Raport de cercetare - Lorentz JÄNTSCHI

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81 0.88 0.58 2.61 2.39 146 82 0.82 0.57 2.27 2.31 156 83 0.79 0.55 1.98 Matricea valorilor coeficientului de corelaţie: 2.23 167 ρ(XX) d_IP d_IR D_Cr d_RSD d_Volum d_IP 1 0.9965 0.742 0.9958 0.8395 d_IR 1 0.7462 0.9985 0.8461 d_Cr 1 0.7455 0.7047 d_RSD 1 0.842 d_Volum Matricea valorilor parametrului testului Student: 1 t(XX) d_IP d_IR d_Cr d_RSD d_Volum d_IP INF 35.4911 2.7981 32.6577 4.2139 d_IR INF 2.8444 53.8965 4.3495 d_Cr INF 2.8362 2.4278 d_RSD INF 4.2657 d_Volum Matricea probabilitatiilor (p-value): INF pt(XX) d_IP d_IR d_Cr d_RSD d_Volum d_IP 0 4.08E-18 0.0119 1.79E-17 5.22E-04 d_IR 0 0.0108 2.37E-21 3.86E-04 d_Cr 0 0.011 0.0259 d_RSD 0 4.65E-04 d_Volum 0 Valorile lui p-value colorate în albastru sunt semnificative (
30 1.02 0.63 1.75 2.67 160 31 1.14 0.68 1.4 2.74 201 53 0 0 0 0 0 54 0 0 1.5 0 0 55 1 0.69 1.89 2.77 187 56 1.2 0.69 1.61 3.24 133 57 1.27 0.7 1.75 3.33 160 79 0.97 0.61 5.49 2.57 160 80 0.97 0.6 2.81 2.47 137 81 0.88 0.58 2.61 2.39 146 82 0.82 0.57 2.27 2.31 156 83 0.79 0.55 1.98 2.23 167 Matricea valorilor coeficientului de corelaţie Spearman semi-cantitativ: λ(XX) d_IP d_IR d_Cr d_RSD d_Volum d_IP 1 0.9744 0.2626 0.9963 0.7814 d_IR 1 0.0423 0.9779 0.8604 d_Cr 1 0.263 0.2756 d_RSD 1 0.7805 d_Volum Matricea valorilor parametrului testului Student: 1 t(XX) d_IP d_IR d_Cr d_RSD d_Volum d_IP INF 12.8365 0.2932 34.7766 3.2709 d_IR INF 0.0076 13.8793 4.6713 d_Cr INF 0.2941 0.3232 d_RSD INF 3.2588 d_Volum INF Matricea probabilitaţiilor (p-value): pt(XX) d_IP d_IR d_Cr d_RSD d_Volum d_IP 0 1.69E-10 0.772 5.86E-18 4.25E-03 d_IR 0 0.994 4.69E-11 1.90E-04 d_Cr 0 0.7721 0.7502 d_RSD 0 4.36E-03 d_Volum 0 Valorile lui p-value colorate în albastru sunt semnificative (
Page 1 and 2: Raport de cercetare - lucrare în e
Page 3 and 4: 2. Scop şi obiective Scopul proiec
Page 5 and 6: abordare integrată în căutarea r
Page 7 and 8: • cu acces parţial restricţiona
Page 9 and 10: 2007A1. Planificarea activităţilo
Page 11 and 12: 2 Y = 0.852 -1 =a+bX -1 (Y -1 -a-bX
Page 13 and 14: PCB128 136.38 -3.4116 0.7761 PCB129
Page 15 and 16: ISDmsHt lADrtHg Y Equation Residue
Page 21 and 22: Tabelul următor prezintă sintetic
Page 23: d_RSD INF 2.6057 d_Volum Matricea p
Page 27 and 28: Matricea valorilor coeficientului d
Page 29 and 30: evaluare sistematică pentru identi
Page 31 and 32: introductivă în subiectul prezent
Page 33 and 34: Studio (al companiei Accelrys) a pe
Page 35 and 36: Setting the weights equal to 1 give
Page 37 and 38: ÷ Lucrare: Quantitative structure-
Page 39 and 40: compound ranking in the database. A
Page 41 and 42: vectors based on the cloning strate
Page 43 and 44: "Recent Advances in Synthesis and C
Page 45 and 46: will be highly inactive, moderately
Page 47 and 48: Publication Frequency: 8 issues per
Page 49 and 50: of strand breaks and when they do o
Page 51 and 52: ibonucleotide reductase Journal of
Page 53 and 54: scenarios are to be compared, e.g.
