Systems biology - Bioinformatics on complete biological systems

•Télécharger en tant que PPT, PDF•

5 j'aime•1,457 vues

Lars Juhl Jensen

Formation Technologie

Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011

Exercise 1
Go to http://string-db.org
Query for CDC28 in budding yeast
Try different evidence views
Show only high-confidence links
Show only experimental evidence

Korbel et al., Nature Biotechnology, 2004

Beyer et al., Nature Reviews Genetics, 2007

Letunic & Bork, Trends in Biochemical Sciences, 2008

Exercise 2
Go to http://stitch-db.org
Query for TYMS in human
What is the role of thymidylate?
What is the role of dUMP
What is the role of Permetrexed

von Mering et al., Nucleic Acids Research, 2005

Exercise 3
Go to http://diseases.jensenlab.org
Find TYMS disease associations
nspect the text-mining evidence
Find genes linked to colorectal cance
Explore the gene network

Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009
O’Donoghue et al., Journal of Web Semantics, 2010

Contenu connexe

Tendances

Systems biology

VWR INTERNATIONAL

proteomics and system biology

Nawfal Aldujaily

System biology and its tools

Gaurav Diwakar

I elaborated these slides for an introductory class on Network Medicine given at UPV (Valencia) in October 2017. The fundamental principle behind Network Medicine is that disease phenotypes emerge from genotypes via the network properties of interactions between the underlying biological components. These phenotypes are best conceptualized as consequences of perturbations to disease modules of the biological networks in the cell, whether at the node level (disease genes) or the link level (disease edgotypes). With the further analysis of drug-disease association and drug-target association data, one can investigate the effects - therapeutic and undesired - of the associated medication. Understanding the molecular level networks allows to understand the connections between different diseases and the effects of drugs designed to target them, paving the way for personalized treatments based on one's own interactome.

Introduction to Network Medicine

Marc Santolini

“Organisms function in an integrated manner-our senses, our muscles, our metabolism and our minds work together seamlessly. But biologists have historically studied organisms part by part and celebrated the modern ability to study them molecule by molecule, gene by gene. Systems biology is critical science of future that seeks to understand the integration of the pieces to form biological systems” (David Baltimore, Nobel Laureate)

Interactomics, Integromics to Systems Biology: Next Animal Biotechnology Fron...

Varij Nayan

Advanced Systems Biology Methods in Drug Discovery

Mikel Txopitea Elorriaga

In interactome, basically for interaction of proteins there is certain key elements requited, they are: Interactomics and Proteomics, Complementation groups, Modifier screens 1. Interactomics and Proteomics Field of interactomics is concerned with interactions between genes or proteins. They can be genetic interactions, in which two genes are mainly involved in the same functional pathway (leading to a particular phenotype), or physical interactions, in which there is direct physical contact between two proteins (or between protein and DNA) (Janga et al.,2008). 2. Complementation groups Using forward saturation genetics, one may recover several independent mutants with the same (or similar) phenotype (Hernández et al., 2007). There are two possibilities: a) Mutations are in the same gene b) Mutations are in different genes involved in the same pathway. Scenario (b) Can be tested genetically with a complementation test:  Cross two homozygous mutants (samples) and observe heterozygous offspring phenotypes(samples) Mutations in the same gene will not complement  offspring have mutant phenotype Mutations in different genes will complement  offspring have wild Type phenotype  Do pairwise crosses for all mutants to identify complementation groups  Typically each complementation group represents a different gene  If many mutations are recovered in the same genes, this implies saturation

