TOM 13.09.2017

Venue: Biomedicum 1, Meeting room 8-9, P-floor

Timing: 15:30 onwards

Presenter: Mehreen Ali, PhD student, FIMM

Missing data imputation methods in proteomic datasets

Mass spectrometry (MS)-based proteomic profiling has the potential to study comprehensive protein profiling of biological samples and thus has shifted the focus of research from qualitative to quantitative analyses. MS-based proteomics provide opportunity for more global profiling of post-translational modifications, in terms of yielding proteome-wide information about cancer cell signaling activity that is not accessible by genomics or transcriptomics alone. 

However, a substantial amount of data is missing at peptide/protein level primarily due to low-abundance peptides and/or poor ionization. Missing values in proteomics datasets limit the information extraction from proteomics datasets using statistical and machine learning methods, and thus have detrimental effect on downstream analyses.

In this talk, I will give a general overview of imputation methods adapted for proteomics datasets

TOM 16.08.2017

Venue: Biomedicum 1, Meeting room 8-9, P-floor

Timing: 15:30 onwards

Presenter: Lea Urpa, FIMM-EMBL Rotation PhD student, FIMM

FocusedMDS: Interactive, intuitive visualization of high-dimensional data

Dealing with high-dimensional data is increasingly necessary in biological sciences. When the number of features or measures in a dataset far outnumbers the individuals measured (ie gene expression data, patient registry data), discovering structures and relationships in the data can be challenging. Existing widely-used visualization methods may also give misleading representations. We present focusedMDS, an intuitive, interactive multidimensional scaling tool for high-dimensional data exploration. If time allows, we will also introduce FINEMAPviewer, an interactive visualization tool for GWAS and FINEMAP results.

TOM Fall schedule 2017

Tentative schedule for Fall session 2017

Date Presenter  Title of presentation
16.08 Lea Urpa

FocusedMDS: Interactive, intuitive visualization of high-dimensional data


Mehreen Ali 

Missing data imputation methods in proteomic datasets

Andres Veidenberg

 Web-based evolutionary sequence analysis with Wasabi

Balaguru Ravikumar

C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms


Chiara Facciotto

Interactive Visualization in R using Shiny and Plotly


ILS Mentor of the year 2016

On May 8th, the ILS Doctoral Program announced the awards for Mentor of the year 2016. Last fall, the ILS student council invited nominations from all ILS students, asking them to describe the appreciable qualities of their mentors.

A total of 8 nominations were received, highlighting the positive aspects of the mentors such as:

  • Letting the student to be independent
  • Letting them make decisions regarding their projects
  • Giving importance to brainstorming regarding the students project, especially in the beginning
  • Being excited about the students project
  • Motivating the students in the face of negative results
  • Availability
  • Having a social and friendly relationship with the student

Dr. Krister Wennerberg and Dr. David Fewer were chosen as the mentors of the year, based on the testimonials. Krister Wennerberg is a PI at the Institute for Molecular Medicine Finland (FIMM) and David Fewer works at the Division of Microbiology and Biotechnology, Department of Food and Environmental Sciences.

The awardees mentioned in their acceptance speech that they were extremely honored by receiving this award. They think that as a PI it’s also their responsibility to train the next generation of scientists, and a good way to do this is to get the students to be excited about their projects so that they are the ones who are driving it forward. And the best way to do that is to discuss about ideas and brainstorm with the students and let the student figure the way out himself/herself.

Nominations also included Eija Jokitalo (EM Unit, BI), Maarja Mikkola (Developmental Biology Program, BI), Susanna Fagerholm (Biosciences), Frederic Michon (Developmental Biology Program, BI), Andrii Domanskyi (BI), Eeva Sievi (DS Health) and Erkki Raulo (ILS) who were also acknowledged and felicitated at the event.

We congratulate both mentors and nominees and wish them to keep up their good work as role models.

ILS Student Council


Student in Spotlight – Pia Kinaret


Pia Kinaret is a PhD student at the Institute of Biotechnology, in the research group led by Dario Greco. She is studying alternative approaches for nanomaterial safety assessment, and has recently published an article on this topic. Congratulations Pia!

A suitable alternative for nanomaterial toxicity testing

Research digest:

The world is going nano! Nanoscience is a very rapidly growing field of research. Nanotechnology, nanostructure and nanoparticles are now commonplace terms and have revolutionized various aspects of our daily lives. Nanomaterials are already being used in cosmetics, cleaning products and our food, and have the potential to make supercomputers that will fit in our pockets. One very promising area is the use of nanoparticles as vehicles for drug delivery to targeted tissue sites such as tumor. But, how grave are the consequences when these particles pile up in the environment or inside us?

