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    Mathematik in den Life Sciences

    Grundlagen der Modellbildung und Statistik mit einer Einführung in die Statistik-Software R

    Mathematik in den Life Sciences
    Grundlagen der Modellbildung und Statistik mit einer Einführung in die Statistik-Software R

    Autoren:

    Verlag:
    UTB   Weitere Titel dieses Verlages anzeigen

    Erschienen: April 2011
    Seiten: 232
    Sprache: Deutsch
    Preis: 17.90 €
    Illustration: 49 Abbildungen
    Maße: 215x150x18
    Einband: Taschenbuch
    Reihe: Uni-Taschenbücher M
    ISBN: 9783825234935

    Inhaltsverzeichnis

    1Einführung11
    1.1Warum Mathematik?11
    1.2Vorbereitende und ergänzende Literatur13
    2Mathematische Grundbegriffe15
    2.1Zahlen15
    2.2Rechenregeln16
    2.3Zahlen als Messergebnisse17
    2.3.1Messgenauigkeit, Runden17
    2.3.2Maßeinheiten18
    2.3.3Mol und Molekulargewicht18
    2.4Vektoren, Matrizen19
    2.5Matrizenmultiplikation21
    2.6Zahlenfolgen22
    2.7Funktionen23
    2.8Bemerkungen zum Rechnen mit Logarithmen25
    2.9Fragen und Aufgaben25
    3Differenzieren, Ableitung27
    3.1Ableitung von Funktionen einer Variablen27
    3.2Ableitungsregeln29
    3.3Integral und Stammfunktion32
    3.4Partielle Ableitungen33
    3.5Fragen und Aufgaben34
    4Grafische Darstellung von Daten und beschreibende Statistik35
    4.1Datenvektoren und Datenmatrizen35
    4.2Beschreibende Statistik - Grundbegriffe37
    4.3Eindimensionale Stichproben38
    4.3.1Nominale Merkmale38
    4.3.2Metrische Merkmale39
    4.3.3Statistische Kennzahlen41
    4.4Zweidimensionale Stichproben43
    4.5Lineare Regression45
    4.6Allometrie48
    4.7Fragen und Aufgaben51
    5Wachstumsmodelle: unbeschränktes Wachstum53
    5.1Lineares Wachstum53
    5.2Exponentielles Wachstum - diskrete Zeit54
    5.2.1Modellwahl8
    .2.2Quadratische Abweichung9
    5.3Exponentielles Wachstum - stetige Zeit0
    5.3.1Von diskreter zu stetiger Zeit60
    5.3.2Die Differenzialgleichung für exponentielles Wachstum in stetiger Zeit61
    5.3.3Kommentar aus der Sicht der Mathematik62
    5.3.4Lineare Regression bei exponentiellem Wachstum63
    5.3.5Zusammenfassung zum exponentiellen Wachstum:64
    5.3.6Exponentielles Aussterben64
    5.3.7Verdopplungszeit, Halbwertzeit65
    5.4Fragen und Aufgaben66
    6Wachstumsmodelle: beschränktes Wachstum67
    6.1Logistisches Wachstum67
    6.1.1 Ein paar grundsätzliche Bemerkungen zum Begriff
    der Differenzialgleichung71
    6.1.2Bemerkungen zum numerischen Lösen einer Differenzialgleichung72
    6.1.3Anpassung des logistischen Modells an Daten73
    6.1.4Ein Residuenplot74
    6.2Stabilisierung bei konstantem Zufluss und exponentiellem Abbau75
    6.3Variationen zum logistischen Wachstum76
    6.3.1Ein logistisches Modell mit „Bejagung"76
    6.3.2Ein Modell mit zwei stabilen Gleichgewichten79
    6.4Zeitverzögerungen80
    6.5Zwei Modelle der chemischen Reaktionskinetik81
    6.6Fragen und Aufgaben85
    7Modelle der Populationsgenetik87
    7.1Das Hardy-Weinberg-Modell87
    7.2Inzucht91
    7.3Selektion92
    7.4Fragen und Aufgaben97
    8Wachstumsmodelle: zwei Populationen98
    8.1Das Räuber-Beute-Modell von Lotka und Volterra98
    8.2Ein einfaches Epidemiemodell103
    8.3Fragen und Aufgaben105
    9Wahrscheinlichkeitsrechnung106
    9.1Zufallsvariablen106
    9.1.1Diskrete Zufallsvariablen107
    9.1.2Kontinuierliche Zufallsvariablen108
    9.2Unabhängigkeit diskreter Zufallsvariablen109
    9.2.1Bedingte Wahrscheinlichkeit und Unabhängigkeit110
    9.2.2Die Binomialverteilung110
    9.3Unabhängigkeit kontinuierlicher Zufallsvariablen112
    9.4Histogramm unabhängiger Beobachtungen112
    9.5Erwartungswert und Varianz113
    9.5.1Erwartungswert und Varianz diskreter Zufallsvariablen113
    9.5.2Erwartungswert und Varianz kontinuierlicher Zufallsvariablen115
    9.6Normal-und Poisson-Approximation der Binomialverteilung116
    9.6.1Verteilungsfunktionen binomialverteilter Zufallsvariablen116
    9.6.2Normalapproximation der Binomialverteilung117