Interactomeee

Dr. sreeremya S

Report on System Biology Funding from BMBF

EuroBioForum

Protein interaction networks

Lars Juhl Jensen

Protein–protein interaction networks

Lars Juhl Jensen

DNA Sequencing in Phylogeny

Bikash1489

System's Biology

Pritam Shil

Protein protein interaction, functional proteomics

KAUSHAL SAHU

Large-scale integration of data and text

Lars Juhl Jensen

Protein interaction, types by kk sahu

KAUSHAL SAHU

In this talk, I will describe several recently developed methods to study disease perturbations through the lens of network science. First I will present evidence that one can accurately predict perturbation patterns from the topology of biological networks, even when lacking measurements on the kinetic parameters governing the dynamics of these interactions. Using 87 biochemical networks with experimentally measured kinetic parameters, we show that a knowledge of the network topology offers 65% to 80% accuracy in predicting the impact of perturbations. In other words, we can use the increasingly accurate topological models to approximate perturbation patterns, bypassing expensive kinetic constant measurement. These results open new avenues in modeling drug action, and in identifying drug targets relying on the human interactome only. Then, I will present a novel approach to identify the collective impact of miRNAs in disease. Instead of focusing on the magnitude of miRNA differential expression, here we address the secondary consequences for the interactome. We developed the Impact of Differential Expression Across Layers (IDEAL), a network-based algorithm to prioritize disease-relevant miRNAs based on the central role of their targets in the molecular interactome. This method was used in the context of asthmatic Th2 inflammation and identified five Th2-related miRNAs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. This result offers novel approaches for therapeutic interventions. Finally, I will present an investigation of the personalized gene expression responses when inducing hypertrophy and heart failure in 100+ strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). I will show that genes whose expression change significantly correlates with the severity of the disease are either up- or down-regulated across strains, and therefore missed by traditional population-wide analyses of differential gene expression. These uncovered personalised genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome, the set of molecular interactions in the cell. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes, demonstrating that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.

Perturbing The Interactome: Multi-Omics And Personalized Methods For Network ...

Marc Santolini

Protein interactions

Lars Juhl Jensen

protein-protein interaction

Zeshan Haider

Structural Genomics

Aqsa Javed

STRING: Large-scale data and text mining

Lars Juhl Jensen

Tendances (20)

Systems biology

proteomics and system biology

System biology and its tools

Introduction to Network Medicine

Interactomics, Integromics to Systems Biology: Next Animal Biotechnology Fron...

Advanced Systems Biology Methods in Drug Discovery

Interactomeee

Report on System Biology Funding from BMBF

Protein interaction networks

Protein–protein interaction networks

DNA Sequencing in Phylogeny

System's Biology

Protein protein interaction, functional proteomics

Large-scale integration of data and text

Protein interaction, types by kk sahu

Perturbing The Interactome: Multi-Omics And Personalized Methods For Network ...

Protein interactions

protein-protein interaction

Structural Genomics

STRING: Large-scale data and text mining

Similaire à Systems biology - Bioinformatics on complete biological systems

STRING & related databases: Large-scale integration of heterogeneous data

Lars Juhl Jensen

Network biology: Large-scale data and text mining

Lars Juhl Jensen

STRING: protein association networks

Lars Juhl Jensen

STRING: Protein association networks

Lars Juhl Jensen

Network biology - Large-scale integration of data and text

Lars Juhl Jensen

Network biology: Large-scale integration of data and text

Lars Juhl Jensen

Network biology: Large-scale integration of data and text

Lars Juhl Jensen

Protein association networks with STRING

Lars Juhl Jensen

Gene association networks: Large-scale integration of data and text

Lars Juhl Jensen

Networks of proteins and diseases

Lars Juhl Jensen

Networks of proteins and diseases

Lars Juhl Jensen

Large-scale integration of data and text

Lars Juhl Jensen

Gene association networks: Large-scale integration of data and text

Lars Juhl Jensen

Gene association networks: Large-scale integration of data and text

Lars Juhl Jensen

Protein association networks: Large-scale integration of data and text

Lars Juhl Jensen

Exploring proteins, chemicals and their interactions with STRING and STITCH

biocs

Biological literature mining - from information retrieval to biological disco...

Lars Juhl Jensen

Text and data integration

Lars Juhl Jensen

The STRING database and related tools

Lars Juhl Jensen

Large-scale data and text mining - Linking proteins, chemicals, and side effects

Lars Juhl Jensen

Similaire à Systems biology - Bioinformatics on complete biological systems (20)

STRING & related databases: Large-scale integration of heterogeneous data

Network biology: Large-scale data and text mining

STRING: protein association networks

STRING: Protein association networks

Network biology - Large-scale integration of data and text

Network biology: Large-scale integration of data and text

Protein association networks with STRING

Gene association networks: Large-scale integration of data and text

Networks of proteins and diseases

Large-scale integration of data and text

Gene association networks: Large-scale integration of data and text

Protein association networks: Large-scale integration of data and text

Exploring proteins, chemicals and their interactions with STRING and STITCH

Biological literature mining - from information retrieval to biological disco...

