Computational Methods in Genomic and Proteomic Data Analysis

Peter Johansson

Computational Methods in Genomic and Proteomic Data Analysis

Peter Johansson

Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)

40 Nedladdningar (Pure)

Sammanfattning

Popular Abstract in Swedish
Med modern mätteknik kan vi mäta cellers egenskaper för alla gener samtidigt. För att tolka den stora datamängden krävs analysmetoder och datorverktyg. Den här avhandlingen behandlar ett antal sådana verktyg avsedda att klargöra geners och proteiners inbördes samband. En metod att hantera datavärden av varierande kvalité presenteras, såväl som ett verktyg att visualisera samband i masspektrometri-data. Klassificering och då speciellt ensemblemetoder diskuteras och används för att undersöka två signalvägar, MAPK och PI3K, som är viktiga i cancer.

Originalspråk	engelska
Kvalifikation	Doktor
Tilldelande institution
Handledare	Ringnér, Markus, handledare
Tilldelningsdatum	2006 juni 2
Förlag	Department of Theoretical Physics, Lund University
ISBN (tryckt)	91-628-6852-7
Status	Published - 2006

Bibliografisk information

Defence details

Date: 2006-06-02
Time: 10:15
Place: Lecture Hall F Sölvegatan 14 A Lund

External reviewer(s)

Name: Wessels, Lodewyk
Title: Dr.
Affiliation: Netherlands Cancer Institute

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FN:s Globala mål

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SDG 3 – God hälsa och välbefinnande

Ämnesklassifikation (UKÄ)

Biofysik

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Peter_Johansson_kappa

Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity
Saal, L., Johansson, P., Holm, K., Gruvberger, S., She, Q.-B., Maurer, M., Koujak, S., Ferrando, A. A., Malmström, P., Memeo, L., Isola, J., Bendahl, P.-O., Rosen, N., Hibshoosh, H., Ringnér, M., Borg, Å. & Parsons, R., 2007 maj 1, I: Proceedings of the National Academy of Sciences. 104, 18, s. 7564-7569
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

Öppen tillgång
An evaluation of using ensembles of classifiers for predictions based on genomic and proteomic data
Ringnér, M. & Johansson, P., 2006 apr., 9 s. (LU TP 06-19)
Forskningsoutput: Bok/rapport › Rapport › Forskning

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Detection and identification of protein isoforms using cluster analysis of MALDI-MS mass spectra
Alm, R., Johansson, P., Hjerno, K., Emanuelsson, C., Ringnér, M. & Häkkinen, J., 2006 mars 16, I: Journal of Proteome Research. 5, 4, s. 785-792
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

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@phdthesis{80c11b171be344beb628939f6ec8980f,

title = "Computational Methods in Genomic and Proteomic Data Analysis",

abstract = "With the great progress of technology in genomics and proteomics generating an exponentially increasing amount of data, computational and statistical methods have become indispensable) for accurate biological conclusions. In this doctoral dissertation, we present several algorithms designed to delve large amounts of data and bolster the understanding of molecular biology. MAPK and PI3K, two signaling pathways important in cancer, are explored using gene expression profiling and machine learning. Machine learning and particularly ensembles of classifiers are studied in context of genomic and proteomic data. An approach to screen and find relations in protein mass spectrometry data is described. Also, an algorithm to handle unreliable values in data with much redundancy is presented.",

keywords = "Physics, Microarray, Cancer, Fysik, Classification",

author = "Peter Johansson",

note = "Defence details Date: 2006-06-02 Time: 10:15 Place: Lecture Hall F S{\"o}lvegatan 14 A Lund External reviewer(s) Name: Wessels, Lodewyk Title: Dr. Affiliation: Netherlands Cancer Institute ---",

year = "2006",

language = "English",

isbn = "91-628-6852-7",

publisher = "Department of Theoretical Physics, Lund University",

type = "Doctoral Thesis (compilation)",

}

TY - THES

T1 - Computational Methods in Genomic and Proteomic Data Analysis

AU - Johansson, Peter

N1 - Defence details Date: 2006-06-02 Time: 10:15 Place: Lecture Hall F Sölvegatan 14 A Lund External reviewer(s) Name: Wessels, Lodewyk Title: Dr. Affiliation: Netherlands Cancer Institute ---

PY - 2006

Y1 - 2006

N2 - With the great progress of technology in genomics and proteomics generating an exponentially increasing amount of data, computational and statistical methods have become indispensable) for accurate biological conclusions. In this doctoral dissertation, we present several algorithms designed to delve large amounts of data and bolster the understanding of molecular biology. MAPK and PI3K, two signaling pathways important in cancer, are explored using gene expression profiling and machine learning. Machine learning and particularly ensembles of classifiers are studied in context of genomic and proteomic data. An approach to screen and find relations in protein mass spectrometry data is described. Also, an algorithm to handle unreliable values in data with much redundancy is presented.

AB - With the great progress of technology in genomics and proteomics generating an exponentially increasing amount of data, computational and statistical methods have become indispensable) for accurate biological conclusions. In this doctoral dissertation, we present several algorithms designed to delve large amounts of data and bolster the understanding of molecular biology. MAPK and PI3K, two signaling pathways important in cancer, are explored using gene expression profiling and machine learning. Machine learning and particularly ensembles of classifiers are studied in context of genomic and proteomic data. An approach to screen and find relations in protein mass spectrometry data is described. Also, an algorithm to handle unreliable values in data with much redundancy is presented.

KW - Physics

KW - Microarray

KW - Cancer

KW - Fysik

KW - Classification

M3 - Doctoral Thesis (compilation)

SN - 91-628-6852-7

PB - Department of Theoretical Physics, Lund University

ER -

Computational Methods in Genomic and Proteomic Data Analysis

Sammanfattning

Bibliografisk information

FN:s Globala mål

Ämnesklassifikation (UKÄ)

Tillgång till dokument

Fingeravtryck

Forskningsoutput

Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity

An evaluation of using ensembles of classifiers for predictions based on genomic and proteomic data

Detection and identification of protein isoforms using cluster analysis of MALDI-MS mass spectra

Citera det här