Stem protein$ (all stems)

101 papers:

ICML-2015-PachecoS #approach #pseudo

Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach (JP, EBS), pp. 2200–2208.

DAC-2014-XueQBYT #analysis #framework #manycore #scalability

Disease Diagnosis-on-a-Chip: Large Scale Networks-on-Chip based Multicore Platform for Protein Folding Analysis (YX, ZQ, PB, FY, CYT), p. 6.

ICML-c1-2014-ZhouT #generative #network #predict #probability

Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction (JZ, OGT), pp. 745–753.

ICML-c2-2014-McGibbonRSKP #comprehension #markov #modelling

Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models (RM, BR, MS, GK, VSP), pp. 1197–1205.

ICPR-2014-GienTCL #fuzzy #learning #multi #predict

Dual Fuzzy Hypergraph Regularized Multi-label Learning for Protein Subcellular Location Prediction (JG, YYT, CLPC, YL), pp. 512–516.

ICPR-2014-OkadaFWP #analysis #random

Microenvironment-Based Protein Function Analysis by Random Forest (KO, LF, MW, DP), pp. 3138–3143.

MLDM-2014-WangLK #concurrent #data mining #mining

Applications of Concurrent Sequential Patterns in Protein Data Mining (CW, JL, MK), pp. 243–257.

SIGMOD-2013-LapeineHHG #data analysis #interactive #mobile #query

Mobile interaction and query optimizationin a protein-ligand data analysis system (ML, KGH, EH, NMG), pp. 1291–1292.

KDD-2013-TabeiKKY #constraints #scalability #similarity

Succinct interval-splitting tree for scalable similarity search of compound-protein pairs with property constraints (YT, AK, MK, YY), pp. 176–184.

SAC-2013-NardelliTB #behaviour

Cross-lattice behavior of general ACO folding for proteins in the HP model (MN, LT, AB), pp. 1320–1327.

ICPR-2012-CantoniOFP #analysis

Structural analysis of protein Secondary Structure by GHT (VC, OO, AF, AP), pp. 1767–1770.

ICPR-2012-SuryantoJF #3d #image #multi #similarity #visualisation

Protein structure similarity based on multi-view images generated from 3D molecular visualization (CHS, SJ, KF), pp. 3447–3451.

KDD-2012-YuDRZY #classification #multi #predict

Transductive multi-label ensemble classification for protein function prediction (GXY, CD, HR, GZ, ZY), pp. 1077–1085.

KDIR-2012-BressoGDNS #3d #concept analysis #learning #relational

Formal Concept Analysis for the Interpretation of Relational Learning Applied on 3D Protein-binding Sites (EB, RG, MDD, AN, MST), pp. 111–120.

MLDM-2012-SinghCS #approach #hybrid #performance #recognition #using

A Hybrid Approach to Increase the Performance of Protein Folding Recognition Using Support Vector Machines (LS, GC, DS), pp. 660–668.

SAC-2012-MenorPB #kernel #predict #probability #using

Probabilistic prediction of protein phosphorylation sites using kernel machines (MM, GP, KB), pp. 1393–1398.

ICML-2011-PengHMU #set

Convex Max-Product over Compact Sets for Protein Folding (JP, TH, DAM, RU), pp. 729–736.

KDIR-2011-BicegoFBCM #grid #protocol

An Innovative Protocol for Comparing Protein Binding Sites via Atomic Grid Maps (MB, ADF, PB, AC, VM), pp. 413–422.

SAC-2011-ChamorroDA #predict

Evolutionary computation for the prediction of secondary protein structures (AEMC, FD, JSAR), pp. 1082–1087.

SAC-2011-TranCS #permutation #predict

Prediction of permuted super-secondary structures in β-barrel proteins (VDT, PC, JMS), pp. 110–111.

ICPR-2010-SakarKSG #clustering #feature model #predict

Prediction of Protein Sub-nuclear Location by Clustering mRMR Ensemble Feature Selection (COS, OK, HS, FG), pp. 2572–2575.

KDIR-2010-CamposMO #random #recognition #using

Recognition of Gene/Protein Names using Conditional Random Fields (DC, SM, JLO), pp. 275–280.

KDIR-2010-Molokov #combinator #identification

Application of Combinatorial Methods to Protein Identification in Peptide Mass Fingerprinting (LM), pp. 307–313.

SAC-2010-AminBJ #framework #interactive #performance

A cytoscape based framework for efficient sub-graph isomorphic protein-protein interaction motif lookup (MSA, AB, HMJ), pp. 1572–1576.

