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

Qualifications : Ph. D.

Desirable : Experience on DNA Markers, plant genome mapping and bioinformatics

No. of Post : 03

Department : Genetics

Salary : Rs. 60,000/-
How to apply

The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room. Applicants are requested to bring all related documents, in original and a set of photocopy, for verification. Date and time of the interview : 25.06.2015 at 10:30 AM.

Click Here for Job Details http://www.du.ac.in/du/index.php?mact=News,cntnt01,detail,0&cntnt01articleid=5492&cntnt01returnid=83

sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config

On MacOS, the Apple Developer tools and Fink (or MacPorts or Brew) must be installed, then:

sudo fink install bzip2-dev pkgconfig

Address of the bookmark: https://github.com/neufeld/pandaseq

Applications are invited from individuals who have high motivation to do research for the below mentioned position,

1. Research Associate - 1 No.
in the DBT sponsored project under the supervision of Dr. D. Prabaharan, Principal Investigator, National Facility for Marine Cyanobacteria, Dept. of Marine Biotechnology, Bharathidasan University, Tiruchirappalli-24.

Title of the Project: “Establishment of National Repository for Micro algae & Cyanobacteria” funded by Department of Biotechnology, Govt. of India

Qualification

1. Research Associate – 1 No. Rs. 36,000/38,000/40,000 per month for I, II and III year + 20% HRA

Essential : Doctoral degree in relevant subject from recognized University/ Institutes
Desirable: Research experience in molecular biology and bioinformatics

Interested candidates can send their complete CV in plain paper with a passport size photograph, with details of Marks secured in all subjects from plus two stage (with proof, full postal address, sex, date of birth, community etc., along with additional qualification or experiences and two address of references whom could be contacted (One of whom should be PG teacher/guide). Application should reach the Principal Investigator on or before 30.06.2015 by Email (nfmcbic@yahoo.com)/Registered post/ Speed post, with subject subscribed as “Application for Research Associate /Technical Assistant /Lab attendant”. Qualifying candidates will be short listed and communicated with date of interview. No TA and DA will be given for attending the interview. Addressfor Communication Dr. D. Prabaharan Principal Investigator National Facility for Marine Cyanobacteria Bharathidasan University Tiruchirappalli-620024, Tamil Nadu.

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Current research interests include next-generation DNA sequencing, structural variation, genome rearrangements in cancer and evolution, and network analysis of somatic mutations in cancer. Earlier research included topics in comparative genomics, multiple sequence alignment, and motif finding.

More athttp://compbio.cs.brown.edu/

The candidate is expected to have experience in handling functional genomics tools to dissect defense responses against bacterial pathogens and drought stress tolerance. This project may involve use of bioinformatics tools, database development, large scale transcriptome profiling, virus-induced gene silencing and any other research work as assigned by the PI.

Qualification: Candidates having a Ph. D. degree in Bioinformatics/Plant Molecular Biology/Plant Physiology/Plant Pathology/Plant Breeding & Genetics and strong publication record can apply. Candidates having prior work experience in using advanced molecular biology tools in laboratory with strong bioinformatics knowledge are preferred.

The Fellowship amount for the position will be given at par with the similar fellowships by DBT/DST.

NIPGR reserves the right to select the candidate against the above post depending upon the qualifications and experience of the candidate. Reservation of post shall be as per Govt. of India norms.

Eligible candidates may apply by sending hard copy of complete application in the given format with a cover letter showing interest and specifying the position. The attested copies of the mark-sheets, certificates, proof of research experience/publications are to be attached. The application should reach at the address given below within 15 days from the date of advertisement. The envelope must be superscribed by "Application for the post of RA under NIPGR Short-term research fellowship programme". No TA/DA will be paid for attending the interview.

ONLY hard copy of the application in the given format will be accepted.
www.nipgr.res.in/files/careers/format_RA2.doc

Dr. Senthil-Kumar Muthappa
Staff Scientist - III,
National Institute of Plant Genome Research (NIPGR)
Aruna Asaf Ali Marg, P.O. Box NO. 10531,
New Delhi - 110067

More at http://biorg.cis.fiu.edu/

Assam Applications are invited for Walk-in-Interview for the following temporary positions in the MHRD sponsored Centre of Excellence under FAST project entitled “Machine Learning Research and Big Data Analysis” under the Principal Investigator Professor D.K. Bhattacharyya, Department of Computer Science & Engineering, Tezpur University.

Position : Senior Research Fellows (SRFs) in the field of (i) Bioinformatics (ii) Natural Language Processing / Speech Processing (iii) Cognitive Radio Networks / Optical Networks (iv) Network Security. No. of Positions : Five (05).

Qualification : First class in ME / M. Tech. in CSE / IT / ECE with research experience in relevant fields of research. Candidates having valid GATE / NET score shall be preferred.

Fellowship : Rs. 18,000/- (Rupees Eighteen Thousand) only per month.

Duration : Two (02) years and may be extended depending on status of the project.

Position : Junior Research Fellows (JRFs) in the field of Bioinformatics

No. of Positions : One (01).

Qualification : First class in B. Tech. in CSE / IT/ ECE or MCA with consistently good academic records. Candidates with M. Tech. in CSE / IT / ECE shall be preferred.

Fellowship : Rs. 12,000/- (Rupees twelve Thousand) only per month.

Duration : Two (02) years and may be extended depending on status of the project.

Interested candidates may send their application on plain paper by post along with his/her educational qualifications, research experience certificates (for Senior Research Fellow), 02 copies of recent passport/stamp size photograph and contact phone number to Prof. D.K. Bhattacharyya, Principal Investigator, Department of Computer Science & Engineering, Tezpur University, Napaam- 784028 or mail it to dkb@tezu.ernet.in (or to smh@tezu.ernet.in) within 15 days of publication of this advertisement.

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Applications are invited for the post of Senior Research Fellow- SRF (one) and Junior Research Fellow- JRF (one) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong.

Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite.

For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by publications.

Students waiting for their last semester result can apply for JRF position.

Stipend: As per SERB norms.

Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 01.08.15. The hard copy is not required at this stage.

The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. P.S: Students applied for the same post as per date 01.06.15, need not to apply again as their application will be considered in this advertisement also.

For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com

Dr. Timir Tripathi Principal Investigator DST-SERB Project Department of Biochemistry NEHU, Shillong

Advertisement: www.nehu.ac.in/Advertisements/BiochemPVAdvtTT_200715.pdf

Eligibility : MSc(Bio-Chemistry, Bio-Informatics, Bio-Tech)

Location : Chennai

Last Date : 20 Aug 2015

Hiring Process : Walk - In
Alagappa University - Job Details

RA Bioinformatics Job position in Alagappa University

Qualification: M.Sc., in Bioinformatics/Biotechnology/Biophysics/Biochemistry/ Life Sciences

No.of Post: One

Salary : Rs. 11000
How to apply

A walk-in Interview will be held at the Department of Biotechnology, Alagappa University, Science Campus, Karaikudi 630 004 on 20.08.2015 (Thursday) at 10.30 AM.

Interested candidates are encouraged to send their Curriculum Vitae by email in advance. On the day of interview, the candidates must produce original certificates in proof of their educational qualification and experience and a recommendation letter from the Head of the Department/Institution where last studied/worked. Candidates who have already passed the required Degree alone are eligible to appear for interview.

Click Here for more http://alagappauniversity.ac.in/files/news_files/Notification.pdf