Text and data integration

The STRING database and related tools

Large-scale data and text mining - Linking proteins, chemicals, and side effects

Plus de Lars Juhl Jensen

One tagger, many uses: Illustrating the power of dictionary-based named entit...

Lars Juhl Jensen

One tagger, many uses: Simple text-mining strategies for biomedicine

Lars Juhl Jensen

Extract 2.0: Text-mining-assisted interactive annotation

Lars Juhl Jensen

Network visualization: A crash course on using Cytoscape

Lars Juhl Jensen

STRING & STITCH: Network integration of heterogeneous data

Lars Juhl Jensen

Biomedical text mining: Automatic processing of unstructured text

Lars Juhl Jensen

Medical network analysis: Linking diseases and genes through data and text mi...

Lars Juhl Jensen

Network Biology: A crash course on STRING and Cytoscape

Lars Juhl Jensen

Cellular networks

Lars Juhl Jensen

Cellular Network Biology: Large-scale integration of data and text

Lars Juhl Jensen

Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...

Lars Juhl Jensen

Tagger: Rapid dictionary-based named entity recognition

Lars Juhl Jensen

Network Biology: Large-scale integration of data and text

Lars Juhl Jensen

Medical text mining: Linking diseases, drugs, and adverse reactions

Lars Juhl Jensen

Medical data and text mining: Linking diseases, drugs, and adverse reactions

Lars Juhl Jensen

Cellular Network Biology

Lars Juhl Jensen

Biomarker bioinformatics: Network-based candidate prioritization

Lars Juhl Jensen

The Art of Counting: Scoring and ranking co-occurrences in literature

Lars Juhl Jensen

Text-mining-based retrieval of protein networks

Lars Juhl Jensen

Medical data and text mining: Linking diseases, drugs, and adverse reactions

Lars Juhl Jensen

Plus de Lars Juhl Jensen (20)

One tagger, many uses: Illustrating the power of dictionary-based named entit...

One tagger, many uses: Simple text-mining strategies for biomedicine

Extract 2.0: Text-mining-assisted interactive annotation

Network visualization: A crash course on using Cytoscape

STRING & STITCH: Network integration of heterogeneous data

Biomedical text mining: Automatic processing of unstructured text

Medical network analysis: Linking diseases and genes through data and text mi...

Network Biology: A crash course on STRING and Cytoscape

Cellular networks

Cellular Network Biology: Large-scale integration of data and text

Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...

