Notebook HEARTBEAT
Welcome to the notebook of the HEARTBEAT (Heidelberg Artificial Transcription Factor Binding Sites Assembly and Engineering Tool) project. This notebook comprises the work on three sublanes: HEARTBEAT database (DB), HEARTBEAT graphical user interface (GUI) and HEARTBEAT fuzzy modeling (FN) as well as some additional work on logo as well as wiki design. Have fun!
Contents
July
7-27-2009
- Meeting with Oliver Pelz
- Discuss general ideas of our Database Structure and Content
- An introduction into PromoterSweep (LINK). PromoterSweep screens a given sequence for conserved regions giving us consensus sequences and moreover screens them for TFBS by using database search (TRANSFAC, Jasper) (LINK)
- Our new database should contain following informations: promoter sequence, TFs, TFBS, position of TFBS, number of binding TFBS, "host organism"
- We decide to choose MySQL as a appropiate language solving this challenge which allows us also a graphical representation of the database on the web later.
- GUI on wiki: which language? php? javascript?
- Problems: access to PromoterSweep (Husar Bioinformatics Group, DKFZ), choice of Promoter Database (DoOP, UCSC, EnsEMBL) (LINK)
- aim: create database until end of August
[TOP]
August
[TOP]
8-3-2009
- First contact with MySQL
- Start making an overview of other team's projects
- Configuring our Virtual Server
8-4-2009
- Official Team Meeting (LINK) @ BQ seminar room 43: preparaing presentation & writing meeting report
- Start installing developing environment on our internal server
8-5-2009
- Meeting with Tobias Bauer & Anna-Lena Kranz (Theoretical Bioinformatics, DKFZ) @ TP3, DKFZ
- Integrating ideas of PromoterSweep, Transfac as well as DoOP/CisRED
- select "interesting" TFs (e.g. HIF, NFkB, c-myc, p53) for Wetlab
- select "interesting" pathways (e.g. cell cycle, inflammation, metabolism etc)
- future experimental validation: ChIP-on-Chip
- for this we need a TFBS-free sequence
- idea: plot histogram of TFBS relative to TSS
- problem: choice of sequence: upstream only? inculde downstream?
- new programming language: R and perl
- next meeting: Friday after team meeting
- Meeting with Karl-Heinz Glatting (HUSAR, DKFZ) @ TP3, DKFZ
- An introduction into PromoterSweep
- Structure and analysis principles of PromoterSweep
- Output is stored in an XML file. This means we have to parse the xml code.
- Oliver Pelz will give help for us in programming
- Protocol of the meeting can be downloaded from here.
- Start working with MySQL
- request UNIX/HUSAR/HPC access at DKFZ (Nao)
- first contact with several databases: EmsEMBL, Compara, cisRED, DoOP, TiProD, contra (LINKS)
8-6-2009
- Meeting with Oliver Pelz
- defining workflow with PromoterSweep, Matrix Profile Search and introduction into different Motif Discovery Algorithms
- installation of NX server for access onto internal server from Windows
- configure developing environment (printing from Linux, configure Mediawiki)
- defining basic concept of database construction
- we select annotated promoter sequences in DoOP
- we make a selection of pathway of interest using KEGG
- narrow down number of target promoter sequences <10000.
8-7-2009
- Official Team Meeting on Scheduling
- Meeting with Anna-Lena and Tobias
- Introduction into R
- Tobias will give us access to their computing cluster (Group Roland Eils)
- Promoter Selection: DoOP, EnsEMBL, or UCSC?
- HUSAR account arrived
- installation of R, R editor and perl editor
- further configuration of our internal server / mediawiki
[TOP]
8-10-2009
- first contact with R and perl
- playing around with R and perl
- playing around with R library: Biobase
- check working on DKFZ cluster
8-11-2009
- defining programming languages: perl, R, MySQL
- retrieving first Promotersweep output files
- Meeting with Marti
- ideas for modeling
- we will have at least three colors which overlap in their spectra.
- a very nice approach will be Fuzzy Logic Modeling.
- idea 1: error checking of affinity: compare expectation to experimental results and figure out where the error is hiding
- idea 2: create&visualize fancy and fuzzy data from in silico simulation
- combine: promoter, output and graphic representation (GRAFIK!)
- next meeting with Marti: end of next week.
- extract NCBI Entrez Gene IDs with R and perl
- MAC adresses registered for bioquant network
8-12-2009
- configure perl working environment
- study structure of DoOP database
- download DoOP and load DoOP database into MySQL
8-13-2009
- trying out some DoOP queries
- download fasta sequences from UCSC gene browser (LINK)
- mapping of NCBI Entrez Gene IDs with RefSeq IDs
- configure perl working environment on Windows XP
- contact Endre Sebestyen concerning the perl module Bio-DoOP-DoOP (LINK)
8-14-2009
- start PromoterSweep Analysis over Weekend
[TOP]
8-18-2009
Tim, Stephen, ab hier müsst ihr eure Sachen selber eintragen!
- study outputfile of PromoterSweep. check out general structure and pick up useful information.
- result is grouped in: General Info, Best Genomic Mapping, Promoter DB Search Result, Graphical Overview, Combined Binding Sites, TSS and Exon Info, Profile Matrices and Generated Output Files.
