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2008, illustrated edition, ISBN 0805852220, xxiii, 404
In this volume, top experts in the field of delinquency discuss the implications of the findings of the Pittsburgh Youth Study for current conceptualizations... 
Sociology, Social Studies | Juvenile delinquency | Forensic Psychiatry | Criminology & Delinquency | Child & Adolescent Psychiatry & Clinical Psychology | Criminal behavior, Prediction of - Pennsylvania - Pittsburgh | Criminal behavior | Criminal behavior, Prediction of
Book
eJournal
Journal of forecasting, ISSN 0277-6693, 1982
Journal
2013, ISBN 9781461468493, xiii, 600
Book specializes in data analysis with focus on practice of predictive modeling Useful as a guide for practitioners Reader can reproduce all results using R. 
Prediction theory | Mathematical statistics | Mathematical models | Statistics | Statistics and Computing/Statistics Programs | Statistics, general | Statistics for Life Sciences, Medicine, Health Sciences
Book
2017, Third edition., Elsevier insights, ISBN 0444636315, xxi, 559 pages
"A fully updated overview of both historic and recent developments in volcanic eruptions with an extensive collection of illustrations and case studies."... 
Prévision | Activité volcanique | Seismology | Volcanic activity prediction | Volcanism | Sismologie | Earth Sciences | Physics
Book
2010, ISBN 0691138168, 260
An earthquake can strike without warning and wreak horrific destruction and death, whether it’s the cataclysmic 2008 Sichuan quake in China that killed tens of... 
Earthquake prediction | General Science | Seismology & Volcanism | Earth Sciences | SCIENCE | Earthquakes
Book
2008, ISBN 9780470018989, xvii, 249
Assessing Risk in Sex Offenders: A Practitioner's Guide is a handy resource for forensic practitioners responsible for assessing an managing sexual offenders... 
Prevention | Evidence, Expert | Sex offenders | Criminal behavior, Prediction of | Risk assessment | Recidivism | United States | Sex crimes
Book
2012, ISBN 9780195369083, xvi, 272
The study of crime has focused primarily on why particular people commit crime or why specific communities have higher crime levels than others. In The... 
Crime prevention | Crime scenes | Crime analysis | Crime | Environmental aspects | Criminal behavior, Prediction of | Geographical offender profiling | social theory | Crime hot spots | Study of crime | Seattle | Communities | Crime levels | Crime trends | City | Street segments
Book
Journal of earthquake prediction, ISSN 1002-1604, 1992
Journal
Futures research quarterly, ISSN 8755-3317, 1985
Journal
2016, The Munk debates, ISBN 1487001681, viii, 111 pages
"Progress. It is one of the animating concepts of the modern era. From the Enlightenment onwards, the West has had an enduring belief that through the... 
Civilization | Progress | Social prediction | Forecasting
Book
2017, ISBN 9780525955184, viii, 357 pages
Earthquakes. You need to worry about them only if you're in San Francisco, right? Wrong. We have been making enormous changes to subterranean America, and... 
Earthquake prediction | Induced seismicity | United States | Earthquake zones | NATURE / Earthquakes & Volcanoes | NATURE / Natural Disasters | SCIENCE / Earth Sciences / Seismology & Volcanism
Book
Protein Science, ISSN 0961-8368, 12/2002, Volume 11, Issue 12, pp. 2774 - 2791
Methods that predict membrane helices have become increasingly useful in the context of analyzing entire proteomes, as well as in everyday sequence analysis.... 
