Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/

Essential requirements: Experience of using bioinformatics tools.

Experience of working in Linux. Basic knowledge of computer network administration.

Desirable: Knowledge of Linux installation/administration and proficiency in either of the following:

Shell/PERL/Java/Python/VB/Oracle/MySQL/C/CUDA.

Qualification: PhD. or First class M.Sc degree in Bioinformatics or Biotechnology/life science with specialization in Bioinformatics.

Fellowships: Rs 22,000/- with HRA for PhD qualified, Rs 16000/- with HRA for NET/BET/BINC/GATE qualified and 12000/- with HRA for non NET qualified applicants.

Interested candidates may send their complete biodata along with a write-up of their experience and suitability for the position to Dr. Dinesh Gupta by email only to dinesh@icgeb.res.in within 15 days of publication of this advertisement. Kindly mark the email with subject “Application for BIF-RA-2013”

Closing date for applications: 18 October 2013

Only short listed candidates will be invited for an interview at ICGEB.

No TA/DA will be paid for attending the interview.

Advertisement: http://www.icgeb.org/tl_files/Vacancies/BIF-RA-Advt.pdf

Applications on plain paper along with details of CV (relevant photocopies of their
qualifications/experience and reprints of published work to be attached) are invited from qualified candidates for Research Fellowship in CSIR- sponsored research project.

JRF/SRF/RA (one vacancy)

CSIR sponsored “In silico design, identification and in vitro validation of lead molecule inhibitors to Bcr-Abl kinase”

JRF: M.Sc in Chemistry/ Bioinformatics/ Biotechnology with I division and NET or GATE qualified

SRF: M.Sc in chemistry/ Bioinformatics/ Biotechnology with at least two years of post- M.Sc research experience as evidenced from published papers in standard refereed journals in relevant area

RA: PhD in chemistry/ Bioinformatics/ Biotechnology with research experience in
relevant area.

As per CSIR guidelines

Notes:
1) You may visit the University of Hyderabad website www.uohyd.ernet.in to learn more about the University of Hyderabad.
2) Applicants should note that the appointment to be made is purely temporary and there is no right for claiming for any regular appointment in the University.
3) No TA/DA will be paid for attending the interview or at the time of joining the post, if selected.
4) The application should be submitted by post/courier/in-person to the address given below on or before November 1st 2013.

Prof. Lalitha Guruprasad
W-103, Gurbakhsh Singh Building
School of Chemistry
University of Hyderabad
Hyderabad- 500 046
5) Short-listed candidates will be called for interview at a short notice.

Advertisement: http://www.uohyd.ac.in/images/recruitment/chemisry_advt_101013.pdf

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AGORA is used to generate ancestral genomes for the Genomicus online server for gene order comparison, and has been in constant use in the group since.

Address of the bookmark: https://github.com/DyogenIBENS/Agora

Available immediately until 30th November 2015, to work on the development of bioinformatics approaches to aid analysis of data derived from the metabolomic profiling of biological matrices. The successful applicant will lead research activities on an FP7 funded EU-wide collaborative project aimed at establishing biomarker-based strategies for high throughput diagnostic screening. Key tasks will involve multivariate analysis of large datasets, bioinformatic-based selection and validation of identified markers, construction of metabolomic spectral profile databases and development of machine learning/database searching approaches amenable to analytical screening techniques. This position will offer the opportunity to travel and undertake work with project collaborators based in the Republic of Ireland and Europe.

Informal enquiries may be directed to Dr Terry McGrath, email: terry.mcgrath@qub.ac.uk.

Anticipated interview date: Thursday 31st October 2013
Salary scale: £30,424 – £39,649 per annum (including contribution points)
Closing date: Monday 21st October 2013

Telephone (028) 90973044 FAX: (028) 90971040 or e-mail on personnel@qub.ac.uk

The University is committed to equality of opportunity and to selection on merit. It therefore welcomes applications from all sections of society and particularly welcomes applications from people with a disability.

Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.

More @ https://hrwebapp.qub.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=5616943npO&WVID=6273090Lgx&LANG=USA

Following are the list of Ancestral /sequence/ reconstruction (ASR) tools: 

inferCars

Reconstructs contiguous regions of an ancestral genome. Given information about adjacencies between conserved segments in each modern species, our goal is to infer segment order in the ancestral genome. To get a clean and precise statement of the problem, we formalize it using graph theory. We develop an algorithm that identifies a most parsimonious scenario for the history of each individual adjacency, although the whole-genome prediction is not guaranteed to optimize traditional measures like the number of breakpoints. We introduce weights to the graph edges to model the reliability of each adjacency.