Page 55 and 56: hydrazones • ligand-based drug de
Page 57 and 58: modalitatea de culegere, colectare
Page 59 and 60: ÷ Transversală: studierea unui e
Page 61 and 62: 9 10 12 8 1 4 3 2 2 15 8 5 4 3 4 8
Page 63 and 64: 2 1 1 2 3 2 0 1 4 3 2 2 5 4 2 0 6 5
Page 65 and 66: 10 1 0 1 0 1 1 1 1 0 1 0 11 0 0 0 1
Page 67 and 68: 12 0 0 0 1 0 0 L12 Factori (nivele)
Page 69 and 70: 3 1 ×2 4 A(3) B(2) C(2) D(2) E(2)
Page 71 and 72: 9 8 0 2 2 2 1 1 10 9 1 2 1 1 0 0 11
Page 73 and 74: 7 1 4 1 1 2 4 8 2 2 3 4 1 1 9 3 2 1
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1 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0
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11 10 9 9 4 11 12 11 8 10 3 13 13 1
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÷ Endorelaţie binară (`2-e-r`):
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muchiei e); ponderile pentru vârfu
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ale grafului; între numărul de fe
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Detur d5,1=3; d5,2=3; d5,3=2; d5,4=
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3 1 024220000 1145 4 0 022100222 11
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o ΣA(·) 2 : 231; o Matricea: De 1
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(10, 3) [10, 6, 3] {7, 10, 11} (3,
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11 0.250 0.333 0.333 0.333 0.250 0.
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(5, 11) [5, 1, 2, 3, 6, 9, 8, 7, 11
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(1, 11) [1, 2, 3, 6, 10, 11] {1, 4,
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(9, 11) [9, 8, 7, 11] {1, 2, 3, 4,
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(3, 8) [3, 6, 10, 11, 7, 8] {1, 2,
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6 0.167 0.167 0.167 0.167 0.167 0.0
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5 0.500 0.500 0.500 0.500 0.000 0.3
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Tabelul 10. Matricea caracteristic
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10 6 7 8 9 10 11 11 6 7 8 9 10 11 6
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Astfel, adaptând principiul I al t
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Din formula sa de definiţie dS = d
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produsul final al întregului lanţ
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Tabelul 16. Cât de dulci sunt zaha
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÷ CSLS; ÷ Cyberlipid Center; ÷ D
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÷ STING Millenium Suite; ÷ wwPDB;
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pentru care algoritmul performează
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scopul maximizării randamentului d
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solului, calitatea vremii, manageme
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Fragmentation criteria Fragment of
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o Se încrucişează Genotip1 cu Ge
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Measures of Disease in Health Resea
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Generarea întâmplătoare stratifi
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Functional Networks Noelia Sánchez
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o SVMs application to protein secon
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Meta-learning for Algorithm Recomme
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Similarity Assessment with PDR-FP
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• Representations of a molecular
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Introduction - Non HTS Hit Recognit
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Post-processing: Visual Inspection
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PCB013 146.55 -2.7348 0.3315 0.3241
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PCB113 136.08 -3.2367 0.5862 0.5861
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Regression 1 6.730776811 6.730777 7
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Metoda Formula intervalului de înc
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1.2 1 0.8 0.6 0.4 0.2 Metoda ArcS 0
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Metoda AvADA(0) AvADA(1) AvADS(0) A
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12 11.01 9.99 10 8 6 4 2 0 6 5 4 3
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Planificarea activităţilor experi
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o Generalized functions; o Operator
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approaches of QSAR modeling o Sessi
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Bookhaven pe care o transferă prog
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1.21739507388622E+000 y= 7.38149868
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20 020_3613389 7.783 -1.627 5.661 0
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} function atom_info($atom,&$cnv_to
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}else{ } } $this->tmp_dist=array();
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} } return "({".implode(",",$this->
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if($this->p12_2) $this->f[57] =$thi
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$fr_f_t=pow(pow($fr_f_x,2)+pow($fr_
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} } $this->f[$a]=$ret; } Interacţi
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÷ 2 tipuri de selecţii ale valori
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} $ret[$j][$k]=array(0.0,0.0,0.0,0.