HPDC-2010-HigdonLK #functional #modelling #sequence #similarity

Modeling sequence and function similarity between proteins for protein functional annotation (RH, BL, EK), pp. 499–502.

ICLP-J-2010-PaluDFP #assembly

CLP-based protein fragment assembly (ADP, AD, FF, EP), pp. 709–724.

ICML-2009-KamisettyL #approach #assessment #quality

A Bayesian approach to protein model quality assessment (HK, CJL), pp. 481–488.

KDIR-2009-PaquetV #2d #3d #multi #product line #realtime

Finding Protein Family Similarities in Real Time through Multiple 3D and 2D Representations, Indexing and Exhaustive Searching (EP, HLV), pp. 127–133.

SIGIR-2009-YangGH #identification #information retrieval #problem

Protein identification as an information retrieval problem (YY, SG, AH), pp. 752–753.

SAC-2009-CorderoVB #clustering #framework

A new protein motif extraction framework based on constrained co-clustering (FC, AV, MB), pp. 776–781.

SAC-2009-RekapalliHZ #identification #named #scalability

HSP-HMMER: a tool for protein domain identification on a large scale (BR, CH, IBZ), pp. 766–770.

CASE-2008-GeorgievA

Two-stage robotic crystal mounting of protein crystals for X-ray data collection (AG, PKA), pp. 1019–1024.

CASE-2008-RussoMCK #automation #modelling #petri net

Petri net modeling and automated system control of protein crystallization experimentation in drug discovery (MFR, SM, MHC, HK), pp. 906–911.

VLDB-2008-PaquetV #database #named #perspective

Capri/MR: exploring protein databases from a structural and physicochemical point of view (EP, HLV), pp. 1504–1507.

ICML-2008-AllauzenMT #kernel #predict #sequence

Sequence kernels for predicting protein essentiality (CA, MM, AT), pp. 9–16.

ICPR-2008-KuksaHP #detection #kernel #performance

Fast protein homology and fold detection with sparse spatial sample kernels (PPK, PHH, VP), pp. 1–4.

SAC-2008-AntonyBHP #approach #biology #interactive #mining #using #validation

Computational approach to biological validation of protein-protein interactions discovered using literature mining (AA, SB, SH, MJP), pp. 1302–1306.

ICML-2007-BhattacharyaBC #classification #kernel

Structural alignment based kernels for protein structure classification (SB, CB, NRC), pp. 73–80.

KDD-2007-PandeySGGK #case study #interactive #network #predict

Association analysis-based transformations for protein interaction networks: a function prediction case study (GP, MS, RG, TG, VK), pp. 540–549.

MLDM-2007-Kertesz-FarkasKP #classification #equivalence #learning

Equivalence Learning in Protein Classification (AKF, AK, SP), pp. 824–837.

DLT-2006-PaunP

P Systems with Proteins on Membranes and Membrane Division (AP, BP), pp. 292–303.

CIKM-2006-MarsoloPR #query #using

Structure-based querying of proteins using wavelets (KM, SP, KR), pp. 24–33.

ICML-2006-EngelhardtJB #predict #visual notation

A graphical model for predicting protein molecular function (BEE, MIJ, SEB), pp. 297–304.

ICPR-v1-2006-WenGL #clustering #detection #markov #monte carlo

Markov Chain Monte Carlo Data Association for Merge and Split Detection in Tracking Protein Clusters (QW, JG, KLP), pp. 1030–1033.

ICPR-v3-2006-BaldacciGLR #approach #clustering

A Template-Matching Approach for Protein Surface Clustering (LB, MG, AL, SR), pp. 340–343.

ICPR-v3-2006-BouchaffraT #markov #recognition #using

Protein Fold Recognition using a Structural Hidden Markov Model (DB, JT), pp. 186–189.

KDD-2006-ChenHLN #interactive #named #network

NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs (JC, WH, MLL, SKN), pp. 106–115.

SAC-2006-ChenPSW

An integrated computational proteomics method to extract protein targets for Fanconi Anemia studies (JYC, SLP, CS, MW), pp. 173–179.

SAC-2006-ChongL #using

An extension of dead end elimination for protein side-chain conformation using merge-decoupling (KFC, HWL), pp. 195–199.

SAC-2006-CraigL #classification #learning #using

Protein classification using transductive learning on phylogenetic profiles (RAC, LL), pp. 161–166.