Tagger: Rapid dictionary-based named entity recognition

Network Biology: Large-scale integration of data and text

Medical text mining: Linking diseases, drugs, and adverse reactions

Medical data and text mining: Linking diseases, drugs, and adverse reactions

Cellular Network Biology

Biomarker bioinformatics: Network-based candidate prioritization

The Art of Counting: Scoring and ranking co-occurrences in literature

Text-mining-based retrieval of protein networks

Medical data and text mining: Linking diseases, drugs, and adverse reactions

Dernier

Klinik_ Apotek Onlin 085657271886 Solusi Menggugurkan Masalah Kehamilan Anda Jual Obat Aborsi Asli KLINIK ABORSI TERPEECAYA _ Jual Obat Aborsi Cytotec Misoprostol Asli 100% Ampuh Hanya 3 Jam Langsung Gugur || OBAT PENGGUGUR KANDUNGAN AMPUH MANJUR OBAT ABORSI OLINE" APOTIK Jual Obat Cytotec, Gastrul, Gynecoside Asli Ampuh. JUAL ” Obat Aborsi Tuntas | Obat Aborsi Manjur | Obat Aborsi Ampuh | Obat Penggugur Janin | Obat Pencegah Kehamilan | Obat Pelancar Haid | Obat terlambat Bulan | Ciri Obat Aborsi Asli | Obat Telat Bulan | Pil Aborsi Asli | Cara Menggugurkan Konten | Cara Aborsi Tuntas | Harga Obat Aborsi Asli | Pil Aborsi | Jual Obat Aborsi Cytotec | Cara Aborsi Sendiri | Cara Aborsi Usia 1 Bulan | Cara Aborsi Usia 2 Tahun | Cara Aborsi Usia 3 Bulan | Obat Aborsi Usia 4 Bulan | Cara Abrasi Usia 5 Bulan | Cara Menggugurkan Konten | Kandungan Obat Penggugur | Cara Menghitung Usia Konten | Cara Mengatasi Terlambat Bulan | Penjual Obat Aborsi Asli | Obat Aborsi Garansi | Kandungan Obat Peluntur | Obat Telat Datang Bulan | Obat Telat Haid | Obat Aborsi Paling Murah | Klinik Jual Obat Aborsi | Jual Pil Cytotec | Apotik Jual Obat Aborsi | Kandungan Dokter Abrasi | Cara Aborsi Cepat | Jual Obat Aborsi Bergaransi | Jual Obat Cytotec Asli | Obat Aborsi Aman Manjur | Obat Misoprostol Cytotec Asli. "APA ITU ABORSI" “Aborsi Adalah dengan membendung hormon yang di perlukan untuk mempertahankan kehamilan yaitu hormon progesteron, karena hormon ini dibendung, maka jalur kehamilan mulai membuka dan leher rahim menjadi melunak,sehingga mengeluarkan darah yang merupakan tanda bahwa obat telah bekerja || maksimal 1 jam obat diminum || PENJELASAN OBAT ABORSI USIA 1 _7 BULAN Pada usia kandungan ini, pasien akan merasakan sakit yang sedikit tidak berlebihan || sekitar 1 jam ||. namun hanya akan terjadi pada saatdarah keluar merupakan pertanda menstruasi. Hal ini dikarenakan pada usiakandungan 3 bulan,janin sudah terbentuk sebesar kepalan tangan orang dewasa. Cara kerja obat aborsi : JUAL OBAT ABORSI AMPUH dosis 3 bulan secara umum sama dengan cara kerja || DOSIS OBAT ABORSI 2 bulan”, hanya berbedanya selain mengisolasijanin juga menghancurkan janin dengan formula methotrexate dikandungdidalamnya. Formula methotrexate ini sangat ampuh untuk menghancurkan janinmenjadi serpihan-serpihan kecil akan sangat berguna pada saat dikeluarkan nanti. APA ALASAN WANITA MELAKUKAN ABORSI? Aborsi di lakukan wanita hamil baik yang sudah menikah maupun belum menikah dengan berbagai alasan , akan tetapi alasan yang utama adalah alasan-alasan non medis (termasuk aborsi sendiri / di sengaja/ buatan] MELAYANI PEMESANAN OBAT ABORSI SETIAP HARI, SIAP KIRIM KESELURUH KOTA BESAR DI INDONESIA DAN LUAR NEGERI. HUBUNGI PEMESANAN LEBIH NYAMAN VIA WA/: 085657271886

Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...

ZurliaSoop

psychiatric nursing HISTORY COLLECTION .docx

PoojaSen20

Holdier Curriculum Vitae (April 2024).pdf

agholdier

The basics of sentences session 3pptx.pptx

heathfieldcps1

Basic Civil Engineering notes first year Notes Building notes Selection of site for Building Layout of a Building What is Burjis, Mutam Building Bye laws Basic Concept of sunlight ventilation in building National Building Code of India Set back or building line Types of Buildings Floor Space Index (F.S.I) Institutional Vs Educational Building Components & function Sills, Lintels, Cantilever Doors, Windows and Ventilators Types of Foundation AND THEIR USES Plinth Area Shallow and Deep Foundation Super Built-up & carpet area Floor Area Ratio (F.A.R) RCC Reinforced Cement Concrete RCC VS PCC

Basic Civil Engineering first year Notes- Chapter 4 Building.pptx

Denish Jangid

Python Notes for mca i year students osmania university.docx

Ramakrishna Reddy Bijjam

Explore the world of IT certification with CompTIA. Discover how the CompTIA Security+ Book SY0-701 can elevate your cybersecurity expertise and open doors to new career opportunities. This PDF provides essential insights into the CompTIA Security+ certification, guiding you through exam preparation and showcasing the benefits of becoming CompTIA-certified. Download now to embark on your journey to IT excellence with CompTIA.