    9.6.3Poisson-Approximation der Binomialverteilung118
    9.7Fragen und Aufgaben119
    10Beurteilende Statistik: Testen120
    10.1Der Binomialtest120
    10.1.1Formulierung des Testproblems120
    10.1.2Durchführung des Tests121
    10.1.3Unabhängigkeit der Beobachtungen122
    10.2Chi-Quadrat-Tests123
    10.3Fragen und Aufgaben129
    11Beurteilende Statistik: Schätzen131
    11.1Schätzen von Erfolgswahrscheinlichkeiten131
    11.2Konfidenzintervall für den Erwartungswert134
    11.2.1Konfidenzintervall bei normalverteilten Beobachtungen135
    11.2.2Der Ein-Stichproben-t-Test136
    11.3Fragen und Aufgaben137
    12Beurteilende Statistik: Korrelation und Regression138
    12.1Ist der Korrelationskoeffizient signifikant von Null verschieden?138
    12.2Die statistische Beurteilung der geschätzten Regressionskoeffizienten140
    12.3Vorsicht bei linearer Regression142
    12.4Fragen und Aufgaben142
    13Einführung in das Sequenz-Alignment143
    13.1Scoring-Modelle zur Bewertung von Alignments143
    13.1.1Scoring bei DNA-Alignments143
    13.1.2Scoring bei Proteinsequenz-Alignments144
    13.2Scores und Wahrscheinlichkeiten146
    13.3Der Needleman-Wunsch-Algorithmus148
    13.3.1Die Grundidee des Needleman-Wunsch-Algorithmus149
    13.3.2 Eine Realisierung des Needleman-Wunsch-Algorithmus
    für den Vergleich zweier DNA-Sequenzen in R151
    13.3.3Beispiele zum Needleman-Wunsch-Algorithmus152
    13.3.4Der Smith-Waterman-Algorithmus153
    13.4Clustering154
    13.5Fragen und Aufgaben156
    R Einführung in R157
    R1 Erste Schritte158
    Rl.l R als Taschenrechner158
    R1.2 Eine erste Grafik161
    R2 Grundlegende Begriffe162
    R2.1 Variablen162
    R2.2 Folgen163
    R2.3 Die erzeugten Objekte165
    R3 Funktionen, Nullstellen, Maxima, Minima, R-Hilfe166
    R3.1 Funktionen166
    R3.2 Funktionsgraphen167
    R3.3 Hilfe in der Dokumentation168
    R3.4 Nullstellen, Maxima und Minima169
    R4 Funktionen mehrerer Variablen, der Workspace von R171
    R4.1 Funktionen mehrerer Variablen171
    R4.2 Wie funktioniert R im Hintergrund?172
    R5 Vektoren, Matrizen, der Dateneditor174
    R5.1 Vektoren174
    R5.2 Matrizen176
    R6 Matrizenmultiplikation, Dotplots180
    R6.1 Matrizenmultiplikation180
    R6.2 Der Befehl out er ()182
    R6.3 Eine Vergleichstabelle für Sequenzvergleiche und ein Dotplot183
    R7 Datensätze, R Commander, beschreibende Statistik185
    R7.1 Der R Commander185
    R7.2 Datensätze186
    R7.3 Speichern von Programmen und Objekten189
    R7.4 Lineare Regression und Korrelation190
    R8 Datenim- und -export, Grafikexport193
    R8.1 Erstellen und Einlesen eigener Datensätze193
    R8.2 Grafik-Export195
    R9 Exponentielles Wachstum und Abklingen197
    R9.1 Zinseszins mit R als Taschenrechner197
    R9.2 Exponentielles Wachstum - US-Bevölkerungsdaten197
    R9.3 Exponentieller Abbau - Medikamentenabbau im Körper198
    RIO Nichtlineare Regression200
    R10.1 Logistisches Wachstum - US-Bevölkerungsdaten201
    RIO.2 Biexponentielles Abklingen201
    RIO.3 Michaelis-Menten-Funktion202
    RH Binomial-, Normal- und Poisson-Verteilung203
    Rll.l Die Binomialverteilung203
    Rll.2 Die Normalverteilung204
    Rll.3 Die Poisson-Verteilung205
    RH .4 Plotten von Dichten und Verteilungsfunktionen205
    R12 Binomialtest und Chi-Quadrat-Tests206
    R12.1 Die Binomialverteilung und der Binomialtest206
    R12.2 x2-Tests208
    R13 Schätzen und Testen bei normalverteilten Beobachtungen209
    R13.1 Konfidenzintervalle bei normalverteilten Beobachtungen209
    R13.2 Ein-Stichproben-t-Test211
    R13.3 Zwei-Stichproben-t-Test - verbundene Strichproben212
    R13.4 Statistik zur linearen Regression213
    R14 Sequence Alignment214
    R14.1 Die Datenbank Genbank214
    R14.2 Die Bereitstellung von Sequenzen für R215
    R14.3 Needleman-Wunsch-Algorithmus für Protein-Sequenzen216
    R14.4 Gleichzeitiger Vergleich mehrerer Sequenzen217
    Verzeichnisse219
    R-Codes zu ausgewählten Abbildungen219
    Literatur225
    Sachregister227
    Index der R-Befehle231