ANGES:reconstructing ANcestral GEnomeS maps

A suite of Python programs that allows reconstructing ancestral genome maps from the comparison of the organization of extant-related genomes. ANGES can reconstruct ancestral genome maps for multichromosomal linear genomes and unichromosomal circular genomes. It implements methods inspired from techniques developed to compute physical maps of extant genomes.

Cocos

Constructs phylogenies of multi-domain proteins. With a given species tree and domain phylogenies, the procedure infers the composition of ancestral multi-domain proteins. Cocos implements and extend a suggested algorithmic approach by Behzadi and Vingron in an easy-to-use program. Such method could be applied to reconstruction of partial homologous units such as bacterial operons or protein complexes.

MySSP

Constructs an initial DNA sequence at the root of the tree and simulates evolution across the tree using a variety of common models of DNA evolution. MySSP is a program for the simulation of DNA sequence evolution across a phylogenetic tree. It is designed for large-scale studies, including simulation of multiple replicates and outputs sequences into NEXUS, MEGA, or FASTA formats. MySSP has a fairly simple graphical user interface (GUI) for basic use, but also has a specialized batch script interpreter to allow for more complicated or large-scale simulations.

PARANA: Parsimonious Ancestral Reconstruction And Network Analysis

Performs parsimony based inference of ancestral biological networks. Given multiple extant networks and phylogenetic information relating extant nodes, PARANA finds a parsimonious set of ancestral interaction events (edge gains and losses) which explain the extant networks. The framework adopted by PARANA is able to represent network evolution under models that support gene duplication and loss and independent interaction gain and loss. The method works on both directed and undirected networks and can incorporate asymmetric interaction gain and loss costs. In contrast to previous approaches, PARANA does not require knowing the relative ordering of unrelated duplication events and thus, works on phylogenetic trees even where branch lengths are not provided.

GapAdj: Gapped Adjacencies

A synteny-based method that is flexible enough to handle a model of evolution involving whole genome duplication events, in addition to rearrangements, gene insertions, and losses. Ancestral relationships between markers are defined in term of Gapped Adjacencies, i.e. pairs of markers separated by up to a given number of markers. It improves on a previous restricted to direct adjacencies, which revealed a high accuracy for adjacency prediction, but with the drawback of being overly conservative, i.e. of generating a large number of contiguous ancestral regions (CARs).

ANCESTOR

A web server allowing one to easily and quickly perform the last three steps of the ancestral genome reconstruction procedure. Ancestors implements several alignment algorithms, an indel maximum likelihood solver and a context-dependent maximum likelihood substitution inference algorithm. The results presented by the server include the posterior probabilities for the last two steps of the ancestral genome reconstruction and the expected error rate of each ancestral base prediction.

ProCARs

Reconstructs ancestral gene orders as contiguous ancestral regions (CARs) with a progressive homology-based method. ProCARs runs from a phylogeny tree (without branch lengths needed) with a marked ancestor and a block file. This homology-based method is based on iteratively detecting and assembling ancestral adjacencies, while allowing some micro-rearrangements of synteny blocks at the extremities of the progressively assembled CARs. The method starts with a set of blocks as the initial set of CARs, and detects iteratively the potential ancestral adjacencies between extremities of CARs, while building up the CARs progressively by adding, at each step, new non-conflicting adjacencies that induce the less homoplasy phenomenon. The species tree is used, in some additional internal steps, to compute a score for the remaining conflicting adjacencies, and to detect other reliable adjacencies, in order to reach completely assembled ancestral genomes.

FastML

A user-friendly tool for the reconstruction of ancestral sequences. FastML implements various novel features that differentiate it from existing tools: (i) FastML uses an indel-coding method, in which each gap, possibly spanning multiples sites, is coded as binary data. FastML then reconstructs ancestral indel states assuming a continuous time Markov process. FastML provides the most likely ancestral sequences, integrating both indels and characters; (ii) FastML accounts for uncertainty in ancestral states: it provides not only the posterior probabilities for each character and indel at each sequence position, but also a sample of ancestral sequences from this posterior distribution, and a list of the k-most likely ancestral sequences; (iii) FastML implements a large array of evolutionary models, which makes it generic and applicable for nucleotide, protein and codon sequences; and (iv) a graphical representation of the results is provided, including, for example, a graphical logo of the inferred ancestral sequences.

maxAlike

Reconstructs a genomic sequence for a specific taxon based on sequence homologs in other species. The input is a multiple sequence alignment and a phylogenetic tree that also contains the target species. For this target species, the algorithm computes nucleotide probabilities at each sequence position. Consensus sequences are then reconstructed based on a certain confidence level.