SAC-2006-MerschmannP #approach #classification

A Bayesian approach for protein classification (LHdCM, AP), pp. 200–201.

SAC-2006-PaluPHL #3d #approach #constraints #logic programming #scalability

A constraint logic programming approach to 3D structure determination of large protein complexes (ADP, EP, JH, YL), pp. 131–136.

SAC-2006-WuH #interactive #mining #network

Mining and analyzing the topological structure of protein-protein interaction networks (DDW, XH), pp. 185–189.

SIGMOD-2005-MurphyF #database #image #research

Research issues in protein location image databases (RFM, CF), pp. 966–967.

CIAA-J-2004-HanMZ05 #approach #automaton #database #sequence

An automata approach to match gapped sequence tags against protein database (YH, BM, KZ), pp. 487–497.

ICML-2005-IeWNL #adaptation #multi #recognition #using

Multi-class protein fold recognition using adaptive codes (EI, JW, WSN, CSL), pp. 329–336.

ICML-2005-LiuXC #graph #predict #using

Predicting protein folds with structural repeats using a chain graph model (YL, EPX, JGC), pp. 513–520.

ICML-2005-WangS #classification #kernel

New kernels for protein structural motif discovery and function classification (CW, SDS), pp. 940–947.

MLDM-2005-KurganH #approach #feature model #predict #sequence

Prediction of Secondary Protein Structure Content from Primary Sequence Alone — A Feature Selection Based Approach (LAK, LH), pp. 334–345.

PPDP-2005-PaluDP #heuristic #optimisation #parallel #predict

Heuristics, optimizations, and parallelism for protein structure prediction in CLP(FD) (ADP, AD, EP), pp. 230–241.

SAC-2005-DalkilicS #analysis #design #evaluation

Design and evaluation of CATPA: curation and alignment tool for protein analysis (MMD, AS), pp. 190–194.

SAC-2005-DavidssonHS #predict #sequence

Comparing approaches to predict transmembrane domains in protein sequences (PD, JH, KS), pp. 185–189.

SAC-2005-HuP #3d #complexity #parametricity

Volume fractal dimensionality: a useful parameter for measuring the complexity of 3D protein spatial structures (MH, QP), pp. 172–176.

SAC-2005-PlakeHL #interactive #optimisation #syntax

Optimizing syntax patterns for discovering protein-protein interactions (CP, JH, UL), pp. 195–201.

HPDC-2005-GrothMFWZM #empirical #using

Recording and using provenance in a protein compressibility experiment (PTG, SM, WF, SCW, KPZ, LM), pp. 201–208.

CIAA-2004-HanMZ #approach #automaton #database #sequence

An Automata Approach to Match Gapped Sequence Tags Against Protein Database (YH, BM, KZ), pp. 167–177.

ICALP-2004-FuW #algorithm

A 2O(n1-(1/d)log n) Time Algorithm for d-Dimensional Protein Folding in the HP-Model (BF, WW), pp. 630–644.

CIKM-2004-AghiliAA #geometry #using

Protein structure alignment using geometrical features (SAA, DA, AEA), pp. 148–149.

ICML-2004-ChuGW #predict #visual notation

A graphical model for protein secondary structure prediction (WC, ZG, DLW).

ICPR-v2-2004-ColleP #predict #process

Relaxation Labeling Processes for Protein Secondary Structure Prediction (GC, MP), pp. 355–358.

ICPR-v2-2004-VijayaMS #classification #clustering #performance #sequence

An Efficient Technique for Protein Sequence Clustering and Classification (PAV, MNM, DKS), pp. 447–450.

SIGIR-2004-LiuCKG #predict

Context sensitive vocabulary and its application in protein secondary structure prediction (YL, JGC, JKS, VG), pp. 538–539.

SAC-2004-JiangWM #network #thread

Protein threading with residue-environment matching by artificial neural networks (NJ, WXW, IM), pp. 209–210.

SAC-2004-WeisserK #identification #metric #sequence #statistics #using

Identification of fundamental building blocks in protein sequences using statistical association measures (DKW, JKS), pp. 154–161.

ICLP-2004-PaluDF #simulation

Protein Folding Simulation in CCP (ADP, AD, FF), pp. 452–453.

ICEIS-v2-2003-VogiatzisFP #information management #predict

The Protein Structure Prediction Module of the Prot-Grid Information System (DV, DF, GAP), pp. 372–378.