- upon selection, sections of interest will be collected and made ready for entry into MySQL DB
- discuss table structure of our database
- How should our database be called? - Brainstorming -
- SHOULD contain: iGEM, Transcription Factor, Binding Site, Promoter, synthetic biology, Heidelberg
- MAY contain: position, heartbeat, prediction, assembly, eukaryotes
- and still more keywords to come
8-19-2009
- parse Promotersweep xml file into tab-separated text file (PERL CODE?)
- the text file should contain: RefSeq ID, TF name, TFBS position, TF motif sequence, TFBS Quality, TSS, Entrez ID, EnsEMBL ID, further gene description.
- this provided us with several programming problems concerning working with multiple arrays, hashes and their combinations (arrays of hashes, hashes of hashes, etc.) thus
- studying structure and basic concepts of hash & key
8-20-2009
- pre-decision for our table-structure
- Table: Main_Info
- RefSeq ID, TF, TF motif start & end position, TFBS motif score, TFBS quality, TSS database info
- Table: Gene_Info
- Ensembl_ID, Gene Symbol, Gene Description.
- we go for the RefSeq ID to be the key connecting these two tables.
8-21-2009
- update script for parsing the Promotersweep output files due to unexpected errors
- we forgot to include "weak" as a category for the TFBS quality - added!
- PromoterSweep result contains information about TSS derived from different promoter databases. On which should we rely, if they differ from each other?
- We set our highest priority to DoOP database since they show a good accordance within the RefseqID results when compared to other databases (e.g. DBTSS).
- order [http://www.mathworks.com/| Matlab] iGEM licence
- search for a tool to use MySQL in R programming environment
- wiki: write an short article about the German Cancer Research Center (DKFZ)
- Meeting with Anna-Lena: once we established our database... then
- two strategies:
- manually select interesting transcription factors and analyse them using database queries
- plot histograms of TFBS occurance within the target promoter sequence (TSS - 1000bp upstream) for each TF and make systematic analysis
- we go for both!
- idea for the future: we can analyze combinatorial appearance of distinct TF pairs
- We have a name for our database - we call it -
- wait for it -
HEARTBEAT database (Heidelberg Artificial Transcription Factor Binding Site Engineering and Assembly Tool)
[TOP]
8-24-2009
- Meeting with Marti: defining output modeling strategies
- "exclusive promoters"
- a model for predicting the behaviour of activation of one, two, three... promoters at the same time.
- the potential of this model lies in the possibility to model single as well as many pathways in combination and even check for synergistic effects
- modeling logic: quantitative ODE VS. quantitative & qualitative fuzzy logic
- "error checking"
- what to capture/measure: affinity of transcription factor binding to DNA
- calculate score / reliabilty
- phenotypic measurement
- if we have time in the end: model/experiment optimization by wetlab-drylab-rounds (GRAFIK)
- if we do not have much time: figure out where is catch
- modeling layers & final visualization
- (i) capture affinity - (ii) model gene expression - (iii) pathway activity - (iv) fancy visualization (Mathworks Simulink?)
- plot: time course, dynamic affinity
- keep in mind the possible high amount of False Positives using promoter search/analysis
8-25-2009
- official Team Meeting also with Mr. Kai Ludwig (LANGE + PFLANZ) as guest for Logo / Title Claim discussion
- so far we have 1753 promoter sequences analyzed by PromoterSweep!
- Meeting with Daniela (Nao): Cell Profiler for capturing biological images & data analysis based on MATLAB
- working with R module RMySQL (LINK) for using the pipeline between R and MySQL
- create a list of useful RMySQL commands
8-26-2009
- Workflow for plotting histogram - workflow (SOURCE CODE/S?)
- make MySQL query using R
- make list of TFs, avoid duplicates using perl
- pick up each TF (perl/R) and plot histogram (R)
- create MySQL command list including combinatorial queries
8-27-2009
- check HEARTBEAT DB for duplicate entries
- how should we plot the histogram?
- (a) histogram - how "wide" should be each bin? 100bp? 50bp? 20bp?
- (b) plot probability density
- study Transfac PWM (position weight matrices) for
- difference in consensus sequences (also ask Anna-Lena)
- different PWM types (vertebrates, plant, insect, fungi, bacteria, nematodes...)
- positive control: when histograms are generated and plotted, check distribution of Sp1 (LINK)
- so far we have 3640 promoter sequences "sweeped"!
8-28-2009
[TOP]
8-31-2009
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September
[TOP]
9-1-2009
- derive transcription factor data using R and MySQL
- plot HEARTBEAT TF hit distribution as histograms & density functions for different PWM subsets (all, vertebrates only, single matrices and joined TFs)
9-2-2009
- discussion on how to make statistical studies on our gained distributions
- ideas: define maximum and variance -> Nao
- look for motif sequences -> Tim
- we have 4476 sequences analysed by Promotersweep so far!
- but we are expecting 4700 sequences - check missing ones!
9-3-2009
9-4-2009
[TOP]
9-7-2009
9-8-2009
9-9-2009
[TOP]
October
10-1-2009
10-2-2009
[TOP]
10-5-2009
10-6-2009
10-7-2009
10-8-2009
10-9-2009
[TOP]
10-12-2009
10-13-2009
[TOP]
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