Technically, nanomaterials are any particles with at least one dimension less than 100 nanometers. The inherent shape and size of the nanomaterials makes them an oddball for our immune system to handle. Similar to asbestos, inhaled nanomaterials can be hazardous; cause severe asthma-type symptoms, granuloma formation, fibrosis and cardiovascular diseases. As the number of engineered nanomaterials is increasing exponentially, understanding the physiological effects of exposure to nanomaterials and developing toxicity standard for nanomaterials is of great importance. Therefore, Pia and colleagues [1] have studied an efficient and cost-effective method to assess nanomaterial toxicity.

The most common route of human exposure to nanomaterials is through respiration. State-of-the-art method for studying the airway-exposure of nanomaterials is via inhalation method, in which lab mice are exposed to aerosolized nanomaterial. However, this is cumbersome and time-consuming. Alternatively, this could be studied by oropharyngeal aspiration, in which the nanomaterial is introduced to animal airways as a liquid dispersion. Aspiration is much faster and cost-effective method compared to inhalation, however it is not yet clear whether the two methods are comparable.

Pia [1] studied the responses of lab mice exposed to carbon-based nanomaterials by inhalation and aspiration method at various doses. She found that the immune responses of the mice at low doses of aspiration were comparable to that of inhalation. Also, the responses at molecular level in terms of the gene expression changes and induced biological functions were also very similar. Pia thus concludes that aspiration is a valid alternative to the inhalation method for assessment of nanomaterial toxicity.

  1. Inhalation and Oropharyngeal Aspiration Exposure to Rod-Like Carbon Nanotubes Induce Similar Airway Inflammation and Biological Responses in Mouse Lungs. Kinaret P, Ilves M, Fortino V, Rydman E, Karisola P, Lähde A, Koivisto J, Jokiniemi J, Wolff H, Savolainen K, Greco D, Alenius H. ACS Nano. 2017 Jan 24;11(1):291-303.


TOM 10.05.2017

Venue: Biomedicum 1, Meeting room 3, P-floor

Timing: 15:30 onwards

Presenter: Abhishekh Gupta, Post-doc, Group Aittokallio, FIMM

Drug response quantification: past, present and future

Quantifying drug response is crucial for assessing vulnerabilities of cancer cells, and plays an important role in drug discovery.  In this talk, I will present state-of-the-art methods to infer drug response from high-throughput drug screening experiments. In addition, I will illustrate a novel Normalized Drug Response (NDR) metric which realistically captures full-spectrum of the drug-induced effects. The drug sensitivity scores based on this metric are able to precisely capture the drug’s biological behavior, aiding the differentiation of drugs as into distinct drug-classes, namely lethal, sub-effective, effective and growth-stimulatory.

TOM 05.04.2017

Venue: Biomedicum 1, Meeting room 5-6, 3rd Floor

Timing: 16:00 onwards

Presenter: Alok Jaiswal, PhD student, FIMM

Methods for analyzing genome-wide loss-of-function screening data

Loss-of-function techniques, such as RNAi and CRISPR, are widely used for gene silencing. These experimental methods have been extensively applied in establishing gene function in biological processes, identification of therapeutic drug targets and vulnerabilities of cancer cells. In this talk, I will describe about statistical methods that are used to analyse genome-wide loss-of-function datasets.

TOM 08.03.2017

Venue: Biomedicum 1, Meeting room 8-9, P floor

Timing: 15:30 onwards

Presenter: Dr. Ari Löytynoja, Group Leader, Institute of Biotechnology

Generalised model of local template switch mutations

Replication-related template switch mutations are known to create short,
perfect inverted repeats in bacteria. We developed a generalised model
(the four point mutation model; 4PM) that describes local template
switches in DNA replication. Using this model, we studied the mutation
clusters in human and primate sequence data and found that large numbers
of these are caused by template switch events. The 1000 Genomes data
show that 4PM events segregate in human populations and the Icelandic
trio data contain de novo 4PM events. I describe the 4PM alignment
algorithm and the computational analyses involved in the study
( I will then
discuss what the findings mean for reference-based sequencing studies
and for the evolution of genomes.

TOM 08.02.2017

Venue: Biomedicum 1, Meeting room 5-6, 3rd Floor

Timing: 15:30 onwards

Presenter: Dr. Matti Kankainen, Bioinformatics Team, FIMM

Best practices in RNA-seq data analysis

RNA sequencing (RNA-seq) has become an indispensable tool to characterize transcriptomes and understand the molecular indicators of disease and treatment. It is a powerful technology to study gene expression and discover novel isoforms, in addition to which RNA-seq has proven to be highly useful technique to discover expressed coding variants, deep intronic mutations, and fusion-transcripts. In this talk, I will describe how we at the FIMM sequencing center process RNA-seq data from model organisms and will give a sneak preview to the upcoming new analysis features we are developing at the moment.

TOM Spring schedule 2017

Tentative schedule for Spring session 2017

Date Presenter       Title of presentation
08.02 Matti Kankainen Best practices in RNA-seq data analysis

Ari Löytynoja

Generalised model of local template switch mutations

05.04 Alok Jaiswal

Methods for analyzing loss-of-function screening data

10.05 Julia Casado

Single-cell data analysis framework