KDD-2003-SheCWEGB #predict

Frequent-subsequence-based prediction of outer membrane proteins (RS, FC, KW, ME, JLG, FSLB), pp. 436–445.

SAC-2003-CanWWS #3d #java #named #performance #using #visualisation

FPV: Fast Protein Visualization Using Java 3D (TC, YW, YFW, JS), pp. 88–95.

SAC-2003-NgZT #approach #interactive

Integrative Approach for Computationally Inferring Protein Domain Interactions (SKN, ZZ, SHT), pp. 115–121.

SAC-2003-VulloF #approach #predict #recursion

A Recursive Connectionist Approach for Predicting Disulfide Connectivity in Proteins (AV, PF), pp. 67–71.

ICLP-2003-BackofenW #approach #constraints #modelling #predict

A Constraint-Based Approach to Structure Prediction for Simplified Protein Models That Outperforms Other Existing Methods (RB, SW), pp. 49–71.

VLDB-2002-HammelP #sequence

Searching on the Secondary Structure of Protein Sequences (LH, JMP), pp. 634–645.

ICPR-v2-2002-TaoIS

Extracting Fractal Features for Analyzing Protein Structure (YT, TRI, JCS), pp. 482–485.

SAC-2002-DinakarpandianK #predict #proximity

BlOMIND-protein property prediction by property proximity profiles (DD, VK), pp. 168–172.

MLDM-2001-MottlDSKM #classification #pattern matching #pattern recognition #recognition

Featureless Pattern Recognition in an Imaginary Hilbert Space and Its Application to Protein Fold Classification (VM, SD, OS, CAK, IBM), pp. 322–336.

SAC-2001-DeermanLP #algorithm #predict #problem #search-based

Linkage-learning genetic algorithm application to the protein structure prediction problem (KRD, GBL, RP), pp. 333–339.

SAC-2001-Grigoriev #identification

Computational structural genomics: identifying protein targets for structural studies (IVG), pp. 41–45.

HPDC-2001-NatrajanFHGWCB #case study #experience #grid #using

Studying Protein Folding on the Grid: Experiences Using CHARMM on NPACI Resources under Legion (AN, ADF, MAH, ASG, NWD, MC, CLBI), pp. 14–21.

KDD-2000-KingKCD #data mining #functional #mining #predict #sequence #using

Genome scale prediction of protein functional class from sequence using data mining (RDK, AK, AC, LD), pp. 384–389.

KDD-2000-WangMSW #biology #case study #classification #data mining #mining #network #sequence

Application of neural networks to biological data mining: a case study in protein sequence classification (JTLW, QM, DS, CHW), pp. 305–309.

ICALP-1999-Clote #markov

Protein Folding, the Levinthal Paradox and Rapidly Mixing Markov Chains (PC), pp. 240–249.

SIGMOD-1998-ChenWZ #query

A Protein Patent Query System Powered By Kleisli (JC, LW, LZ), pp. 593–595.

STOC-1998-CrescenziGPPY #complexity #on the

On the Complexity of Protein Folding (Extended Abstract) (PC, DG, CHP, AP, MY), pp. 597–603.

SAC-1996-RamamurthyYG #generative #on the #parallel #scalability

On the scalability of parallel triplet generation for protein crystallography (SR, BWY, CG), pp. 344–352.

STOC-1995-HartI #performance

Fast protein folding in the hydrophobic-hydrophilic model within three-eights of optimal (Extended Abstract) (WEH, SI), pp. 157–168.

ICML-1995-CrawH #network #refinement

Protein Folding: Symbolic Refinement Competes with Neural Networks (SC, PH), pp. 133–141.

KDD-1995-TsumotoT95a #automation #component #functional #representation #sequence #set

Automated Discovery of Functional Components of Proteins from Amino-Acid Sequences Based on Rough Sets and Change of Representation (ST, HT), pp. 318–324.

ICML-1994-AbeM #predict #probability

A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars (NA, HM), pp. 3–11.

CADE-1994-BaumgartnerF94a #interface #named #proving

PROTEIN: A PROver with a Theory Extension INterface (PB, UF), pp. 769–773.

SEKE-1992-SubramaniamTHRR #design #information management #prototype #type system

Knowledge Engineering for Protein Structure and Motifs: Design of a Prototype System (SS, DKT, KH, HR, LAR), pp. 420–435.

ICLP-1986-RawlingsTNFS86 #prolog #using

Using Prolog to Represent and Reason about Protein Structure (CJR, WRT, JN, JF, MJES), pp. 536–543.