ComPTIA Overview | Comptia Security+ Book SY0-701

bronxfugly43

This PowerPoint helps students to consider the concept of infinity.

christianmathematics

PROCESS RECORDING FORMAT.docx

PoojaSen20

Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...

christianmathematics

Key note speaker Neum_Admir Softic_ENG.pdf

Admir Softic

Grant Readiness 101 TechSoup and Remy Consulting

TechSoup

SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx

Amanpreet Kaur

How to Manage Global Discount in Odoo 17 POS

Celine George

Dyslexia AI Workshop for Slideshare.pptx

callscotland1987

Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...

pradhanghanshyam7136

Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi Welcome to VIP Call Girl In Delhi Hello! Delhi Call Girls is one of the most popular cities in India. Girls who call in Delhi frequently Advertise their services in small promgons in magazines, as well as on the Internet but We do not act as a direct-promoter. We will do everything we can to make sure that you're safe to the max to the best of our abilities and making sure of our ability and ensuring that you're obtained to the best of our abilities and making sure that you get what you want. Sexuality of our females is recognized by our Business proposals. Top-of-the-line, fully-featured Delhi girl call number and we offer To be aware of it is a major reason in deciding to use our services to ensure that our customers realize the worth of their lives swiftly and in a pleasant manner by engaging with web series performers for a cost of 10000.Here you are able to be Relax knowing that personal information is stored in the business proposals, giving an appearance of like you're as if you are a full affirmation. Call Girls Service Now Delhi +91-9899900591 *********** N.M.************* 01/04/2024 ▬█⓿▀█▀ 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 CALL 𝐆𝐈𝐑𝐋 𝐕𝐈𝐏 𝐄𝐒𝐂𝐎𝐑𝐓 SERVICE ✅ ❣️ ⭐➡️HOT & SEXY MODELS // COLLEGE GIRLS AVAILABLE FOR COMPLETE ENJOYMENT WITH HIGH PROFILE INDIAN MODEL AVAILABLE HOTEL & HOME ★ SAFE AND SECURE HIGH CLASS SERVICE AFFORDABLE RATE ★ SATISFACTION,UNLIMITED ENJOYMENT. ★ All Meetings are confidential and no information is provided to any one at any cost. ★ EXCLUSIVE PROFILes Are Safe and Consensual with Most Limits Respected ★ Service Available In: - HOME & HOTEL Star Hotel Service .In Call & Out call SeRvIcEs : ★ A-Level (star escort) ★ Strip-tease ★ BBBJ (Bareback Blowjob)Receive advanced sexual techniques in different mode make their life more pleasurable. ★ Spending time in hotel rooms ★ BJ (Blowjob Without a Condom) ★ Completion (Oral to completion) ★ Covered (Covered blowjob Without condom SAFE AND SECURE

Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi

kauryashika82

Micro-Scholarship, What it is, How can it help me.pdf

Poh-Sun Goh

On National Teacher Day, meet the 2024-25 Kenan Fellows

Mebane Rash

𝐋𝐞𝐬𝐬𝐨𝐧 𝐎𝐮𝐭𝐜𝐨𝐦𝐞𝐬: -Discern accommodations and modifications within inclusive classroom environments, distinguishing between their respective roles and applications. -Through critical analysis of hypothetical scenarios, learners will adeptly select appropriate accommodations and modifications, honing their ability to foster an inclusive learning environment for students with disabilities or unique challenges.

Understanding Accommodations and Modifications

MJDuyan

Dernier (20)

Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...

psychiatric nursing HISTORY COLLECTION .docx

Holdier Curriculum Vitae (April 2024).pdf

The basics of sentences session 3pptx.pptx

Basic Civil Engineering first year Notes- Chapter 4 Building.pptx

Python Notes for mca i year students osmania university.docx

ComPTIA Overview | Comptia Security+ Book SY0-701

This PowerPoint helps students to consider the concept of infinity.

PROCESS RECORDING FORMAT.docx

Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...