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if(!$q){ } echo($query." :ERROR!\r\
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} unset($a); $query="INSERT INTO `"
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$ok=$this->check_finite();if(!$ok)r
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$q=mysql_query($query_prop."'".$mdf
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2005-RIMC; Jäntschi & Bolboacă, 2
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0.918 0.9 5 14 23110_ 69 332064 837
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0.9665 0.9525 4 30 33504 73 r = 0.9
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20 41521_ lNMrEQg*0.336843860556055
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54 DevMTOp25_ y=1.893045064859439+
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82 19654_ lIDRFMg*-1.31755354516111
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y=3.463929176330566+ ABDmtQg*-13.01
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iBMmwHg*1195.781250000000000+ iFPME
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161 15aacidsHyd_ lSDmwMt*6.37250438
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Relaţii semicantitative structură
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MDFV (Jäntschi şi Bolboacă, 2008
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SAPF (©2009) CF:3 DO:2 AP:5 DP:6 P
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N0) fenotipurilor între generaţii
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adevăr (T/F) pentru fiecare operat
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S5 String[255] Şir de maxim 255 ca
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end; with(MDF)do repeat CF_Rs;SA_Fr
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sfs_FITNESS_strategy= proportional/
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parametrul statistic descriptiv mx
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d_n:S9; Variabilă folosită la pen
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(s:S9):B0T; configurare a execuţie
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; ÷ mută părinţi cu probabilita
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procedure SL_QSr (i,j:I0T); procedu
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XX_min = XX_max = XX_avg = XX (XX =
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$p_max[$i]=1.0*$m-1.0*$m*$tdist->_g
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$d[$i][$k++]=$c[$i][$j]; for($i=0;$
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for($i=0;$i
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mat_means($n,$m,$y,$x,$ma,$mb); red
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} if(strlen($s)>0) $t[]=$s; return
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este necesar ca să se asume ipotez
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6(( b − a + 1) Asimetria; excesul
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Minim; Maxim 0; ∞ Funcţia de pro
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Varianţa Var γ1 (nX-1)σ 2 /nX 2
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Σ1≤i≤m(Ŷi-Yi) 2 → min. (3)
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Tabelul 24. Valorile optimizate ale
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eroare m(n-1) 2 m ⎛ n ⎛ n ⎞
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http://l.academicdirect.ro/Chemistr
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73 la convergenţă folosind un alg
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Cl(n) Cl (n) PCBs: Seria bifenililo
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PCB027 Cl Cl Cl 5.447 PCB028 Cl Cl
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PCB071 Cl Cl Cl Cl 5.987 PCB072 Cl
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PCB110 Cl Cl Cl Cl Cl 6.532 PCB111
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PCB151 Cl Cl Cl Cl Cl Cl 6.647 PCB1
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PCB191 Cl Cl Cl Cl Cl Cl Cl 7.557 P
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O altă remarcă se poate face cu p
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al eşantionului pe care o induc me
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PmkEt 1 26 26 sDDJEg 1 26 26 MDDKHt
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86 Abateri semnificative statistic
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Generaţii ce produc evoluţii (num
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Rar (D, P) (D, T) Figura 2. Cât de
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2010A5. Construirea bazei de date c
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Portalul "MDF" Portalul "Statistics
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(Bolboacă & Jäntschi, 2007-AAHS):
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Environment, Applied Medical Inform
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AcademicDirect, ISSN 1583-1078, www
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Observable: Maximum Likelihood Esti
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and Veterinary Medicine Cluj-Napoca
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Relative Response Factor using Mole
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