structure determination pipelines, and thus, automated techniques to interpret maps can greatly improve the throughput. We have developed WebTex, a simple and yet powerful web interface to TEXTAL, a program that automates this process of fitting atoms into electron density maps. TEXTAL can also be downloaded for local installation. AVAILABILITY: Web interface, downloadable binaries and documentation at http://textal.tamu.edu
Kreshna Gopal, Erik McKee, Tod D. Romo, Reetal Pai, Jacob N. Smith, James C. Sacchettini, Thomas R. Ioerger
Bioinform.3
2005 TEXTAL™: Automated Crystallographic Protein Structure Determination
Kreshna Gopal, Tod D. Romo, Erik McKee, Kevin Childs, Lalji Kanbi, Reetal Pai, Jacob N. Smith, James C. Sacchettini, Thomas R. Ioerger
AAAI2
2004 Efficient retrieval of electron density patterns for modeling proteins by X-ray crystallography
abstract
Inefficient case retrieval is a major problem in many case-based reasoning systems, especially when case matching is expensive and the case-base is large. In this paper, we present a two-phase approach where an inexpensive feature-based method is used to jind a set of potential matches and a more expensive and accurate case matching method is used to make the jinal selection. This approach has been successfully employed in TEXTALTM, a system that retrieves previously solved 3D patterns of electron density from a database to determine the structure of proteins. Electron density patterns are characterized by numeric features and an appropriate distance measure is used to efficiently jilter good matches through an exhaustive search of the database. These matches are then examined using a computationally expensive density correlation procedure based on jinding an optimal superposition between 3D patterns. We provide an empirical and theoretical analysis of some of the keys issues related to this method. In particular, we dejine a model for estimating how approximate various featurebased similarity measures are (relative to an objective matching metric), and determine its relation to the number of cases that should be jiltered from a given database to make the approach effective.
Kreshna Gopal, Tod D. Romo, James C. Sacchettini, Thomas R. Ioerger
ICMLA2
2003 TEXTALTM: Artificial Intelligence Techniques for Automated Protein Structure Determination
Kreshna Gopal, Reetal Pai, Thomas R. Ioerger, Tod D. Romo, James C. Sacchettini
IAAI4