Av‐Cid, normalized average hydrophobicity scale (Cid 1992) | PSI‐BLAST, position‐specific iterated database search (Altschul et al. 1997) | TrEMBL, translation of the EMBL‐nucleotide database coding DNA to protein sequences (Bairoch and Apweiler 2000) | TopPred2, hydrophobicity‐based membrane helix prediction (von Heijne 1992; Cserzö et al. 1997) | Fauchere, hydrophobic parameter π from the partitioning of N‐acetyl‐amino‐acid amides (Fauchere and Pliska 1983) | BIG, nonidentical merger of SWISS‐PROT (Bairoch and Apweiler 2000) and TrEMBL (Bairoch and Apweiler 2000) and PDB (Berman et al. 2000) | PHDhtm, profile‐based neural network prediction of transmembrane helices (Rost 1996; Rost et al. 1996b) | Eisenberg, normalized consensus hydrophobicity scale (Eisenberg et al. 1984) | TM, transmembrane | MEMSAT, dynamic‐programming based prediction of transmembrane helices (Jones et al. 1994) | PDB, Protein Data Bank of experimentally determined 3D structures of proteins (Bernstein et al. 1977; Berman et al. 2000) | A‐Cid, normalized hydrophobicity scale for α‐proteins (Cid 1992) | GES, hydrophobicity property (Engelman et al. 1986; Prabhakaran 1990) | MaxHom, dynamic programming algorithm for conservation weight‐based multiple sequence alignment (Sander and Schneider 1991) | EM, Solvation free energy (Eisenberg and McLachlan 1986) | bioinformatics | SignalP, signal peptide prediction (Nielsen et al. 1997a) | Ben‐Tal, hydrophobicity scale representing the free energy of transferring an amino acid from water into the center of the hydrocarbon region of a lipid bilayer (Kessel and Ben‐Tal 2002) | TMHMM, transmembrane prediction using cyclic hidden Markov models (Sonnhammer et al. 1998; Krogh et al. 2001) | computational biology | Roseman, solvation‐corrected side‐chain hydropathy (Roseman 1988) | KD, Kyte–Doolittle hydropathy index (Kyte and Doolittle 1982) | PHDpsihtm, divergent profile (PSI‐BLAST)‐based neural network prediction 2002 | Radzicka, transfer free energy from 1‐octanol to water (Radzicka and Wolfenden 1988) | Sweet, optimal matching hydrophobicity (Sweet and Eisenberg 1983) | HMM, hidden Markov model | SWISS‐PROT, database of protein sequences (Bairoch and Apweiler 2000) | TMAP, alignment‐based prediction of transmembrane helices (Persson and Argos 1996) | Wolfenden, hydration potential (Wolfenden et al. 1981) | BLAST, fast sequence alignment method (Altschul and Gish 1996) | Levitt, hydrophobic parameter (Levitt 1976) | multiple alignments, predicting transmembrane helices | proteomes | Lawson, transfer free energy (Lawson et al. 1984) | WW, Wimley–White hydrophobicity scale‐based method (Wimley et al. 1996a,b; White and Wimley 1999; White 2001) | Nakashima, normalized composition of membrane proteins (Nakashima et al. 1990) | SOSUI, hydrophobicity‐ and amphiphilicity‐based transmembrane helix prediction (Hirokawa et al. 1998) | Bull‐Breese, Bull‐Breese hydrophobicity scale (Bull 1974) | SPLIT, transmembrane helix prediction (Juretic et al. 1998) | EVA, server automatically evaluating structure prediction methods (Eyrich et al. 2001a,b) | comparing genomes | TMpred, prediction of transmembrane helices (Hofmann and Stoffel 1993) | Heijne, transfer free energy to lipophilic phase (von Heijne and Blomberg 1979) | TMH, transmembrane helix | HMMTOP, hidden Markov model predicting transmembrane helices (Tusnady and Simon 1998) | Sequence analysis | protein structure prediction | DSSP, program assigning secondary structure (Kabsch and Sander 1983) | META‐PP, internet service allowing access to a variety of bioinformatics tools through one single interface (Eyrich and Rost 2000) | Hopp‐Woods, Hopp‐Woods hydrophilicity value (Hopp and Woods 1981) | Protein structure prediction | Multiple alignments, predicting transmembrane helices | Proteomes | Bioinformatics | Comparing genomes | Computational biology | PROTEIN SECONDARY STRUCTURE | predicting transmembrane helices | BIOCHEMISTRY & MOLECULAR BIOLOGY | ESCHERICHIA-COLI | multiple alignments | ACID SIDE-CHAINS | TOPOLOGY PREDICTION | INTEGRAL MEMBRANE-PROTEINS | BACTERIAL OUTER-MEMBRANE | SARCOPLASMIC-RETICULUM CA2+-ATPASE | STRUCTURAL CLASSIFICATION | sequence analysis | C-TERMINAL DOMAIN | MITOCHONDRIAL PROTEINS | Computational Biology - methods | Algorithms | Animals | Membrane Proteins - chemistry | Protein Structure, Secondary | Sensitivity and Specificity | Models, Molecular | Software | Protein Folding
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