MLGO: Maximum Likelihood for Gene Order Analysis

A web tool for the reconstruction of phylogeny and/or ancestral genomes from gene-order data. MLGO was designed for analysis of large-scale genomic changes including not only rearrangements but also gene insertions, deletions and duplications. MLGO can be used to infer a phylogeny from genome rearrangement and gene order data, and can also obtain an estimation of ancestral genomes, given an input tree. MLGO takes the advantage of binary encoding on gene-order data, supports a fairly general model of genomic evolution (rearrangements plus duplications, insertions, and losses of genomic regions), and successfully accommodates itself into the framework of maximized likelihood.

Image Reference : Wiki

(INDIAN COUNCIL OF MEDICAL RESEARCH)

P.O BOX 101,
Dr. M. Miyazaki Marg,
Tajganj, Agra - 282001

Applications are invited for a walk-in interview to be held in the Seminar Hall of the on 15th November, 2013, 9:30 am for temporary positions of JRF, Lab Technician and Field attendant in a ICMR funded project entitled "Elucidating the strain differentiation and transmission dynamics of M. leprae through simple sequence repeats ISSR-PCR marker"

1. JRF (one Post)

Essential qualification: Candidates with M.Sc/IVI.Tech or equivalent degree in any life science related subjects with UGC-CSIR/ICMR/DBT-Net qualified

Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.

Age. Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rs. 6,000 + 20% HRA per Month

2. Lab Technician (One Post)

Essential Qualification: 12th with DMLT/B.SCA4.SC in Life sciences

Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.

Age: Maximum 30 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rs13,760/ Per Month

3. Field Attendant (One Post)

Essential Qualification: 10th Pass

Desirable Qualification: Experience in field work

Age: Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rsl2,040l Per Month

Terms: posts are purely temporary. Appointment will be initially made for a period of one (01) year and may be extended further based on the performance of the candidate up to completion of the project.

Application & Selection procedure: candidates have to appear in the walk-in-interview in person along with an application/CV on plain paper giving details of at educational qualificationq experience and submit photocopies of relevant documents at the time of interview. Selection will be based on the performance of the candidate in the interview' Candidates will not be sent any interview call letter separately. No TA/DA will be paid to the candidate for appearing in the interview. selection is not possible without appearing in the interview. All candidates must report by 9:00am on the date of interview. Advance copy of CV may be sent to m.sarathipartha@gmail.com

Advertisement: http://www.jalma-icmr.org.in/P_S_M_advertisment.pdf

Deadline for applications : January 15, 2014.

Description :

We seek a talented and motivated post-doc to develop computational methods for inferring the molecular basis of genetic diseases by integration of personal omics data. Research topics include: identifying causal mutations of rare disease patients by meta-analysis; inferring disease-causing molecular pathways from genotype, human phenotypes, and omics profile of patient-derived cell lines; and causal inference from longitudinal omics studies of patients. The developed methods will be applied to analyze data from our medical collaborators.

Candidates must either hold a PhD in computational biology or bioinformatics, or hold a PhD in physics, statistics, or applied mathematics with practical experience with high-dimensional data analysis. Experience in quantitative genetics is a plus. Applicants must have a proven publication record and an interest for translational research.

The Gagneur lab is a young, lively and multidisciplinary group with a research focus on systems genetics and gene regulation. It is located at the Gene Center of the LMU (University of Munich), an interdisciplinary institution whose 16 independent research groups investigate the regulation of gene expression at all levels - from the underlying molecular mechanisms to the biological system. The institute is located on the biomedical research campus Munich-Grosshadern, offering a dynamic, interactive and internationally oriented research environment. The dynamism of Munich and the proximity of the Alps provide an excellent quality of life.

The salary is according to the TV-L (German academic salary scale).
Applications including a cover letter, CV, and references must be sent by January 15th 2014 to Julien Gagneur (gagneur@genzentrum.lmu.de)

About the lab: http://www.gagneur.genzentrum.lmu.de

It efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.

GeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at http://lce.biohpc.swmed.edu/geneck

Address of the bookmark: http://lce.biohpc.swmed.edu/geneck/