VLDB 2026 Research / reviewers in the wild / expert
Hin Hark Gan
dblp:13/893
· DBLP profile ↗
4ranked-venue papers
1as first author
0since 2021 · last 2007
0000-0002-0952-1780ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 1 first-authorTheory of computation · 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
3 papers |
Bioinformatics and computational biology · 100% | |
| Theoretical computer science
1 paper |
Computational geometry · 100% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics › RNA structure
RNA secondary structure |
0.1 | 1 | 2007 | RAGPOOLS: RNA-As-Graph-Pools - a web server for assisting the design of structured RNA pools for in vitro selection · Bioinform. 2007 |
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure analysis |
0.1 | 1 | 2007 | RAGPOOLS: RNA-As-Graph-Pools - a web server for assisting the design of structured RNA pools for in vitro selection · Bioinform. 2007 |
Bioinformatics and computational biology › structural bioinformatics › nucleic acid structure analysis
RNA structural bioinformatics |
0.0 | 1 | 2004 | RAG: RNA-As-Graphs database-concepts, analysis, features · Bioinform. 2004 |
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure |
0.0 | 1 | 2004 | Searching for 2D RNA geometries in bacterial genomes · SCG 2004 |
Bioinformatics and computational biology › molecular informatics › cheminformatics
molecular graph representation |
0.0 | 1 | 2004 | RAG: RNA-As-Graphs database-concepts, analysis, features · Bioinform. 2004 |
Computational geometry › geometric matching
geometric pattern matching |
0.0 | 1 | 2004 | Searching for 2D RNA geometries in bacterial genomes · SCG 2004 |
Computational geometry
geometric search |
0.0 | 1 | 2004 | Searching for 2D RNA geometries in bacterial genomes · SCG 2004 |
Methods — techniques the papers use, named apart from their topics
mixing matrix · 0.1in vitro selection · 0.1graph theory · 0.1topological complexity ranking · 0.0graph enumeration · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | RAGPOOLS: RNA-As-Graph-Pools - a web server for assisting the design of structured RNA pools for in vitro selectionabstractSUMMARY: Our RNA-As-Graph-Pools (RagPools) web server offers a theoretical companion tool for RNA in vitro selection and related problems. Specifically, it suggests how to construct RNA sequence/structure pools with user-specified properties and assists in analyzing resulting distributions. This utility follows our recently developed approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a 'mixing matrix' approach combined with a graph theory analysis of RNA secondary-structure space; the mixing matrix specifies nucleotide transition rates, and graph theory links sequences to simple graphical objects representing RNA motifs. The companion RagPools web server ('Designer' component) provides optimized starting sequences, mixing matrices and associated weights in response to a user-specified target pool structure distribution. In addition, RagPools ('Analyzer' component) analyzes the motif distribution of pools generated from user-specified starting sequences and mixing matrices. Thus, RagPools serves as a guide to researchers who aim to synthesize RNA pools with desired properties and/or experiment in silico with various designs by our approach. AVAILABILITY: The web server is accessible on the web at http://rubin2.biomath.nyu.edu Namhee Kim, Jin Sup Shin, Shereef Elmetwaly, Hin Hark Gan, Tamar Schlick |
Bioinform. | 4 |
| 2004 | Searching for 2D RNA geometries in bacterial genomesabstractArticle Share on Searching for 2D RNA geometries in bacterial genomes Authors: Uri Laserson New York University, New York, NY New York University, New York, NYView Profile , Hin Hark Gan New York University, New York, NY New York University, New York, NYView Profile , Tamar Schlick New York University, New York, NY New York University, New York, NYView Profile Authors Info & Claims SCG '04: Proceedings of the twentieth annual symposium on Computational geometryJune 2004 Pages 373–377https://doi.org/10.1145/997817.997819Published:08 June 2004Publication History 5citation310DownloadsMetricsTotal Citations5Total Downloads310Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access Uri Laserson, Hin Hark Gan, Tamar Schlick |
SCG | 2 |
| 2004 | RAG: RNA-As-Graphs database-concepts, analysis, featuresabstractMOTIVATION: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire. RESULTS: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as 'tree graphs' and other RNAs, including pseudoknots, as general 'dual graphs'. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs. AVAILABILITY: The database is accessible on the web at http://monod.biomath.nyu.edu/rna Hin Hark Gan, Daniela Fera, Julie Zorn, Nahum Shiffeldrim, Michael Tang, Uri Laserson, Namhee Kim, Tamar Schlick |
Bioinform. | 1 |
| 2004 | RAG: RNA-As-Graphs web resourceabstractBACKGROUND: The proliferation of structural and functional studies of RNA has revealed an increasing range of RNA's structural repertoire. Toward the objective of systematic cataloguing of RNA's structural repertoire, we have recently described the basis of a graphical approach for organizing RNA secondary structures, including existing and hypothetical motifs. DESCRIPTION: We now present an RNA motif database based on graph theory, termed RAG for RNA-As-Graphs, to catalogue and rank all theoretically possible, including existing, candidate and hypothetical, RNA secondary motifs. The candidate motifs are predicted using a clustering algorithm that classifies RNA graphs into RNA-like and non-RNA groups. All RNA motifs are filed according to their graph vertex number (RNA length) and ranked by topological complexity. CONCLUSIONS: RAG's quantitative cataloguing allows facile retrieval of all classes of RNA secondary motifs, assists identification of structural and functional properties of user-supplied RNA sequences, and helps stimulate the search for novel RNAs based on predicted candidate motifs. Daniela Fera, Namhee Kim, Nahum Shiffeldrim, Julie Zorn, Uri Laserson, Hin Hark Gan, Tamar Schlick |
BMC Bioinform. | 6 |