Key note speaker Neum_Admir Softic_ENG.pdf

Grant Readiness 101 TechSoup and Remy Consulting

SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx

How to Manage Global Discount in Odoo 17 POS

Dyslexia AI Workshop for Slideshare.pptx

Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...

Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi

Micro-Scholarship, What it is, How can it help me.pdf

On National Teacher Day, meet the 2024-25 Kenan Fellows

Understanding Accommodations and Modifications

Systems biology - Bioinformatics on complete biological systems

1. Lars Juhl Jensen Systems biology Bioinformatics on complete biological systems

2. can a biologist fix a radio?

3. Lazebnik, Biochemistry, 2004

4. one gene

5. one postdoc

6. knockout phenotype

7. name the gene

8. Lazebnik, Biochemistry, 2004

9. all aspects

10. one gene

11. high-throughput biology

12. one technology

13. one lab

14. all genes

15. one aspect

16. systems biology

17. complete systems

18. all aspects

19. all genes

20. systems-level properties

21. two subfields

22. mathematical modeling

23. small systems

24. data integration

25. large systems

26. mathematical modeling

27. small systems

28. Chen, Mol. Biol. Cell, 2004

29. many equations

30. Chen, Mol. Biol. Cell, 2004

31. simulation

32. Chen, Mol. Biol. Cell, 2004

33. many parameters

34. Chen, Mol. Biol. Cell, 2004

35. equires detailed knowledge

36. network biology

37. association networks

38. guilt by association

39.

40. protein networks

41. STRING

42. >1100 organisms

43. ~2.6 million proteins

44. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011

45. Exercise 1 Go to http://string-db.org Query for CDC28 in budding yeast Try different evidence views Show only high-confidence links Show only experimental evidence

46. genomic context

47. gene fusion

48. Korbel et al., Nature Biotechnology, 2004

49. operons

50. Korbel et al., Nature Biotechnology, 2004

51. bidirectional promoters

52. Korbel et al., Nature Biotechnology, 2004

53. phylogenetic profiles

54. Korbel et al., Nature Biotechnology, 2004

55. a real example

56.

57.

58.

59. Cell Cellulosomes Cellulose

60. experimental data

61. gene coexpression

62.

63. protein interactions

64. Jensen & Bork, Science, 2008

65. genetic interactions

66. Beyer et al., Nature Reviews Genetics, 2007

67. curated knowledge

68. complexes

69. pathways

70. Letunic & Bork, Trends in Biochemical Sciences, 2008

71. chemical networks

72. STITCH

73. STRING + 300k chemicals

74. drugs

75. metabolites

76. known drug targets

77. high-throughput assays

78. metabolic pathways

79.

80. Exercise 2 Go to http://stitch-db.org Query for TYMS in human What is the role of thymidylate? What is the role of dUMP What is the role of Permetrexed

81. many databases

82. different formats

83. different identifiers

84. variable quality

85. not comparable

86. hard work

87. quality scores

88. von Mering et al., Nucleic Acids Research, 2005

89. calibrate vs. gold standard

90. missing most of the data

91. text mining

92. >10 km

93. too much to read

94. computer

95. as smart as a dog

96. teach it specific tricks

97.

98.

99. named entity recognition

100. comprehensive lexicon

101. cyclin dependent kinase 1

102. CDK1

103. CDC2

104. flexible matching

105. spaces and hyphens

106. cyclin dependent kinase 1

107. cyclin-dependent kinase 1

108. orthographic variation

109. CDC2

110. hCdc2

111. “black list”

112. SDS

113. information extraction

114. count co-mentioning

115. within documents

116. within paragraphs

117. within sentences

118. scoring scheme

119.

120.

121. proteins

122. small molecules

123. compartments

124. tissues

125. phenotypes

126. diseases

127. adverse drug reactions

128. organisms

129. environments

130. Exercise 3 Go to http://diseases.jensenlab.org Find TYMS disease associations nspect the text-mining evidence Find genes linked to colorectal cance Explore the gene network

131. text corpus

132. ~22 million abstracts

133. no access

134.

135. ~4 million full-text articles

136. augmented browsing

137. Reflect

138. browser add-on

139. real-time text mining

140. Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009 O’Donoghue et al., Journal of Web Semantics, 2010

141. localization and disease

142. suite of web resources